CN117592948B

CN117592948B - Construction project early warning method, system, device and storage medium

Info

Publication number: CN117592948B
Application number: CN202410075220.4A
Authority: CN
Inventors: 赵燚; 周平江; 张伟
Original assignee: Yizhi Technology Chengdu Co ltd
Current assignee: Yizhi Technology Chengdu Co ltd
Priority date: 2024-01-18
Filing date: 2024-01-18
Publication date: 2024-04-26
Anticipated expiration: 2044-01-18
Also published as: CN117592948A

Abstract

The invention provides a construction project early warning method, a system, a device and a storage medium, wherein the method comprises the steps of obtaining acceptance information of a minimum production unit and record information of a task list in a plurality of task procedures of a construction project, wherein the minimum production unit comprises space information, component information and task item information, and each minimum production unit corresponds to one final task item corresponding to a component unit in one space unit; predicting a progress of at least part of the unfinished task process based on the acceptance information and/or the labor information; and sending out early warning in response to the pushing progress not meeting the preset condition. The method can be realized through a construction project early warning device. The method may also be run after being read by computer instructions stored on a computer readable storage medium.

Description

Construction project early warning method, system, device and storage medium

Technical Field

The present disclosure relates to the field of construction management, and in particular, to a method, a system, an apparatus, and a storage medium for early warning of construction projects.

Background

Construction progress is the main dimension of construction industry field management, and construction quality, safety, technology, cost, materials, machinery and contracts are all related to construction progress, but the existing progress management mode is difficult to meet management requirements. The current mainstream progress management mode mainly measures the construction progress by manually observing whether key nodes are finished or not, and only the completion condition can be expressed by a Boolean value or a percentage, so that the construction progress is fuzzy and difficult to quantify, cannot be used for calculation of a computer, and cannot guarantee the authenticity and accuracy of the construction progress. Before the progress risk explodes, no precursor is usually available, and only the management experience of the manager can be used for prejudgment, so that an effective progress and cost early warning method is lacked.

Therefore, it is desirable to provide a construction project early warning method, system, device and storage medium, which can effectively realize effective early warning of construction progress.

Disclosure of Invention

One of the invention provides a construction project early warning method, which comprises the following steps: acquiring acceptance information of a minimum production unit and record information of a task list in a plurality of task procedures of a construction project, wherein the minimum production unit comprises space information, component information and task item information, and each minimum production unit corresponds to one final task item corresponding to a component unit in one space unit; predicting a progress of at least part of the incomplete task process based on the acceptance information and/or the labor logging information; and responding to the pushing progress not meeting the preset condition, and sending out early warning.

One of the present disclosure provides a construction project warning system, the system comprising: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring acceptance information of a minimum production unit and record information of a task list in a plurality of task procedures of a construction project, the minimum production unit comprises space information, component information and task item information, and each minimum production unit corresponds to one final task item corresponding to a component unit in one space unit; the prediction module is used for predicting the progress of at least part of unfinished task procedures based on the acceptance information and the labor information; and the early warning module is used for sending early warning in response to the pushing process does not meet the preset condition.

One of the aspects of the invention provides a construction project early warning device, which comprises at least one processor and at least one memory; the at least one memory is configured to store computer instructions; the at least one processor is configured to execute at least some of the computer instructions to implement a construction project pre-warning method.

One aspect of the present invention provides a computer-readable storage medium storing computer instructions, the computer executing a construction project warning method when the computer reads the computer instructions in the storage medium.

The advantages of the above summary include, but are not limited to: whether the early warning is sent out is judged according to the difference between the actual cost consumption of the task list and the theoretical cost consumption, and whether the early warning is sent out can be judged according to the actual condition of the task list or the actual condition of the task procedure, so that when the actual condition is predicted to be inconsistent with the expected condition, the risk early warning is timely sent out, and the follow-up dynamic deduction of the construction process and the adjustment of the construction strategy are facilitated.

Drawings

FIG. 1 is an exemplary block diagram of a construction project pre-warning system shown in accordance with some embodiments of the present description;

FIG. 2 is a schematic diagram of an exemplary mobile device on which certain systems may be implemented, as shown in accordance with some embodiments of the present description;

FIG. 3 is a schematic diagram of exemplary hardware and software components of an exemplary computing device shown in accordance with some embodiments of the present description;

FIG. 4 is an exemplary flow chart of a construction project pre-warning method shown in accordance with some embodiments of the present description;

FIG. 5 is an exemplary flow chart of a progress of a predictive task process shown in accordance with some embodiments of the present disclosure;

FIG. 6 is one of exemplary diagrams of determining whether to issue an early warning according to some embodiments of the present disclosure;

FIG. 7 is a second exemplary diagram illustrating a determination of whether to issue an early warning according to some embodiments of the present disclosure;

FIG. 8 is a third exemplary diagram illustrating a determination of whether to issue an early warning according to some embodiments of the present disclosure;

FIG. 9 is an exemplary flow chart of determining a propulsion strategy for an incomplete task process, according to some embodiments of the present description;

10A-10D are exemplary diagrams of construction period-cost scatter plots according to some embodiments of the present description.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.

As used herein, a "system," "apparatus," "unit," and/or "module" is a means for distinguishing between different components, elements, parts, portions, or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

The terms "a," "an," "the," and/or "the" are not specific to the singular, but may include the plural, unless the context clearly indicates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.

A flowchart is used in this specification to describe the operations performed by the system according to embodiments of the present specification. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.

FIG. 1 is an exemplary block diagram of a construction project pre-warning system shown in accordance with some embodiments of the present description. In some embodiments, the construction project pre-warning system 100 may include an acquisition module 110, a prediction module 120, and a pre-warning module 130. In some embodiments, the acquisition module 110, the prediction module 120, and the pre-warning module 130 may be implemented by a processor.

In some embodiments, the acquisition module 110 may acquire acceptance information of a minimum production unit in a plurality of task processes of a construction project of the construction project and record labor information of a task sheet.

In some embodiments, prediction module 120 may predict a progress of the advancement of at least a portion of the incomplete task process based on the acceptance information and/or the labor information.

In some embodiments, prediction module 120 may determine an equivalent work efficiency and/or an equivalent cost for a first minimum production unit based on the acceptance information and/or the labor information in response to the minimum production unit being included within the task process, the first minimum production unit being the accepted minimum production unit; based on the equivalent work efficiency and/or the equivalent cost and the space information, determining the estimated work efficiency and/or the estimated cost of a second minimum production unit, wherein the second minimum production unit is an unverified minimum production unit; based on the estimated work efficiency and/or the estimated cost, a progress of the incomplete task process is predicted.

In some embodiments, the prediction module 120 may determine the equivalent work efficiency based on the actual work efficiency consumption of the job ticket and the number of first minimum production units the job ticket contains; and/or determining an equivalent cost based on the actual cost consumption of the job ticket and the number of first minimum production units the job ticket contains.

In some embodiments, the prediction module 120 may determine, based on the spatial information, a third minimum production unit and/or a fourth minimum production unit, the spatial positional relationship between the third minimum production unit and the second minimum production unit meeting the preset positional condition, the third minimum production unit being one or more of the first minimum production units, the fourth minimum production unit being one or more of the second minimum production units for which estimated work efficiency and/or estimated cost have been determined; and determining the estimated work efficiency and/or the estimated cost of the second minimum production unit through a preset algorithm based on the equivalent work efficiency and/or the equivalent cost of the third minimum production unit and/or the estimated work efficiency and/or the estimated cost of the fourth minimum production unit.

In some embodiments, the pre-warning module 130 may issue the pre-warning in response to the progress of the advancement not meeting a preset condition.

In some embodiments, the pre-warning module 130 may determine the estimated end time of the task process based on the estimated work efficiency of the second smallest production unit included in the task process; and sending out early warning in response to the estimated ending time being greater than the planned ending time of the task procedure.

In some embodiments, the pre-warning module 130 may determine remaining planning effort for the task process based on planning effort for the task process and acceptance information for the task process; determining a dominable work efficiency of a second minimum production unit included in the task process based on the remaining planning work efficiency; and sending out early warning in response to the estimated work efficiency of the second minimum production unit contained in the task procedure being greater than the available work efficiency.

In some embodiments, the pre-warning module 130 may determine the remaining required cost of the task process based on the estimated cost of the second smallest production unit contained within the task process; and sending out early warning in response to the remaining required cost being greater than the remaining planning cost of the task process.

In some embodiments, the pre-warning module 130 may determine a remaining planning cost for the task process based on the planning cost for the task process and the logging information for the task process; determining a dominant cost of a second minimum production unit contained within the task process based on the remaining planning costs; and sending out an early warning in response to the estimated cost of the second smallest production unit contained in the task procedure being greater than the available cost.

In some embodiments, the pre-warning module 130 may determine an associated task process of the task process in response to the minimum accepted production units not being included within the task process; determining estimated work efficiency and/or estimated cost of a second minimum production unit contained in the task process based on historical acceptance information and/or historical logging information of the associated task process; determining estimated end time and/or residual required cost of the task process based on estimated work efficiency and/or estimated cost of a second minimum production unit contained in the task process; and sending out early warning in response to the estimated ending time being greater than the planned ending time and/or the remaining required cost being greater than the remaining planned cost.

In some embodiments, the construction project pre-warning system 100 may include a planning module 140.

In some embodiments, planning module 140 may prompt the user for a push strategy to incomplete task procedures after issuing the pre-warning. In some embodiments, planning module 140 may determine an estimated end time for an incomplete task process; acquiring a first boundary condition between task procedures and a second boundary condition of a construction item; and determining a propulsion strategy of the unfinished task procedure based on the estimated end time, the first boundary condition and the second boundary condition.

In some embodiments, planning module 140 may determine a plurality of candidate propulsion strategies based on incomplete task procedures; determining a construction period index and a cost index of the candidate propulsion strategy based on the estimated end time, the first boundary condition and the second boundary condition; a propulsion strategy is determined based on the planning objectives and the construction period index and/or the cost index.

In some embodiments, the planning module 140 may determine the propulsion strategy based on the project index in response to the planning target being a project objective.

In some embodiments, the planning module 140 may determine the propulsion strategy based on the cost index in response to the planning goal being a cost goal.

In some embodiments, the planning module 140 may determine a cost-time curve corresponding to the candidate propulsion strategy based on the estimated work efficiency and/or the estimated cost of the second smallest production unit included in the incomplete task process; determining a cash flow time profile based on the cost time profile and the balance data; based on the cash flow time profile, a propulsion strategy is determined.

For more details on the acquisition module 110, the prediction module 120, the pre-warning module 130, and the planning module 140, see the following description.

It should be noted that the above description of the candidate display, determination system, and modules thereof is for descriptive convenience only and is not intended to limit the present description to the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the principles of the system, various modules may be combined arbitrarily or a subsystem may be constructed in connection with other modules without departing from such principles. In some embodiments, the acquisition module 110, the prediction module 120, the early warning module 130, and the planning module 140 disclosed in fig. 1 may be different modules in one system, or may be one module to implement the functions of two or more modules. For example, each module may share one memory module, or each module may have a respective memory module. Such variations are within the scope of the present description.

Fig. 2 is a schematic diagram of an exemplary mobile device on which certain systems may be implemented, as shown in accordance with some embodiments of the present description. In some embodiments, the client terminal device, which may be the mobile device 200, is configured to display and transmit information related to the construction progress. The mobile device may include, but is not limited to, a smart phone, tablet, music player, portable gaming device, GPS receiver, wearable computing device (e.g., glasses, watch, etc.), and the like. Mobile device 200 may include one or more Central Processing Units (CPUs) 240, one or more Graphics Processing Units (GPUs) 230, a display 220, a memory 260, a communication unit 210, a storage unit 290, and one or more input/output (I/O) 250. In addition, mobile device 200 may also include, but is not limited to, a system bus or any other suitable component of a controller (not shown in FIG. 2). As shown in fig. 2, a mobile operating system 270 (e.g., IOS, android, windows Phone, etc.) and one or more application programs 280 may be loaded from the storage unit 290 into the memory 260 for execution by the CPU 240. Application 280 may include a browser or other mobile application for receiving and processing information related to a query (e.g., construction progress) entered by a user in mobile device 200. The user may obtain information related to one or more search results via the system's I/O250 and provide the information to a server and/or other modules or units of the construction project pre-warning system 100.

To implement the various modules, units, and functions thereof described above, a computer hardware platform may be used as a hardware platform for one or more elements. Since these hardware elements, operating systems, and programming languages are general, it can be assumed that those skilled in the art are familiar with these techniques and that they can provide the information required for online-to-offline services according to the techniques described in this disclosure. A computer with a user interface may be used as a Personal Computer (PC) or other type of workstation or terminal device. If properly programmed, a computer with a user interface can be used as a server. It is believed that one skilled in the art will be familiar with the construction, programming, or general operation of computer devices of this type. Accordingly, no additional explanation is made with respect to the description of the drawings.

FIG. 3 is a schematic diagram of exemplary hardware and software components of an exemplary computing device shown in accordance with some embodiments of the present description. The computing device 300 may be configured to perform one or more functions of the various modules in the construction project pre-warning system 100 disclosed in embodiments of the present specification.

The computing device 300 may be a general purpose computer or a special purpose computer, both of which may be used to implement the construction project pre-warning system 100 of the present application. The computing device 300 may be used to implement any component of the construction project pre-warning system 100 according to the present application. For example, a processor may be implemented on computing device 300 by way of its hardware, software programs, firmware, or a combination thereof. For convenience, only one computer is shown, but the computer functions described herein in connection with the search service may be implemented in a distributed fashion across multiple similar platforms to spread out the processing load.

For example, computing device 300 may include a communication port 350 that connects to and/or from a network to enable data communication. Computing device 300 may also include one or more processors 320 in the form of a processor for executing program instructions. An exemplary computer platform can include an internal communication bus 310, different types of program memory and data storage (e.g., magnetic disk 370, read Only Memory (ROM) 330, or Random Access Memory (RAM) 340), and various data files for processing and/or transmission by a computer. The exemplary computer platform also includes program instructions stored in ROM 330, RAM 340, and/or other forms of non-transitory storage media for execution by processor 320. The methods and/or processes of the present application may be implemented as program instructions. Computing device 300 may also include input/output 360, which may support input/output between the computer and other components. Computing device 300 may also receive programming and data over a network communication.

Computing device 300 may also include a hard disk controller in communication with a hard disk, a keypad/keyboard controller in communication with a keypad/keyboard, a serial interface controller in communication with a serial interface device, a parallel interface controller in communication with a parallel interface device, a display controller in communication with a display, and the like, or any combination thereof.

For illustration only, only one CPU and/or processor is illustratively depicted in computing device 300. It should be noted, however, that computing device 300 of the present application may include multiple CPUs and/or processors, and thus, the operations and/or methods described in the present application as being implemented by one CPU and/or processor may also be implemented by multiple CPUs and/or processors, either jointly or independently. For example, if in the present application, the CPUs and/or processors of computing device 300 perform operations A and B, it should be understood that operations A and B may also be performed jointly or independently by two different CPUs and/or processors in computing device 300 (e.g., a first processor performing operation A, a second processor performing operation B, or both first and second processors performing operations A and B).

Fig. 4 is an exemplary flow chart of a construction project pre-warning method shown in accordance with some embodiments of the present description. In some embodiments, the process 400 may be performed by the construction project pre-warning system 100 or a processor. As shown in fig. 4, the process 400 includes the following steps.

Step 410, acquiring acceptance information of a minimum production unit and record information of a task sheet in a plurality of task processes of a construction project. In some embodiments, the acquisition module 110 or processor performs step 410.

In some embodiments, the construction project may include multiple types. Such as construction projects of the type of construction, decoration, installation, municipal, landscaping, etc.

A plurality of task items may be included in the construction project. Taking construction projects of the construction engineering class as an example, a plurality of tasks such as building a foundation, building a main body structure (e.g., wall, column, ceiling, etc.), building an elevator, building a drainage structure, building an electrical structure, finishing, etc. may be included. In some embodiments, the task items are divisible, and the processor can divide the task items into a plurality of subtask items when there is a corresponding processing need. For example, when a task item is to build a wall, the multiple subtask items it divides may be: cleaning and leveling a wall building position, watering and wetting bricks, paying off the bricks at the wall building position by using ink lines, preparing cement mortar, coating the cement mortar on the ground, placing a first layer of bricks, coating the cement mortar on the first layer of bricks, placing a second layer of bricks, scraping the cement mortar, correcting the bricks, installing corner lines and the like. In particular, the level of a task item may be a job level, i.e., a task item may correspond to at least one job required to complete the task item. For example, the task item may be a rebar job, the job for which is a rebar job. For another example, the task item may be to construct a wall, the type of work required of which includes a rebar worker, a cement worker, a tile worker, and the like.

A task process refers to a sequence of one or more minimum production units. In some embodiments, there is a production order for one or more minimum production units included in the task process. For example, a task process includes 3 minimum production units, and the existing production sequence may include: after the first minimum production unit is finished, the second minimum production unit can be performed; after the second minimum production unit is completed, the third minimum production unit can be performed.

The minimum production unit is a minimum unit for production management of workload, cost, working time, work efficiency, and the like of a construction project.

In some embodiments, the minimum production unit includes spatial information, component information, and task item information.

Each minimum production unit has corresponding spatial information. The space information refers to information related to a construction space of a construction project. Taking construction projects of building engineering as an example, the spatial information may include a construction area, the number of buildings, the number of floors, the floor area, the number of rooms on a floor, the room area of each room on a floor, and the like. In some embodiments, the obtaining module 110 or the processor may divide the construction space step by step according to the project portion, the unit project, the floor or the partition to which the construction project belongs, so as to obtain a plurality of space units. Each of the divided space units may correspond to a space range of a certain floor or a certain partition of a certain unit project of a certain project section. For example only, the spatial cell a may be a spatial extent of floor D in cell project C of project B. The division of the construction space is merely an exemplary illustration, and does not limit the embodiments.

Each minimum production unit has corresponding part information. The component information refers to information related to each component unit included in the construction project. The component units are objects or structures to be produced/constructed in construction projects, etc. Such as walls, railings, stairs, etc. Taking construction projects of the construction engineering class as an example, the component information thereof may include wall information (for example, a position, a thickness, an area, a material, a structure, etc. of a wall), column information (for example, a position, a number, a structure, a size, a material, etc. of a column), door and window information (for example, a position, a number, a structure, a size, etc. of a door and window), fence information (for example, a type, a position, a number, a structure, a size, etc. of a fence), and the like.

In some embodiments, the minimum production units corresponding to the plurality of final task items required to build one of the component units in a space unit may be aggregated into one task procedure in production order. Multiple task processes can be determined from different space units and different component units. In some embodiments, the minimum production units corresponding to the plurality of final task items in one of the task items in one space unit may be aggregated into one task procedure according to a production order. Multiple task processes may be determined from different space units, different task items. The task processes may also be aggregated in any other feasible manner.

In some embodiments, at least one task procedure may be determined in one spatial unit. In some embodiments, the number and/or types of task processes determined in different spatial units may be the same or different.

Some embodiments of the present disclosure facilitate the analytical determination and management of the progress of a construction project from the management dimension of the task process by aggregating a plurality of minimum production units contained in the construction project into at least one task process.

Each minimum production unit has corresponding task item information. The task item information refers to the relevant information of the final task item corresponding to the minimum production unit. For example, the task content of the final task item (e.g., wall building, cementing, etc.), a construction plan (e.g., plan start time, plan end time, etc.), and the like.

In some embodiments, the acquisition module 110 or the processor may acquire the task item, the spatial information of the minimum production unit, the part information, and the task item information of the construction project according to the input of the user. For example, the user may upload a contract list, a construction plan table, etc. of the construction project through the terminal device, and accordingly, the acquisition module 110 or the processor may extract a task item, spatial information, component information, and task item information of the minimum production unit of the construction project based on contents of the contract list, the construction plan table, etc.

In some embodiments, the acquisition module 110 or processor may read the task item, the spatial information of the minimum production unit, the component information, and the task item information of the construction project from the storage device. The storage device may be a storage device of the construction project early warning system 100, or may be an external storage device that does not belong to the construction project early warning system 100, for example, a hard disk, an optical disk, or the like. In some embodiments, the acquisition module 110 or processor may read the task item, the spatial information of the minimum production unit, the component information, and the task item information of the construction project through interfaces including, but not limited to, a program interface, a data interface, a transmission interface, and the like. In some embodiments, the construction project pre-warning system 100 may automatically extract the task items of the construction project from the interface, the spatial information, the component information, and the task item information of the minimum production unit when in operation. In some embodiments, the construction project pre-warning system 100 may be invoked by an external device or system, which upon invocation is communicated to the construction project pre-warning system 100. In some embodiments, the task item, the spatial information of the minimum production unit, the component information, and the task item information of the construction project may also be obtained in any manner known to those skilled in the art, which is not limited in this specification.

In some embodiments, each minimum production unit corresponds to a final task item corresponding to a component unit in a spatial unit.

The last-level task item refers to a last-level sub-task item in the task items, which is not divisible. Taking construction projects of building engineering as an example, when a task is used for building a wall, the subtask items such as 'cleaning and leveling a wall building position', 'watering and wetting bricks', 'paying off with ink lines at the wall building position', and the like can not be divided any more, and the subtask items can be regarded as final subtask items. It should be noted that "partitionable" and "non-partitionable" referred to in the embodiments of the present specification refer to whether or not they are sub-partitionable in terms of construction skills required to complete the sub-task item. Specifically, one work category includes at least one construction skill under the work category, and a worker can be assigned to the work category to which the construction skill corresponds only when any one construction skill is provided. Taking the work type as a reinforcing steel bar work example, the construction skills under the work type can comprise reinforcing steel bar rust removal, reinforcing steel bar straightening, reinforcing steel bar connection and the like, and the reinforcing steel bar rust removal, reinforcing steel bar straightening and reinforcing steel bar connection can not be divided into lower-level construction skills, so that the reinforcing steel bar rust removal, reinforcing steel bar straightening and reinforcing steel bar connection respectively correspond to a final-stage task item. It should be understood that some construction skills may have multiple levels, and that the construction skill corresponding to the final task item is the last construction skill.

A space unit refers to a space range in a space partition for building/producing a component unit. Each space unit may be used to build/produce one or more component units.

In some embodiments, a task item that produces/builds a component unit may be composed of one or more subtask items. For example, a task item for building a wall may be made up of multiple subtask items as exemplified above, each of which cannot be subdivided, i.e., one subtask item may be considered a final task item. Accordingly, each minimum production unit may correspond to a final task item corresponding to a component unit in a space unit. By way of example only, a space unit is a space range of building "wall 1 of component a in floor 1 of unit project 1 of project department 1," wall 1 "is a component unit corresponding to the space unit, and the final task item corresponding to the component unit may include: "clean and level the wall location", "wet the brick", "pay out with ink lines at the wall location", etc., each of these final tasks may correspond to a minimum production unit.

In some embodiments, different component units may include partially identical final task items. When the space units to which the same final task items belong are different, the corresponding minimum production units are different.

In some embodiments of the present disclosure, the same final task item belonging to different spatial units is divided into different minimum production units, so that task management at a spatial level can be implemented, and a management party is facilitated to grasp task execution conditions in each spatial unit.

In some embodiments, the minimum production units may be dispatched to the worker in the form of a job ticket. The acceptance information refers to information related to the acceptance of the job ticket. In some embodiments, the acceptance information includes one or more of an actual progress (e.g., accepted or not accepted, etc.), an actual ergonomic consumption, an actual production time, etc. of each minimum production unit in the job ticket. When the minimum production unit is accepted, indicating that the minimum production unit is finished; when the minimum production unit is not verified, it indicates that the minimum production unit is not completed. The actual production time of the minimum production unit comprises an actual start time, an actual end time and/or an actual time consumption of the minimum production unit. When the minimum production unit is not finished, the actual finishing time is unknown. The actual ergonomic consumption of the minimum production unit refers to the actual production efficiency when the minimum production unit is executed. In some embodiments, the acquisition module 110 or the processor may determine a ratio of the actual workload of the minimum production unit to the actual time consumption as the actual ergonomic consumption of the minimum production unit. In some embodiments, the acquisition module 110 or the processor may determine the difference between the actual start time and the current time of the minimum production unit as the actual time consumption of the minimum production unit.

In some embodiments, the acquisition module 110 or processor may acquire acceptance information for the smallest production unit based on user input. For example, when a user (e.g., a constructor, etc.) enters an actual end time of a minimum production unit, the acquisition module 110 or processor may determine acceptance information for the minimum production unit as accepted; when the actual end time of the minimum production unit is not received, the acquisition module 110 or the processor may determine that the acceptance information of the minimum production unit is not accepted. The embodiment of the present specification is not particularly limited, and may employ an operation well known to those skilled in the art.

The job ticket refers to a list of tasks assigned to a construction party (e.g., worker) for construction.

In some embodiments, one or more minimum production units may be included in each job ticket. In some embodiments, the minimum production units in the task sheet exist in the form of tasks, i.e., the task sheet includes a plurality of tasks, each task corresponding to a final task item represented by a minimum production unit.

In some embodiments, the acquisition module 110 or the processor may construct at least one task sheet based on a plurality of minimum production units in a variety of ways. In some embodiments, the acquisition module 110 or processor may construct one or more minimum production units (or last-level task items) belonging to the same spatial unit as a task sheet. In some embodiments, the acquisition module 110 or processor may construct one or more minimum production units (or last-level task items) for producing the same component unit as one task sheet. In some embodiments, the acquisition module 110 or the processor may also construct one or more minimum production units (or final task items) that can be accepted by the same constructor as a task sheet according to the acceptance range of the constructor. The manner of constructing the task sheet in the embodiment of the present specification is not particularly limited, and may be set according to actual requirements.

In some embodiments, a job ticket may be dispatched to a constructor. In some embodiments, multiple job tickets may be dispatched to a constructor or constructors. The job ticket received by each constructor is not repeated. The manner of distributing the task sheet is not particularly limited in the embodiment of the present invention, and may be performed by operations well known to those skilled in the art.

The job information refers to information related to the production situation of the job ticket. In some embodiments, the labor information includes one or more of a construction plan (e.g., plan start time, plan end time, etc.), actual cost consumption, actual progress (e.g., actual start time, actual end time, etc.), etc. for each minimum production unit in the job ticket.

In some embodiments, the acquisition module 110 or processor may acquire the job ticket's logging information based on the input of the constructor. For example, the constructor may upload information such as an actual start time, an actual end time, an actual cost consumption, an actual work efficiency consumption, etc. of each minimum production unit in the job ticket from the terminal device.

Step 420 predicts a progress of the at least partially incomplete task process based on the acceptance information and/or the labor information. In some embodiments, the prediction module 120 or the processor performs step 420.

The incomplete task process refers to a task process in which there is an unverified minimum production unit. The completion of a task process may be measured by the process completion. For example, when all the minimum production units in a task process have been accepted, the process completion degree of the task process may be 1; when no minimum production unit is accepted in the task process, the process completion of the task process may be 0; in other cases, the process completion is an arbitrary value of 0 to 1.

In some embodiments, prediction module 120 or the processor may determine a set of acceptance information for the smallest production unit contained in each task process in each spatial unit based on the acceptance information, the spatial information, and the process information; based on the acceptance information set, a process completion degree of each task process is determined. In some embodiments, the prediction module 120 or the processor may cluster the smallest production units belonging to the same task procedure in the same spatial unit according to the spatial unit and the task procedure to which the smallest production unit belongs; and combining the acceptance information of the clustered minimum production units to obtain an acceptance information set.

In some embodiments, the prediction module 120 or the processor may determine, as the process completion of the task process, a ratio of the number of minimum production units that have been accepted to the total number of elements of the acceptance information set based on the acceptance information set corresponding to the task process.

In some embodiments, the prediction module 120 or the processor may determine a task process that has a process completion of not 1 as an incomplete task process.

In some embodiments of the present description, the construction progress of a construction project may be determined from management dimension analysis of a task process by dividing the construction project into task processes, determining the process completion of the task process, and thus determining the construction progress of the construction project. The method is beneficial to the management side to accurately grasp the construction condition of each task procedure and is beneficial to the management side to conduct targeted management and optimization.

The progress refers to the completion of the predicted unfinished task process. In some embodiments, the progress of the advancement may include one or more of an estimated time required to complete a task procedure, an estimated time required for a critical node, and the like. The expected required time refers to a period of time from the current time point to the acceptance time point of the incomplete task process.

In some embodiments, the critical node may be the smallest production unit that is important in the task process incomplete.

The key nodes may be determined in a number of ways. In some embodiments, the prediction module 120 or the processor may determine the minimum production unit with higher precedence dependence (e.g., above a preset threshold) as the critical node. The order dependency refers to the dependency of the current minimum production unit on the completion of one or more minimum production units having a preceding production order. The higher the dependency of the order, the higher the dependency of the current minimum production unit on the completion of one or more minimum production units preceding the production order. In some embodiments, the dependency of the minimum production units may be sequentially increased according to the production order of the minimum production units, and the increasing trend may be in the form of an index type or a multiple type. By way of example only, the production sequence of the 3 smallest production units included in a task process is: and if the minimum production unit q1 is larger than the minimum production unit q2 and smaller than the minimum production unit q3, the sequential dependency degree w1 of the minimum production unit q1 is smaller than the sequential dependency degree w2 of the minimum production unit q2 and smaller than the sequential dependency degree w3 of the minimum production unit q 1.

In some embodiments, the prediction module 120 or the processor may determine the minimum production unit for which the planning period is long (e.g., above a preset threshold) as a critical node. The planned construction period may be a difference between the planned ending time and the planned starting time.

In some embodiments, the prediction module 120 or the processor may determine the minimum production unit for which the planning cost is high (e.g., above a preset threshold) as a critical node. See fig. 6 and its associated description for more description of planning costs.

The key nodes may also be determined in any other feasible manner, without limitation.

In some embodiments, prediction module 120 may predict a progress of the advancement of at least a portion of the incomplete task process based on the acceptance information.

In some embodiments, the prediction module 120 may predict a progress of the at least partially incomplete task process based on the logging information.

In some embodiments, prediction module 120 may predict a progress of the progress of at least a portion of the incomplete task process based on the acceptance information and the labor information.

For more explanation on the predicted progress of propulsion, see fig. 5 and its associated description.

And step 430, sending out early warning in response to the propulsion process not meeting the preset condition. In some embodiments, the pre-warning module 130 performs step 430.

In some embodiments, the preset condition may include the predicted required time in the progress of the advancement exceeding a preset time threshold. The preset time threshold may be predetermined based on historical data or a priori knowledge.

In some embodiments, the preset conditions may include that the estimated end time of the incomplete task process is greater than the planned end time of the task process. The estimated end time may be determined based on a progress of the incomplete task. For more description of the estimated end time, the planned end time, see fig. 7 and its associated description.

In some embodiments, issuing the pre-warning may include sending pre-warning information to the management party. In some embodiments, the method of sending the early warning information includes, but is not limited to, sending an alarm sound, performing remote notification (such as sending the early warning information to the manager through an app popup window, a short message, etc.), etc.

In some embodiments of the present disclosure, whether to send out an early warning is determined by a progress of the task that is not completed, and whether to send out an early warning may be determined from an angle of whether the task is not completed for an excessive period, so that a risk early warning is timely sent out when the task is predicted to be possibly excessive, which is helpful for a subsequent dynamic deduction of a construction progress and adjustment of a construction policy.

FIG. 5 is an exemplary flow chart of a progress in predicting an incomplete task process, according to some embodiments of the present description. In some embodiments, the process 500 may be performed by the construction project pre-warning system 100 (e.g., the prediction module 120) or a processor. As shown in fig. 5, the process 500 includes the following steps.

Step 510, in response to the task process including the accepted minimum production unit, determining an equivalent work efficiency and/or an equivalent cost of the first minimum production unit based on the acceptance information and/or the labor information.

For more description of the logging information, see fig. 4 and its associated description.

In some embodiments, the first minimum production unit is an approved minimum production unit. The first minimum production unit may be determined based on acceptance information of the minimum production unit. For example, a minimum production unit for which the acceptance information is "accepted" may be determined as the first minimum production unit.

Equivalent work efficiency refers to an index related to the actual production efficiency of producing the first minimum production unit. In some embodiments, the equivalent work efficiency may be used to uniformly scale the actual production efficiency of each first minimum production unit in the job ticket.

The equivalent cost refers to an index related to the cost actually consumed for producing the first minimum production unit. In some embodiments, the equivalent cost may be used to uniformly scale the cost actually consumed by each first minimum production unit in the job ticket.

In some embodiments, the prediction module 120 or the processor may accumulate the actual ergonomic consumption of each first minimum production unit contained in the job ticket, and determine a ratio of the ergonomic consumption sum to the number of first minimum production units as an equivalent ergonomic; and/or accumulating the actual cost consumption of each first minimum production unit contained in the task sheet, and determining the ratio of the sum of the cost consumption to the number of the first minimum production units as the equivalent cost. In some embodiments, the prediction module 120 or the processor may determine a ratio of an actual workload of the first minimum production unit to an actual time consuming as an actual ergonomic consumption of the first minimum production unit.

In some embodiments, the prediction module 120 or the processor may determine the equivalent work efficiency based on the actual work efficiency consumption of the job ticket and the number of first minimum production units the job ticket contains; and/or determining an equivalent cost based on the actual cost consumption of the job ticket and the number of first minimum production units the job ticket contains.

The actual work efficiency consumption of the task sheet refers to the actual production efficiency when executing the task sheet. In some embodiments, the prediction module may determine a ratio of an actual workload of the task sheet to an actual time consumption as an actual ergonomic consumption of the task sheet. In some embodiments, the prediction module 120 or the processor may determine the difference between the actual start time and the current time of the smallest production unit in the job ticket that starts production earliest as the actual time consumption of the job ticket.

In some embodiments, the prediction module 120 or the processor may determine a ratio of the actual ergonomic consumption of the task sheet to the number of first minimum production units contained in the task sheet as an equivalent cost.

The actual cost consumption of a task sheet refers to the cost actually consumed when executing the task sheet. In some embodiments, the prediction module may determine the actual cost consumption of the task sheet based on the job information of the task sheet.

In some embodiments, the prediction module 120 or the processor may determine a ratio of the actual cost consumption of the job ticket to the number of first minimum production units contained in the job ticket as the equivalent cost.

In some embodiments of the present disclosure, by using the actual work efficiency consumption and the actual cost consumption of the task sheet, the equivalent work efficiency and/or the equivalent cost of each minimum accepted production unit can be determined efficiently and accurately, which is beneficial to determining the estimated work efficiency and/or the estimated cost of the minimum accepted production unit.

Step 520, determining estimated work efficiency and/or estimated cost of the second minimum production unit based on the equivalent work efficiency and/or equivalent cost and the spatial information.

In some embodiments, the second minimum production unit is an approved minimum production unit. The second minimum production unit may be determined based on acceptance information of the minimum production unit. For example, the minimum production unit for which the acceptance information is "not accepted" may be determined as the second minimum production unit.

The estimated work efficiency refers to an index related to the estimated production efficiency of the second smallest production unit. In some embodiments, the estimated work efficiency may be used to measure the estimated production efficiency of a second minimum production unit in the job ticket. The estimated work efficiency corresponding to the different second minimum production units may be different.

The estimated cost refers to an index related to the cost of producing the second smallest production unit estimated to consume. In some embodiments, the estimated cost may be used to measure the cost of estimated consumption of a second smallest production unit in the job ticket. The estimated cost corresponding to the different second minimum production units may be different.

The estimated work efficiency and/or estimated cost may be determined in a variety of ways. In some embodiments, the prediction module 120 or the processor may determine, based on the spatial information of the construction project, a corresponding second minimum production unit that belongs to the same component unit within a different spatial unit as the first minimum production unit; and determining the estimated work efficiency and/or the estimated cost of the corresponding second minimum production unit according to the equivalent work efficiency and/or the equivalent cost of the first minimum production unit. For example, the first minimum production unit p1, the first minimum production unit p2 and the first minimum production unit p3 are "exterior wall putty", the space units are "3 building-2 building-1 building", and the component units are "exterior walls", respectively; the second minimum production unit d1 is 'exterior wall putty', the space unit is 'building 4', the part unit is 'exterior wall', and the estimated work efficiency and/or the estimated cost of the corresponding second minimum production unit d1 can be determined according to the equivalent work efficiency and/or the equivalent cost of the first minimum production units p1-p 3.

In some embodiments, the prediction module 120 or the processor may respectively weight the equivalent work efficiency and/or the equivalent cost of the first minimum production unit to determine the estimated work efficiency and/or the estimated cost of the second minimum production unit. Wherein the weighting weights of the different first minimum production units may be different. In some embodiments, the weighting weights may be system default values, empirical values, manually preset values, etc. or any combination thereof, and may be set according to actual requirements, which is not limited in this specification. In some embodiments, the weighted weights may be determined from a spatial distance between the first minimum production unit and the second minimum production unit. The closer the spatial distance, the greater the weighting.

For example, the weighting weights corresponding to the equivalent work efficiency of the first minimum production units p1-p3 may be r1-r3, and the weighting weights corresponding to the equivalent cost of the first minimum production units p1-p3 may be s1-s3, respectively, and then the estimated work efficiency f=g1 of the second minimum production unit d1 may be determined according to the equivalent work efficiency g1-g3 of the first minimum production units p1-p3r1+g2/>r2+g3/>R3, determining the estimated cost e=h1/>, of the second minimum production unit d1 according to the equivalent costs h1-h3 of the first minimum production units p1-p3 respectivelys1+h2/>s2+h3/>s3。

In some embodiments, the prediction module 120 or the processor may determine, based on the spatial information, a third minimum production unit and/or a fourth minimum production unit whose spatial positional relationship with the second minimum production unit satisfies a preset positional condition; and determining the estimated work efficiency and/or the estimated cost of the second minimum production unit through a preset algorithm based on the equivalent work efficiency and/or the equivalent cost of the third minimum production unit and/or the estimated work efficiency and/or the estimated cost of the fourth minimum production unit.

The spatial positional relationship refers to the positional relationship in space of the spatial units to which the two minimum production units belong. In some embodiments, the spatial positional relationship may include a linear distance of the spatial units to which the two smallest production units belong in the same spatial partition.

In some embodiments, the preset position condition may be that the minimum production units belong to the same spatial partition, and the linear distance between the minimum production units is less than the distance threshold. The distance threshold may be a system default value, an empirical value, an artificial preset value, or any combination thereof, and may be set according to actual requirements, which is not limited in this specification. In some embodiments, the preset position condition may be set according to actual requirements, which is not limited herein.

In some embodiments, the third minimum production unit is one or more of the first minimum production units, i.e., the third minimum production unit is one or more of the approved minimum production units.

In some embodiments, the prediction module 120 or the processor may select, as the third minimum production unit, one or more first minimum production units whose spatial positional relationship with the current second minimum production unit satisfies a preset positional condition from among the plurality of first minimum production units. For example, the prediction module 120 or the processor may select, from the plurality of first minimum production units, a first minimum production unit that belongs to the same spatial partition as the current second minimum production unit and has a linear distance from the current second minimum production unit that is less than a distance threshold as the third minimum production unit.

In some embodiments, the fourth minimum production unit is one or more of the second minimum production units for which estimated work efficiency and/or estimated cost has been determined. Wherein the second minimum production unit for which the estimated work efficiency and/or the estimated cost have been determined refers to the second minimum production unit for which the estimated work efficiency and/or the estimated cost have been calculated according to any one of the embodiments of the present specification.

The preset algorithm refers to an algorithm or rule or the like for determining the estimated work efficiency and/or the estimated cost of the second minimum production unit.

The preset algorithm may take a variety of forms. In some embodiments, the preset algorithm may be: in response to the absence of the fourth minimum production unit, performing weighted fusion based on the equivalent work efficiency of the third minimum production unit, and determining the estimated work efficiency of the second minimum production unit; and carrying out weighted fusion based on the equivalent cost of the third minimum production unit, and determining the estimated cost of the second minimum production unit. In some embodiments, the preset algorithm may be: in response to the existence of the fourth minimum production unit, carrying out weighted fusion based on the equivalent work efficiency of the third minimum production unit and the estimated work efficiency of the fourth minimum production unit, and determining the estimated work efficiency of the second minimum production unit; and carrying out weighted fusion on the basis of the equivalent cost of the third minimum production unit and the estimated cost of the fourth minimum production unit, and determining the estimated cost of the second minimum production unit. The weight may be a system default value, an empirical value, a manually preset value, or any combination thereof, and may be set according to actual requirements, which is not limited in this specification.

In some embodiments, the preset algorithm may be: determining a weighted weight of the third minimum production unit and/or the fourth minimum production unit based on the spatial distance between the third minimum production unit and/or the fourth minimum production unit and the second minimum production unit; based on the weighted weight, the equivalent work efficiency and/or the equivalent cost of the third minimum production unit and/or the estimated work efficiency and/or the estimated cost of the fourth minimum production unit, and determining the estimated work efficiency and/or the estimated cost of the second minimum production unit through weighted fusion.

In some embodiments, the prediction module 120 or the processor may determine the weighted weights of the third minimum production unit and/or the fourth minimum production unit by a preset lookup table based on the spatial distance of the third minimum production unit and/or the fourth minimum production unit from the second minimum production unit. In some embodiments, the preset lookup table may include a spatial distance between the third minimum production unit and/or the fourth minimum production unit and the second minimum production unit, and a correspondence relationship between the weighted weights of the third minimum production unit and/or the fourth minimum production unit. For example, the correspondence may be: the weight change may be linear or exponential as the weight corresponding to the third minimum production unit and/or the fourth minimum production unit, which have a smaller spatial distance from the second minimum production unit, is higher. In some embodiments, the preset lookup table may be determined based on historical data or a priori knowledge.

In some embodiments, the prediction module 120 or the processor may determine the predicted work efficiency and/or the predicted cost of the second minimum production unit by weighted fusion based on the weighted weight and the equivalent work efficiency and/or the equivalent cost of the third minimum production unit in response to the absence of the fourth minimum production unit. For example, the estimated work efficiency z _r=（c_r-n+2c_r-(n-1)+3c_r-(n-2)+…+nc_r-1)/(1+2+ … +n) of the second minimum production unit r. Wherein z _r is the estimated work efficiency of the second minimum production unit r, c _r-n to c _r-1 are the equivalent work efficiency of the third minimum production unit r-n to the third minimum production unit r-1, respectively, and 1 to n are the weighting weights of the third minimum production unit r-n to the third minimum production unit r-1, respectively; the third minimum production unit r-n is farthest from the second minimum production unit r and corresponds to the minimum weighting weight; the third smallest production unit r-1 is closest to the smallest second production unit r, which corresponds to the largest weighting weight.

In some embodiments, the prediction module 120 or the processor may determine the estimated work efficiency and/or the estimated cost of the second minimum production unit by weighted fusion based on the weighted weight, the equivalent work efficiency and/or the equivalent cost of the third minimum production unit, and the estimated work efficiency and/or the estimated cost of the fourth minimum production unit in response to the presence of the fourth minimum production unit. For example, the estimated work efficiency of the second minimum production unit r z_r=（c_r-n+2c_r-(n-1)+3c_r-(n-2)+…+nc_r-1）/（1+2+…+n）+（z_r-m+2z_r-(m-1)+3z_r-(m-2)+…+nz_r-1）/（1+2+…+m）.

Wherein z _r is the estimated work efficiency of the second minimum production unit r, z _r-m to z _r-1 are the estimated work efficiency of the fourth minimum production unit r-m to the fourth minimum production unit r-1, respectively, and 1 to m are the weighting weights of the fourth minimum production unit r-n to the fourth minimum production unit r-1, respectively; the fourth minimum production unit r-m is farthest from the minimum second production unit r and corresponds to the minimum weighting weight; the fourth smallest production unit r-1 is closest to the smallest second production unit r, which corresponds to the largest weighting weight.

The calculation manner of the estimated cost of the second minimum production unit is similar to the calculation manner of the estimated work efficiency of the second minimum production unit, and will not be described herein.

In some embodiments of the present disclosure, it is assumed that the work efficiency and cost of the minimum production unit with a closer spatial distance are closer, and according to the equivalent work efficiency and equivalent cost of the third minimum production unit with a spatial position relationship with the second minimum production unit meeting the preset position condition, and according to the spatial distance distribution weight change, the local change of the space can be effectively compatible, and a more accurate predicted value than the experience judgment can be obtained. Furthermore, the estimated work efficiency and the estimated cost of the fourth minimum production unit, of which the spatial position relation with the second minimum production unit meets the preset position condition, are included in the weighted calculation, and the calculation of the rest part can be further optimized according to the determined estimated value, so that the accuracy of the estimated value is improved.

Step 530, predicting the progress of the unfinished task process based on the estimated work efficiency and/or the estimated cost.

In some embodiments, the prediction module 120 or processor may predict the progress of the incomplete task process in a variety of ways based on the estimated work efficiency and/or the estimated cost. In some embodiments, the prediction module 120 or the processor may determine the sum of the estimated time spent on all the second smallest production units in the task process as the estimated completion time for the incomplete task process. For example, if the sum of estimated time spent on all the second minimum production units in the incomplete task process is t _s, it may be determined that the estimated required time for the incomplete task process is t _s. In some embodiments, the estimated time consumption of the second minimum production unit may be determined based on the workload and the estimated work efficiency of the second minimum production unit. In some embodiments, the workload of the second minimum production unit may be determined based on the total workload of the task sheet to which the second minimum production unit belongs and the number of minimum production units in the belonging task sheet.

In some embodiments, the prediction module 120 or the processor may determine the predicted required time for the critical node based on the location of the critical node in the unfinished task process, based on a predicted total of the work efficiency of all second minimum production units located before the critical node in the unfinished task process. The determination of the expected time of the critical node is similar to the determination of the expected time of the task process, and will not be described in detail herein. For more description of key nodes see fig. 4 and its associated description.

In some embodiments of the present disclosure, according to the equivalent work efficiency and the equivalent cost of the minimum production unit that is checked in the task list, the pre-estimation procedure and the pre-estimation cost of the minimum production unit that is not checked are determined by combining the spatial information, so that the local change of the space can be compatible, and thus, a more accurate predicted value than the empirical determination can be obtained. For example, a building comprises 10 working procedures in two floors, but only 3 working procedures are needed for three floors or 30 working procedures are needed for three floors, and the situation can not be handled by using the experience of similar working procedures between adjacent floors, but the building is disassembled to the minimum production unit and can be accurately predicted according to the local change of space. The prediction mode can consider recent business changes from a statistical angle, such as suddenly increasing factors influencing efficiency, such as hands, material supply tension, and the like, and improves prediction accuracy.

FIG. 6 is one of exemplary diagrams illustrating a determination of whether to issue an early warning according to some embodiments of the present disclosure.

In some embodiments, the early warning module may determine whether to send out the early warning according to the actual cost consumption of the task sheet.

Referring to FIG. 6, in some embodiments, the pre-warning module 130 or processor may determine 620 the actual cost consumption of the task sheet based on the labor information of the task sheet 610; determining theoretical cost consumption 650 of the task sheet based on the task completion 630 and the planning cost 640 of the task sheet; and responding to the difference between the actual cost consumption and the theoretical cost consumption to meet the preset early warning condition, and sending out early warning.

The actual cost consumption of a job ticket refers to the sum of the actual cost consumption when the minimum production unit contained in the job ticket is completed. The actual cost consumption of the task sheet may be determined based on the labor information of the task sheet. For example, the early warning module may determine the combination of the actually generated cost consumptions as the actual cost consumptions based on the labor information of the task sheet.

The task completion degree refers to the completion condition of the task sheet. For example, when all the minimum production units in the task sheet have been accepted, the task completion degree of the task sheet may be 1; when no minimum production unit in the task list is checked and accepted, the task completion degree of the task list can be 0; the task completion degree in other cases is any value from 0 to 1.

In some embodiments, the pre-warning module 130 or the processor may determine the task completion of the task sheet based on acceptance information of the minimum production unit contained in the task sheet. For example, the pre-warning module 130 or the processor may determine a ratio of the number of minimum production units accepted in the job ticket to the total number of minimum production units contained in the job ticket as a job completion of the job ticket.

In some embodiments of the present disclosure, the construction progress of a construction project may be determined from management dimension analysis of a task sheet by dividing the construction project into task sheets, determining the task completion of the task sheets, and thus determining the construction progress of the construction project. The method is beneficial to the management side to accurately grasp the construction conditions of each construction side, and is beneficial to the management side to conduct targeted management optimization.

The planning cost of a task sheet refers to the cost budget of a task sheet that is planned in advance. The planning cost of the task sheet may be predetermined by the administrator based on historical data or prior knowledge.

The theoretical cost consumption of a job ticket refers to the sum of theoretical cost consumption when the smallest production unit that the job ticket contains is completed.

In some embodiments, the pre-warning module 130 or processor may determine the product of the task completion and the planning cost of the task sheet as the theoretical cost consumption of the task sheet. For example, the early warning module may scale the task completion to a percentage or a value between 0-1, determining the product of the task completion and the planning cost as the theoretical cost consumption.

The preset early warning condition is a condition for judging whether early warning can be carried out according to the difference between actual cost consumption and theoretical cost consumption. In some embodiments, the preset pre-warning condition may be that the actual cost consumption differs from the theoretical cost consumption by more than a difference threshold. The difference threshold may be a system default value, an empirical value, an artificial preset value, or any combination thereof, and may be set according to actual requirements, which is not limited in this specification. The preset early warning condition can be set according to actual requirements, and is not limited herein.

In some embodiments of the present disclosure, whether to send out an early warning is determined according to a difference between actual cost consumption and theoretical cost consumption of a task sheet, and whether to send out an early warning may be determined from a cost consumption perspective of the task sheet, so that when it is predicted that the cost consumption of the task sheet does not conform to an expected situation, a risk early warning is timely sent out, which is helpful for dynamic deduction of a subsequent construction process and adjustment of a construction policy.

FIG. 7 is a second exemplary diagram illustrating a determination of whether to issue an alert according to some embodiments of the present disclosure.

In some embodiments, the pre-warning module 130 or the processor may determine whether to issue the pre-warning based on the actual time consumption and the labor consumption of the task process.

Referring to FIG. 7, in some embodiments, the pre-warning module 130 or processor may determine an estimated end time 720 of the task process based on an estimated work efficiency 710 of a second minimum production unit contained within the task process; and sending out early warning in response to the estimated ending time being greater than the planned ending time of the task procedure.

The estimated end time refers to the estimated acceptance time point of the task process. In some embodiments, the pre-warning module 130 or the processor may determine an estimated required time for the task process based on the estimated work efficiency of the second smallest production unit contained within the task process; and determining the estimated ending time based on the current time point and the estimated required time. For example, when the current time point is T and the expected required time is T _s, the estimated end time is t+t _s. For more explanation about the expected time needed see step 530 and its associated description.

The planned ending time of the task process refers to the planned ending time of the last minimum production unit in the task process. For more explanation about the planned ending time of the minimum production unit, see fig. 4 and its associated description.

In some embodiments, the estimated end time being greater than the planned end time may refer to the estimated end time being located after the planned end time.

In some embodiments of the present disclosure, by predicting the predicted ending time of the task procedure, whether to send out an early warning is determined according to the precedence relationship between the predicted ending time and the planned ending time, whether to send out an early warning may be determined from the angle of whether the task procedure is out of date, so as to send out a risk early warning in time when it is predicted that the task procedure may be out of date, which is helpful for dynamic deduction of the subsequent construction process and adjustment of the construction strategy.

Referring to fig. 7, in some embodiments, the pre-warning module 130 or processor may determine a remaining planning effort 750 for the task process based on the planning effort 730 for the task process and the acceptance information 740 for the task process; determining a dominant effort 760 of a second minimum production unit contained within the task process based on the remaining planning effort 750; and sending out early warning in response to the estimated work efficiency of the second minimum production unit contained in the task procedure being greater than the available work efficiency.

The planning efficiency of a task process refers to the efficiency budget of a task process that is planned in advance. The planning ergonomics of the task process may be predetermined by the administrator based on historical data or prior knowledge.

The remaining planning effort of a task process refers to the remaining effort budget of the task process that has been produced.

In some embodiments, the pre-warning module 130 or the processor may determine an actual ergonomic consumption of the task process based on the acceptance information of the task process, and determine a difference between the planned and actual ergonomic consumption as the remaining planned ergonomics.

Dominating the work efficiency means that the work efficiency budget of each second smallest production unit in the task process is calculated in case the remaining planning work efficiency is fulfilled.

In some embodiments, the pre-warning module 130 or the processor may determine the available ergonomics of the second minimum production unit contained within the task process based on the remaining planning ergonomics and the number of second minimum production units contained within the task process. For example, the early warning module may determine a ratio of the remaining planning effort to the number of second minimum production units included in the task process as the dominant effort of the second minimum production units included in the task process.

In some embodiments of the present disclosure, by determining the available work efficiency of each second minimum production unit included in the task procedure under the condition that the remaining planned work efficiency is satisfied, whether to send out an early warning may be determined according to whether the available work efficiency of the single second minimum production unit can support the result of the production according to the estimated work efficiency. By the embodiment, whether the early warning is sent out can be judged from the angle of whether the single second minimum production unit exceeds the period, so that the risk early warning is sent out in time when the second minimum production unit is predicted to possibly exceed the period, and the follow-up dynamic deduction of the construction process and the adjustment of the construction strategy are facilitated.

FIG. 8 is a third exemplary diagram illustrating a determination of whether to issue an alert according to some embodiments of the present disclosure.

In some embodiments, the pre-warning module 130 or the processor may determine whether to issue the pre-warning based on the actual cost consumption of the task process.

Referring to FIG. 8, in some embodiments, the pre-warning module 130 or processor may determine a remaining required cost 820 of the task process based on an estimated cost 810 of a second minimum production unit contained within the task process; and sending out early warning in response to the remaining required cost being greater than the remaining planning cost of the task process.

The remaining required costs of the task process refer to the sum of costs required to complete all of the second minimum production units in the task process. In some embodiments, the pre-warning module 130 or the processor may determine the sum of the estimated costs of all the second smallest production units in the task process as the remaining required cost of the task process.

The remaining planning cost of a task process refers to the remaining cost budget of the task process that has been produced.

In some embodiments, the pre-warning module 130 or the processor may determine the remaining planning cost for the task process based on the planning cost for the task process and the logging information for the task process. In some embodiments, the early warning module may determine an actual cost consumption of the task process based on the logging information of the task process, and determine a difference between the planning cost and the actual cost consumption as a remaining planning cost.

In some embodiments of the present disclosure, by determining the remaining required cost of the task procedure, determining whether to issue an early warning according to the magnitude relation between the remaining required cost and the remaining planning cost, it may be determined whether to issue an early warning from the angle of exceeding the cost budget when all the second minimum production units remain in the task procedure, so as to issue a risk early warning in time when it is predicted that the cost budget may be exceeded, which is helpful for dynamic deduction of the subsequent construction process and adjustment of the construction policy.

Referring to fig. 8, in some embodiments, the pre-warning module 130 or processor may determine a remaining planning cost 840 for the task process based on the planning cost 830 for the task process and the logging information 610 for the task process; based on the remaining planning costs 840, determining a dominating cost 850 for a second smallest production unit contained within the task process; and sending out an early warning in response to the estimated cost of the second smallest production unit contained in the task procedure being greater than the available cost. The relevant description of the remaining planning costs is referred to above.

The dominating costs refer to the cost budget of each second smallest production unit in the task process, in case the remaining planning costs are fulfilled.

In some embodiments, the pre-warning module 130 or the processor may determine the available ergonomics of the second minimum production unit contained within the task process based on the remaining planning costs and the number of second minimum production units contained within the task process. For example, the pre-warning module may determine a ratio of the remaining planning cost to the number of second minimum production units included in the task process as a dominant cost of the second minimum production units included in the task process.

In some embodiments of the present disclosure, by determining the available costs of each second minimum production unit included in the task procedure when the remaining planning costs are satisfied, it may further be determined whether to issue an early warning according to whether the available costs of the single second minimum production unit can support the result of production thereof according to the estimated costs. By the embodiment, whether the early warning is sent out can be judged from the angle of whether the single second minimum production unit exceeds the cost budget, so that the risk early warning is sent out in time when the second minimum production unit is predicted to possibly exceed the cost budget, and the follow-up dynamic deduction of the construction process and the adjustment of the construction strategy are facilitated.

In some embodiments, the pre-warning module 130 or the processor may determine an associated task process of the task process in response to the minimum accepted production units not being included within the task process; determining estimated work efficiency and/or estimated cost of a second minimum production unit contained in the task process based on historical labor information and/or historical acceptance information of the associated task process; determining estimated end time and/or residual required cost of the task process based on estimated work efficiency and/or estimated cost of a second minimum production unit contained in the task process; and sending out early warning in response to the estimated ending time being greater than the planned ending time and/or the remaining required cost being greater than the remaining planned cost.

In this embodiment, the manner of determining whether to send out the early warning is similar to that of the previous embodiment, and will not be described again.

The task process that does not include the minimum accepted production units may be referred to as a zero acceptance task process.

The associated task process refers to a task process having an associated relationship with the zero acceptance task process. In some embodiments, the associated task process includes at least a predetermined number of accepted minimum production units. The preset number may be a system default value, an empirical value, an artificial preset value, or any combination thereof, and may be set according to actual requirements, which is not limited in this specification.

In some embodiments, the pre-warning module 130 or the processor may determine the associated task sequence based on the component units and the space units corresponding to the smallest production unit contained in the zero acceptance task sequence. For example, the pre-warning module 130 or the processor may determine, as the associated task process, a task process in which the component unit is the same as the component unit corresponding to the zero acceptance task process and the space unit is adjacent to the space unit corresponding to the zero acceptance task process. In some embodiments, the pre-warning module 130 or the processor may also determine the associated task sequence in any other feasible manner, without limitation.

In some embodiments, the pre-warning module 130 or processor may determine an estimated work efficiency and/or an estimated cost of a second minimum production unit contained within the task process based on historical labor information and/or historical acceptance information of the associated task process. For example, the early warning module may determine an equivalent work efficiency and/or an equivalent cost of the first minimum production unit in the associated task process based on historical labor information and/or historical acceptance information of the associated task process; and determining the estimated work efficiency and/or the estimated cost of the second minimum production unit in the associated task process based on the equivalent work efficiency and/or the equivalent cost of the first minimum production unit in the associated task process and the space information. Further, the early warning module can enable each minimum production unit in the associated task process to correspond to each minimum production unit in the current task process one by one, and respectively determine the equivalent work efficiency and the equivalent cost of one or more first minimum production units in the associated task process as the estimated work efficiency and the estimated cost of one or more second minimum production units in the current task process; and respectively determining the estimated work efficiency and the estimated cost of one or more second minimum production units in the related task process as the estimated work efficiency and the estimated cost of the corresponding one or more second minimum production units in the current task process.

In some embodiments, the pre-warning module 130 or the processor may also determine the estimated end time and/or the remaining required cost of the critical nodes in the task process; and sending out early warning in response to the estimated ending time of the key node being greater than the planned ending time and/or the remaining required cost of the key node being greater than the remaining planned cost.

In some embodiments, the pre-warning module 130 or the processor may determine the estimated end time and/or the remaining required cost of the critical node in the task process based on the location of the critical node in the task process based on the estimated work efficiency and/or the estimated cost of the second smallest production unit located before the critical node in the task process. For more description see the relevant description above.

In some embodiments of the present disclosure, in the case that the current task process does not include the accepted minimum production units, the estimated work efficiency and/or the estimated cost of each second minimum production unit in the current task process may be determined by determining the associated task process. According to the embodiment, the problem that the estimated work efficiency and/or the estimated cost of each second minimum production unit are difficult to determine under the condition that the current task process does not comprise the checked minimum production units can be effectively solved according to a parallel estimation mode.

In some embodiments, after the pre-warning is sent, a pushing strategy for the incomplete task procedure can be automatically generated, and the user is prompted with the pushing strategy for the incomplete task procedure.

The push strategy refers to the production scheduling plan of the second smallest production unit in the incomplete task process. For example, the pushing strategy may include a construction plan, a planning cost, etc. of each second minimum production unit in the incomplete task process. The construction plan of one or more second minimum production units in the propulsion strategy may be interleaved. Examples of the case where the interleaving is performed include: the planned starting time of the second minimum production unit R2 is located between the planned starting time and the planned ending time of the second minimum production unit R1.

FIG. 9 is an exemplary flow chart of a propulsion strategy for determining incomplete task processes, according to some embodiments of the present description. In some embodiments, the process 900 may be performed by the construction project pre-warning system 100 (e.g., the planning module 140) or a processor. As shown in fig. 9, the process 900 includes the following steps.

Step 910, determining an estimated end time for the incomplete task process.

In some embodiments, the accepted minimum production units may not be included within the incomplete task process. In some embodiments, at least one approved minimal production unit may be included within an incomplete task process.

The estimated end time of the unfinished task process refers to an estimated acceptance time point of the unfinished task process.

In some embodiments, in response to the inclusion of at least one accepted minimum production unit within an incomplete task process, planning module 140 or processor may determine an estimated required time to complete all of the second minimum production units based on the estimated work efficiency of the second minimum production units contained within the incomplete task process; and determining the estimated ending time of the unfinished task procedure based on the current time point, the performed time of the second minimum production unit and the estimated required time. For example, the current time point is T1, the time of the second minimum production unit is T2, the predicted required time is T ₁, and the predicted end time is (T1+t ₁ -T2). For more description of the expected time needed see step 1030 and its associated description.

In some embodiments, in response to not including the accepted minimum production units within the incomplete task process, the planning module 140 or the processor may determine an estimated required time to complete all of the second minimum production units based on the estimated work efficiency of the second minimum production units included within the incomplete task process; and determining the estimated ending time of the unfinished task procedure based on the current time point, the actual starting time of the unfinished task procedure and the estimated required time. For example, the current time point is T3, the actual start time is T4, the predicted required time is T ₂, and the predicted end time is [ T ₂ - (T3-T4) +T3]. For more explanation about the expected time needed see step 530 and its associated description.

Step 920, obtaining a first boundary condition between task processes and a second boundary condition of the construction project.

The first boundary condition between task processes refers to a boundary condition related to the sequence and time interval between part of task processes. For example, the first boundary condition may be various forms such that the task process B can be started only after the task process a is completed, the task process B must be started 5 days before the task process a is completed, the task process B must be started 2 days after the task process a is started, the task process B can be started only after the task process a is started, and the like.

The second boundary condition of the construction project refers to a boundary condition related to a cost budget and a construction period budget of the construction project. For example, the second boundary condition may be a cost budget below X, a construction period budget below Y, and so on.

In some embodiments, the planning module 140 or the processor may determine the first boundary condition, the second boundary condition based on production requirements of the respective task processes included in the construction project. The production request includes the sequence of each task process, time intervals, a construction plan (for example, a plan start time, a plan end time, etc.), and the like. The production requirements may be predetermined by the administrator.

Step 930, determining a propulsion policy for the unfinished task process based on the estimated end time, the first boundary condition, and the second boundary condition.

In some embodiments, the planning module 140 or the processor may determine the advancement strategy for the incomplete task process by querying a strategy lookup table based on the estimated end time, the first boundary condition, and the second boundary condition. In some embodiments, the policy lookup table may include a plurality of pre-estimated end times, a plurality of first boundary conditions, a plurality of second boundary conditions, and a plurality of propulsion policies. In some embodiments, the policy lookup table may be determined based on historical data or a priori knowledge.

In some embodiments, the planning module 140 or the processor may determine a plurality of candidate propulsion strategies based on the incomplete procedure; determining a construction period index and a cost index of the candidate propulsion strategy based on the estimated end time, the first boundary condition and the second boundary condition; a propulsion strategy is determined based on the planning objectives and the construction period index and/or the cost index.

Candidate propulsion strategies refer to primarily determined propulsion strategies. The candidate propulsion strategy may be used to determine a final propulsion strategy.

In some embodiments, the planning module 140 or the processor may randomly generate a plurality of candidate propulsion strategies based on the incomplete task sequence. In some embodiments, the planning module 140 or the processor may arrange and combine the plurality of incomplete task processes based on the estimated end time and the first boundary condition to obtain a plurality of process combinations; and screening the process combination based on the second boundary condition to obtain a plurality of candidate propulsion strategies. For example, the planning module 140 or the processor may sort the corresponding incomplete task processes based on the sequence and the time interval of the partial task processes in the first boundary condition, and randomly sort the remaining incomplete task processes to obtain a plurality of process combinations. For another example, the planning module 140 or the processor may determine a remaining planning cost and a remaining planning effort for the incomplete task process according to the second boundary condition and the logging information and/or the acceptance information of the task process, and exclude process combinations in which the sum of the effort and the sum of the costs do not satisfy the second boundary condition, to obtain a plurality of candidate propulsion strategies.

The construction period index refers to the work efficiency consumed in production according to the candidate propulsion strategy. The duration index corresponding to the different candidate propulsion strategies may be different.

In some embodiments, the planning module 140 or the processor may arrange the time periods corresponding to the plurality of incomplete task processes on the time axis according to the arrangement of each incomplete task process, the estimated end time of the incomplete task process, and the first boundary condition between the task processes in the candidate recommendation policy; the time period between the earliest time point and the latest time point is determined as a construction period index of the candidate recommendation strategy.

The cost index refers to the cost spent in production according to the candidate boost strategy. The cost index corresponding to the different candidate propulsion strategies may be different.

In some embodiments, the planning module 140 or the processor may determine a process cost sum of a plurality of incomplete task processes included in the candidate recommendation policy as a cost index for the candidate recommendation policy. Wherein the process cost of each unfinished task process may be determined based on a sum of estimated costs of the second smallest production units included in the unfinished task process.

In some embodiments, the planning module 140 or the processor may select, from among a plurality of candidate propulsion strategies, a candidate propulsion strategy for which the time limit and/or the cost index meets the planning objective as the final propulsion strategy.

In some embodiments, the planning module 140 or the processor may construct a construction period-cost scatter plot based on the construction period index and the cost index of the plurality of candidate propulsion strategies. For example, with the construction period index being the X-axis and the cost index being the Y-axis, innumerable (construction period, cost) scattered points can be obtained in a planar rectangular coordinate system. As shown in fig. 10A-10D, each scatter in the construction period-cost scatter plot represents a different candidate propulsion strategy, the abscissa of each scatter corresponds to the construction period index of the candidate propulsion strategy, and the ordinate of each scatter corresponds to the cost index of the candidate propulsion strategy.

In some embodiments, the planning objectives include a project period objective. The project period target refers to selecting a propulsion strategy according to a project period index.

In some embodiments, the planning module 140 or the processor may determine the propulsion strategy based on the duration index in response to the planning goal being a duration goal. As shown in fig. 10A, the planning module 140 or processor may select a candidate propulsion strategy with an optimal construction period index (e.g., minimum X value) as the propulsion strategy in response to the planning target being a construction period target.

In some embodiments, the planning objectives include cost objectives. Cost targets refer to selecting a propulsion strategy based on a cost index.

In some embodiments, the planning module 140 or the processor may determine the propulsion strategy based on the cost index in response to the planning goal being a cost goal. As shown in fig. 10B, the planning module 140 or processor may select a candidate propulsion strategy with an optimal cost index (e.g., minimum Y value) as the propulsion strategy in response to the planning target being a cost target.

In some embodiments, the planning objectives include dual-optimization objectives. The double-best targets are that when a propulsion strategy is selected, the construction period index and the cost index are considered at the same time, and the influence weights of the construction period index and the cost index are the same. The impact weight may reflect the degree of emphasis on each of the construction index and the cost index when the propulsion strategy is selected. For example, when the impact weight is the same, it is desirable that the construction period index and the cost index are both low when a propulsion strategy is selected.

In some embodiments, the planning module 140 or the processor may determine the propulsion strategy based on the time limit index and the cost index in response to the planning goal being a dual-optimal goal. As shown in fig. 10C, the planning module 140 or processor may select a candidate propulsion strategy for which the construction cost is double optimal (e.g., the distance to the origin of coordinates is minimal) as the propulsion strategy in response to the planning target being a double optimal target.

In some embodiments, the planning objectives further include a project period optimization objective. The better objective of the construction period is to consider the construction period index and the cost index simultaneously when a propulsion strategy is selected, wherein the influence weight of the construction period index is higher than that of the cost index. For example, a higher impact weight on the duration index indicates a lower duration index is more desirable when selecting a propulsion strategy.

In some embodiments, the planning module 140 or the processor may determine the advancement strategy based on the construction period index and the cost index in response to the planning goal being a better construction period goal. As shown in fig. 10D, the planning module 140 or processor may select a candidate propulsion strategy with a higher construction period weight as the propulsion strategy in response to the planning target being a better construction period target. When the influence weight of the construction period index and the cost index is expressed by the elliptical long and short axes, the construction period weight is higher, and the construction period index can be expressed as the elliptical short axis corresponding to the construction period index, that is, the elliptical short axis is located on the X axis or parallel to the X axis.

In some embodiments, the planning objectives further include cost-optimized objectives. The cost better target is that when a propulsion strategy is selected, the construction period index and the cost index are considered at the same time, and the influence weight of the construction period index is lower than that of the cost index. For example, a higher impact weight on the cost index indicates a lower cost index is more desirable when selecting a propulsion strategy.

In some embodiments, the planning module 140 or the processor may determine the advancement strategy based on the construction period index and the cost index in response to the planning goal being a better construction period goal. For example, the planning module 140 or the processor may select a candidate propulsion strategy with a higher cost weight as the propulsion strategy in response to the planning target being a more cost optimal target. When the elliptical short axis is used to represent the influence weight of the construction period index and the cost index, the cost weight is higher, and the cost index can be represented as the elliptical short axis corresponding to the cost index, namely, the elliptical short axis is positioned on the Y axis or parallel to the Y axis.

In some embodiments of the present disclosure, different propulsion strategies are determined according to different planning objectives, and the propulsion strategies may be continuously adjusted according to business objectives (e.g., cost-optimal, construction-period-optimal, etc. business objectives).

In some embodiments, the planning module 140 or the processor may further determine a cost-time curve corresponding to the candidate propulsion strategy based on the estimated work efficiency and/or the estimated cost of the second smallest production unit included in the incomplete task process; determining a cash flow time profile based on the cost time profile and the balance data; based on the cash flow time profile, a propulsion strategy is determined.

The cost time curve refers to a curve in which cost consumption varies with construction time. For example, the horizontal axis of the cost time curve may represent construction time and the vertical axis may represent cost consumption. The cost consumption of the candidate boost strategy increases as the construction time increases, reaching a maximum at the end of the construction time.

The balance data refers to data related to income and expense of the management side. The balance data may be determined by the manager input or by the supervisory system.

The cash flow time curve refers to a curve of cash flow as a function of construction time. For example, the horizontal axis of the cash flow time curve may represent construction time and the vertical axis may represent cash flow. Where cash flow refers to the difference in cost and revenue. In this embodiment, the cost includes the cost corresponding to the construction project and other expenses of the manager.

In some embodiments, the planning module 140 or processor may superimpose the balance data in a cost time curve over time resulting in a cash flow curve.

In some embodiments, the planning module 140 or processor may determine the advancement strategy in a variety of ways based on the cash flow time profile. For example, the planning module 140 or processor may determine a fluctuation of the cash flow from the cash flow time profile, and determine a candidate propulsion strategy with relatively stable cash flow fluctuation as the final propulsion strategy. For another example, the planning module 140 or processor may consider the construction time in combination to determine candidate propulsion strategies with shorter construction times as the final propulsion strategy. The planning module 140 or processor may also determine the recommendation policy in any other feasible manner, without limitation.

In some embodiments of the present disclosure, the recommendation policy is determined based on a cash flow time curve, and the cost and time variation of the recommendation policy and the income situation of the manager can be considered at the same time, so that the manager can select a reasonable recommendation policy according to the actual peak funds bearing capacity and the construction period requirement.

In some embodiments of the present disclosure, the construction plan may be dynamically adjusted by calculating the work efficiency and cost of the minimum production unit, and the data may be used to facilitate the management of the progress of the construction project.

There is also provided in one or more embodiments of the present specification a construction progress pipe apparatus, the apparatus comprising at least one processor and at least one memory; the at least one memory is configured to store computer instructions; the at least one processor configured to execute at least some of the computer instructions to implement the method of job schedule management as in any one of the embodiments

In one or more embodiments of the present disclosure, there is further provided a computer-readable storage medium storing computer instructions, where when the computer reads the computer instructions in the storage medium, the computer executes the construction progress management method according to any one of the embodiments.

In the embodiments of the present disclosure, when operations performed by the steps are described, unless otherwise specified, the order of the steps may be changed, the steps may be omitted, and other steps may be included in the operation.

The embodiments in this specification are described with respect to systems and modules thereof for convenience of description only and are not limited in scope by the illustrated embodiments. It is possible to combine the individual modules arbitrarily or to construct a subsystem in connection with other modules without departing from the principles of the system.

The embodiments in this specification are for illustration and description only and do not limit the scope of applicability of the specification. Various modifications and changes may be made by those skilled in the art in light of the present description while remaining within the scope of the present description.

Certain features, structures, or characteristics of one or more embodiments of the present description may be combined as suitable.

Aspects of the present description may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.) or by a combination of hardware and software. The above hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system," etc. Furthermore, aspects of the specification may take the form of a computer product, comprising computer-readable program code, embodied in one or more computer-readable media.

A computer storage medium may be any computer readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or a combination of any of the foregoing.

The computer program code necessary for operation of the various portions of this specification may be written in any one or more programming languages. The program code may execute entirely on the user's computer or as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or processing device. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or the use of services such as software as a service (SaaS) in a cloud computing environment.

In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the number allows for a 20% variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. Although the numerical ranges and parameters set forth herein are approximations that may be employed in some embodiments to confirm the breadth of the range, in particular embodiments, the setting of such numerical values is as precise as possible.

Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments of this specification. Other variations are possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present specification may be considered as consistent with the teachings of the present specification. Accordingly, the embodiments of the present specification are not limited to only the embodiments explicitly described and depicted in the present specification.

Claims

1. A construction project pre-warning method, the method comprising:

acquiring acceptance information of a minimum production unit and record information of a task list in a plurality of task procedures of a construction project, wherein the minimum production unit comprises space information, component information and task item information, and each minimum production unit corresponds to one final task item corresponding to a component unit in one space unit;

Predicting a progress of at least a portion of the incomplete task process based on the acceptance information and/or the labor logging information, comprising:

In response to the task procedure including the checked minimum production unit, determining the equivalent work efficiency and/or the equivalent cost of a first minimum production unit based on the check information and/or the engineering information, wherein the first minimum production unit is the checked minimum production unit;

Based on the equivalent work efficiency and/or the equivalent cost and the space information, determining estimated work efficiency and/or estimated cost of a second minimum production unit, wherein the second minimum production unit is the minimum production unit which is not checked;

predicting a progress of the unfinished task process based on the estimated work efficiency and/or the estimated cost;

And

Responding to the pushing progress not meeting a preset condition, and sending out early warning;

Wherein the determining the estimated work efficiency and/or the estimated cost of the second minimum production unit based on the equivalent work efficiency and/or the equivalent cost and the spatial information comprises:

Determining a third minimum production unit and/or a fourth minimum production unit, wherein the spatial position relation between the third minimum production unit and the second minimum production unit meets a preset position condition, the third minimum production unit is one or more of the first minimum production units, and the fourth minimum production unit is one or more of the second minimum production units, the estimated work efficiency and/or the estimated cost of which are determined;

Determining the estimated work efficiency and/or the estimated cost of the second minimum production unit by a preset algorithm based on the equivalent work efficiency and/or the equivalent cost of the third minimum production unit and/or the estimated work efficiency and/or the estimated cost of the fourth minimum production unit; the preset algorithm comprises the following steps:

Determining a weighted weight of the third minimum production unit and/or the fourth minimum production unit based on a spatial distance of the third minimum production unit and/or the fourth minimum production unit from the second minimum production unit;

based on the weighted weights, the equivalent work efficiency and/or the equivalent cost of the third minimum production unit and/or the estimated work efficiency and/or the estimated cost of the fourth minimum production unit, determining the estimated work efficiency and/or the estimated cost of the second minimum production unit through weighted fusion.

2. The method of claim 1, wherein the determining an equivalent work efficiency and/or an equivalent cost of a first minimum production unit based on the acceptance information and/or the job ticket's logging information comprises:

Determining the equivalent work efficiency based on the actual work efficiency consumption of the task sheet and the number of the first minimum production units contained in the task sheet; and/or

The equivalent cost is determined based on the actual cost consumption of the job ticket and the number of first minimum production units contained by the job ticket.

3. The method according to claim 1, wherein the method further comprises:

determining an estimated end time of the task process based on the estimated work efficiency of the second minimum production unit contained within the task process;

and sending out early warning in response to the estimated ending time being greater than the planned ending time of the task procedure.

4. The method according to claim 1, wherein the method further comprises:

determining the remaining planning work efficiency of the task process based on the planning work efficiency of the task process and the acceptance information of the task process;

determining a dominating work efficiency of the second smallest production unit contained within the task process based on the remaining planning work efficiency;

And sending out an early warning in response to the estimated work efficiency of the second minimum production unit contained in the task process being greater than the available work efficiency.

5. The method according to claim 1, wherein the method further comprises:

determining a remaining required cost for the task process based on the estimated cost of the second minimum production unit contained within the task process;

And sending out an early warning in response to the remaining required cost being greater than the remaining planning cost of the task process.

6. The method according to claim 1, wherein the method further comprises:

determining the remaining planning cost of the task procedure based on the planning cost of the task procedure and the labor information of the task procedure;

determining a dominant cost of the second smallest production unit contained within the task process based on the remaining planning costs;

And sending an early warning in response to the estimated cost of the second smallest production unit contained within the task process being greater than the available cost.

7. The method according to claim 1, wherein the method further comprises:

determining an associated task process of the task process in response to the task process excluding the accepted minimum production unit;

based on the historical acceptance information and/or the historical engineering information of the associated task procedure, determining estimated work efficiency and/or estimated cost of a second minimum production unit contained in the task procedure;

Determining estimated end time and/or remaining required cost of the task process based on the estimated work efficiency and/or the estimated cost of the second minimum production unit contained within the task process;

and sending out early warning in response to the estimated ending time being greater than the planned ending time and/or the remaining required cost being greater than the remaining planned cost.

8. The method according to claim 1, wherein the method further comprises: and after the early warning is sent out, prompting the user of the pushing strategy of the task procedure which is not completed.

9. The method of claim 8, wherein the method further comprises:

Determining the estimated ending time of the unfinished task procedure;

Acquiring a first boundary condition and a second boundary condition of a construction item between the task procedures;

And determining the propulsion strategy of the unfinished task procedure based on the estimated ending time, the first boundary condition and the second boundary condition.

10. The method of claim 9, wherein the determining the propulsion strategy for the incomplete task process based on the estimated end time, the first boundary condition, and the second boundary condition comprises:

determining a plurality of candidate propulsion strategies based on the incomplete task procedures;

Determining a construction period index and a cost index of the candidate propulsion strategy based on the estimated end time, the first boundary condition and the second boundary condition;

The propulsion strategy is determined based on a planning objective and the construction period index and/or the cost index.

11. The method of claim 10, wherein the planning objective comprises a construction objective; the determining the propulsion strategy based on the planning objectives and the construction period index and/or the cost index comprises:

And determining the propulsion strategy based on the construction period index in response to the planning target being the construction period target.

12. The method of claim 10, wherein the planning objective comprises a cost objective; the determining the propulsion strategy based on the planning objectives and the construction period index and/or the cost index comprises:

in response to the planning target being the cost target, the propulsion strategy is determined based on the cost index.

13. The method according to claim 10, wherein the method further comprises:

Determining a cost time curve corresponding to the candidate propulsion strategy based on estimated work efficiency and/or estimated cost of a second minimum production unit contained in the incomplete task procedure;

determining a cash flow time profile based on the cost time profile and the balance data;

The propulsion strategy is determined based on the cash flow time profile.

14. A construction project warning system, the system comprising:

The system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring acceptance information of a minimum production unit and record information of a task list in a plurality of task procedures of a construction project, the minimum production unit comprises space information, component information and task item information, and each minimum production unit corresponds to one final task item corresponding to a component unit in one space unit;

The prediction module is configured to predict a progress of at least a part of the incomplete task process based on the acceptance information and the labor information, and includes:

The early warning module is used for sending early warning in response to the pushing process does not meet preset conditions;

Wherein, for determining the estimated work efficiency and/or the estimated cost of the second minimum production unit based on the equivalent work efficiency and/or the equivalent cost and the spatial information, the prediction module is further configured to:

15. A construction project early warning device, which is characterized by comprising at least one processor and at least one memory;

the at least one memory is configured to store computer instructions;

the at least one processor is configured to execute at least some of the computer instructions to implement the method of any one of claims 1-13.

16. A computer readable storage medium storing computer instructions which, when read by a computer in the storage medium, perform the method of any one of claims 1-13.