CN117094487A - Intelligent overall method and device for bearing capacity production and electronic equipment - Google Patents
Intelligent overall method and device for bearing capacity production and electronic equipment Download PDFInfo
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Abstract
The application discloses an intelligent overall method, device and electronic equipment for producing bearing capacity, which are characterized in that schedulable personnel information, schedulable vehicle information and schedulable material information are obtained; calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; scheduling resource allocation corresponding to the production task according to the production bearing capacity; the production bearing capacity is calculated according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information, and the resource allocation corresponding to the production task is scheduled, so that the intelligent matching of the resources with the production plan and the temporary overhaul work is realized, the key technical problems that the resource coordination arrangement is difficult, the operation risk prevention and control is difficult and the like under the conditions of heavy production tasks and a large number of overhaul sites are effectively solved, and the intelligent management and control level of the electric overhaul work is effectively improved.
Description
Technical Field
The application relates to the technical field of management of power production bearing capacity, in particular to an intelligent overall method and device for producing bearing capacity and electronic equipment.
Background
The power equipment mainly comprises two major types of power generation equipment and power supply equipment, wherein the power generation equipment mainly comprises a power station boiler, a steam turbine, a gas turbine, a water turbine, a generator, a transformer and the like, and the power supply equipment mainly comprises power transmission lines, transformers, contactors and the like with various voltage levels. The transmission line is mainly erected above the ground and is used for conveying high electric energy. In order to ensure the normal operation of the power transmission work, after the power transmission line fails, the power transmission line needs to be overhauled manually so as to ensure the stable transmission of electric energy.
With the acceleration of the construction of a novel power system, the power grid scale is larger and larger, the power grid structure is more and more complex, and the overhaul task is also heavier and heavier. The existing production bearing capacity management is to manually evaluate the bearing capacities of various maintainers, vehicles and important tools and instruments to realize the matching and scheduling of the man-vehicle objects, the production plan and the operation types. However, manual evaluation is performed by experience, and accuracy and scientificity are poor, so that the problems of long communication time and low maintenance efficiency are caused.
Disclosure of Invention
The present application has been made to solve the above-mentioned technical problems. The embodiment of the application provides an intelligent overall method, device and electronic equipment for production bearing capacity, which are used for calculating the production bearing capacity according to schedulable personnel information, schedulable vehicle information and schedulable material information and scheduling resource allocation corresponding to production tasks so as to realize intelligent matching of resources with production plans and temporary maintenance work, effectively solve the key technical problems of difficult resource coordination arrangement, difficult operation risk prevention and control and the like under the conditions of heavy production tasks and a large number of maintenance sites, and effectively improve the intelligent management and control level of electric power maintenance work.
According to one aspect of the present application, there is provided an intelligent orchestration method for producing a bearing capacity, including: acquiring schedulable personnel information, schedulable vehicle information and schedulable material information; calculating production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; and scheduling the resource allocation corresponding to the production task according to the production bearing capacity.
In an embodiment, after the obtaining the schedulable personnel information, the schedulable vehicle information, and the schedulable material information, the intelligent overall method for producing the bearing capacity further includes: calculating a bearing capacity check value and a safety check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; the bearing capacity check value represents the bearing capacity of personnel, vehicles and materials, and the safety check value represents the operation safety coefficient of the operation personnel; the calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information comprises: and calculating the production bearing capacity according to the bearing capacity check value and the safety check value.
In an embodiment, said calculating said production load bearing capacity from said load bearing capacity check value and said safety check value comprises: and obtaining the production bearing capacity by weighted summation according to the bearing capacity check value and the safety check value.
In an embodiment, the calculating the bearing capacity check value and the safety check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information includes: calculating a personnel bearing capacity check value, a vehicle bearing capacity check value and a material bearing capacity check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; and calculating the bearing capacity check value according to the personnel bearing capacity check value, the vehicle bearing capacity check value and the material bearing capacity check value.
In an embodiment, the calculating the bearing capacity check value and the safety check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information includes: and calculating the safety check value according to the skill level of all schedulable personnel.
In an embodiment, before the scheduling the resource allocation corresponding to the production task according to the production bearing capacity, the intelligent overall method for producing the bearing capacity further includes: acquiring the production task; the scheduling the resource allocation corresponding to the production task according to the production bearing capacity comprises the following steps: and scheduling the resource allocation corresponding to the production task according to the production bearing capacity and the resource requirement corresponding to the production task.
In an embodiment, the acquiring schedulable personnel information, schedulable vehicle information, and schedulable material information includes: counting personnel operation information, vehicle occupation information and material occupation information; and determining the schedulable personnel information, the schedulable vehicle information and the schedulable material information according to the personnel counting operation information, the vehicle occupation information and the material occupation information.
In an embodiment, after calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information, and the schedulable material information, the intelligent overall method for the production bearing capacity further includes: and sending out an alarm notice when the schedulable personnel information indicates that the schedulable personnel number is lower than the preset personnel number, or the schedulable vehicle information indicates that the schedulable vehicle number is lower than the preset vehicle number, or the schedulable material information indicates that the schedulable material number is lower than the preset material number.
According to another aspect of the present application, there is provided an intelligent orchestration device for producing a bearing capacity, including: the information acquisition module is used for acquiring schedulable personnel information, schedulable vehicle information and schedulable material information; the bearing calculation module is used for calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; and the resource scheduling module is used for scheduling the resource allocation corresponding to the production task according to the production bearing capacity.
According to another aspect of the present application, there is provided an electronic apparatus including: a processor; a memory for storing the processor-executable instructions; the processor is configured to execute the intelligent overall method for producing the bearing capacity according to any one of the above.
According to the intelligent overall method, the intelligent overall device and the electronic equipment for producing the bearing capacity, the schedulable personnel information, the schedulable vehicle information and the schedulable material information are obtained; calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; scheduling resource allocation corresponding to the production task according to the production bearing capacity; the production bearing capacity is calculated according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information, and the resource allocation corresponding to the production task is scheduled, so that the intelligent matching of the resources with the production plan and the temporary overhaul work is realized, the key technical problems that the resource coordination arrangement is difficult, the operation risk prevention and control is difficult and the like under the conditions of heavy production tasks and a large number of overhaul sites are effectively solved, and the intelligent management and control level of the electric overhaul work is effectively improved.
Drawings
The above and other objects, features and advantages of the present application will become more apparent by describing embodiments of the present application in more detail with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate the application and together with the embodiments of the application, and not constitute a limitation to the application. In the drawings, like reference numerals generally refer to like parts or steps.
Fig. 1 is a schematic flow chart of an intelligent overall method for producing bearing capacity according to an exemplary embodiment of the present application.
Fig. 2 is a flow chart of an intelligent overall method for producing a bearing capacity according to another exemplary embodiment of the present application.
Fig. 3 is a flow chart of an intelligent overall method for producing a bearing capacity according to another exemplary embodiment of the present application.
Fig. 4 is a flow chart of an intelligent overall method for producing bearing capacity according to another exemplary embodiment of the present application.
Fig. 5 is a flow chart of an intelligent overall method for producing bearing capacity according to another exemplary embodiment of the present application.
Fig. 6 is a flow chart of an intelligent overall method for producing a bearing capacity according to another exemplary embodiment of the present application.
Fig. 7 is a schematic structural diagram of an intelligent overall device for producing bearing capacity according to another exemplary embodiment of the present application.
Fig. 8 is a block diagram of an electronic device according to an exemplary embodiment of the present application.
Detailed Description
Hereinafter, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein.
Fig. 1 is a schematic flow chart of an intelligent overall method for producing bearing capacity according to an exemplary embodiment of the present application. As shown in fig. 1, the intelligent overall method for producing the bearing capacity comprises the following steps:
step 110: schedulable personnel information, schedulable vehicle information, and schedulable material information are acquired.
Specifically, the influence factors such as the job task properties, personnel service capacity, mental states, safety constraints of vehicles and materials (especially special tools) of various jobs (including maintenance tasks and the like) are comprehensively considered, the classification and grading are carried out from the classification and grading of the job tasks and the personnel service capacity, the intelligent evaluation of the job risks, the real-time monitoring of the states of the personnel, the vehicles, the tools and the like, the bearing capacity early warning and the like are carried out in a multidimensional Shi Ce manner, a production bearing capacity evaluation model is built, the bearing capacities of the personnel, the vehicles and the tools are scientifically evaluated by means of a big data intelligent analysis technology, and the automatic retrieval and association of the job tasks and the personnel and the vehicles are realized.
In one embodiment, the specific implementation of step 110 may be: counting personnel operation information, vehicle occupation information and material occupation information; and determining schedulable personnel information, schedulable vehicle information and schedulable material information according to the personnel counting operation information, the vehicle occupation information and the material occupation information.
Step 120: and calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information.
According to the skill level of the schedulable personnel, a skill level management mechanism of the operators is established, and specifically, the key skills of the operations are combed in a professional and classified mode, the corresponding necessary skills are matched according to the A, B, C, D grades, and on the basis of mastering the necessary skills, the corresponding skill levels can be obtained after the experience points of the field work are met.
The class A skill personnel, the work responsible person and the business level are optimal, have experiences of all types of professional work, and have the capability of hosting power grid risks of 5 levels and above and work risks of 3-5 levels.
B class skill personnel, work responsible personnel, participate in more than 80% of professional work, and have the ability of hosting 6 class power grid risks and 4-5 class work risks.
Class C skill personnel and working class members are middle-class and above horizontal operators and can participate in the work of class 4-5 operation risks.
Class D skill personnel and working class members are primary workers or trainers and can participate in the class 5 operation risk work.
The method comprises the steps of distributing operators into operation subgroups according to work responsible persons and work class members, wherein each operation subgroup at least comprises 1 work responsible person and 1 work class member, the subgroup capable of carrying out 3-5-level operation risk work is an A-level subgroup, the subgroup capable of carrying out 4-5-level operation risk work is a B-level subgroup, carrying out operator bearing capacity evaluation by taking the subgroup as a unit, and dividing the operator bearing capacity into three states of sufficiency, early warning and saturation. Wherein, class a job group: class a skills plus class B skills or class a skills plus class C skills; class B job group: class a skills plus class D skills or class B skills plus class D skills; the personnel bearing capacity is sufficient: working states of team operators are counted in real time, two or more working groups can be scheduled at any time, and the operator bearing capacity is sufficient; personnel bearing capacity early warning: only one job team can be scheduled at any time, and the personnel bearing capacity is nearly saturated; the personnel bearing capacity is not enough: the operators cannot form an operation group to participate in the work, and the carrying capacity of the operators is saturated.
The vehicle bearing capacity is calculated according to the type of the dispatchable vehicle (including the number of vehicles, the number of people and the like). Specifically, the common vehicles in work areas are divided into: truck (2 seats), truck/pick-up (5 seats), IVECO (17 seats). The vehicle bearing capacity is sufficient: two or more vehicles can be scheduled at any time, and the bearing capacity of the vehicles is sufficient. Vehicle bearing capacity early warning: only one vehicle is available for dispatch, with the vehicle load capacity near saturation. The vehicle has insufficient bearing capacity: no vehicles are available for dispatching, and the vehicle bearing capacity is saturated.
And calculating the bearing capacity of the materials according to information such as the schedulable materials (the types and the number of the tools) and the like. In particular, different professions relate to different important tools, the variety is large, the number of the important tools is not large, and only one important tool can be arranged in particular, so that the important tools are divided into two stages. The bearing capacity of the important tools is sufficient: there is some important tool available for dispatch, which has sufficient load-bearing capacity. The important tools have insufficient bearing capacity: no important tools are available for dispatching, and the bearing capacity of the tools is saturated.
Step 130: and scheduling the resource allocation corresponding to the production task according to the production bearing capacity.
And summarizing the demands of personnel, vehicles and large tools according to task elements such as work content, work time, work risks and the like. And recommending personnel, vehicles and tools according to the task demands and the existing bearing capacity analysis results.
According to the intelligent overall method for producing the bearing capacity, the schedulable personnel information, the schedulable vehicle information and the schedulable material information are obtained; calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; scheduling resource allocation corresponding to the production task according to the production bearing capacity; the production bearing capacity is calculated according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information, and the resource allocation corresponding to the production task is scheduled, so that the intelligent matching of the resources with the production plan and the temporary overhaul work is realized, the key technical problems that the resource coordination arrangement is difficult, the operation risk prevention and control is difficult and the like under the conditions of heavy production tasks and a large number of overhaul sites are effectively solved, and the intelligent management and control level of the electric overhaul work is effectively improved.
Fig. 2 is a flow chart of an intelligent overall method for producing a bearing capacity according to another exemplary embodiment of the present application. As shown in fig. 2, after step 110, the above-mentioned intelligent overall method for producing the bearing capacity may further include:
step 140: and calculating a bearing capacity check value and a safety check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information.
The bearing capacity check value represents the bearing capacity of personnel, vehicles and materials, and the safety check value represents the operation safety coefficient of the operation personnel.
In one embodiment, the specific implementation of step 120 may be: and according to the bearing capacity check value and the safety check value, weighting and summing to obtain the production bearing capacity.
Correspondingly, the specific implementation manner of step 120 may be: and calculating the production bearing capacity according to the bearing capacity check value and the safety check value.
Fig. 3 is a flow chart of an intelligent overall method for producing a bearing capacity according to another exemplary embodiment of the present application. As shown in fig. 3, the step 140 may include:
step 141: and calculating a personnel bearing capacity check value, a vehicle bearing capacity check value and a material bearing capacity check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information.
Step 142: and calculating the bearing capacity check value according to the personnel bearing capacity check value, the vehicle bearing capacity check value and the material bearing capacity check value.
Fig. 4 is a flow chart of an intelligent overall method for producing bearing capacity according to another exemplary embodiment of the present application. As shown in fig. 4, the step 140 may include:
step 143: and calculating to obtain a safety check value according to the skill level of all schedulable personnel.
Specifically, the production capacity (total calculation value) m=r 1 S+R 2 N; wherein, the production bearing capacity check value n=personnel bearing capacity check value n1+vehicle bearing capacity check value n2+tool bearing capacity check value N3 (after the personnel and the vehicle are arranged according to the selected production scheduling scheme, the bearing capacity values of the rest of the operators, the vehicles and the large tools are respectively N1, N2 and N3). Safety check value s=s1+s2+ … +sn; the Sn is the safety coefficient of the selected operator, the higher the skill level of the operator is, the richer the working experience is, the higher the safety coefficient is, the safety coefficient of the class A skill personnel is 1, and the safety coefficients of the class B skill personnel, the class C skill personnel and the class D skill personnel are 0.9, 0.8 and 0.7 in sequence according to the experience value.
The weight coefficients R1 and R2 are respectively taken as 0.8 and 0.2 according to practical experience, and M takes the maximum value to obtain the optimal production scheduling scheme.
Fig. 5 is a flow chart of an intelligent overall method for producing bearing capacity according to another exemplary embodiment of the present application. As shown in fig. 5, before step 130, the above-mentioned intelligent overall method for producing the bearing capacity may further include:
step 150: and obtaining a production task.
Correspondingly, step 130 may include:
step 131: and scheduling the resource allocation corresponding to the production task according to the production bearing capacity and the resource requirement corresponding to the production task.
And calculating optimal personnel combination, vehicle and large tool arrangement matched with the task according to task requirements in the task pool by means of big data analysis. Specifically, after knowing the production task, the corresponding resource requirement can be calculated according to the type of the production task (such as an overhaul task, etc.), and the resource requirement of the production task can be counted according to the historical production task, for example, the resource requirements of a plurality of production tasks of the same type are calculated to obtain the resource requirement of the corresponding production task. In addition, the completion time of the corresponding production task can be estimated according to the completion progress of the historical production task, and the number of resource allocation and the use time are scheduled in combination with the operation time of each production task.
Fig. 6 is a flow chart of an intelligent overall method for producing a bearing capacity according to another exemplary embodiment of the present application. As shown in fig. 6, after step 120, the above-mentioned intelligent overall method for producing the bearing capacity may further include:
step 160: and when the schedulable personnel information indicates that the schedulable personnel quantity is lower than the preset personnel quantity, the schedulable vehicle information indicates that the schedulable vehicle quantity is lower than the preset vehicle quantity, and the schedulable material information indicates that the schedulable material quantity is lower than the preset material quantity, an alarm notification is sent.
Specifically, according to the states of dynamic analysis personnel, vehicles and important materials, the bearing capacity conditions of groups, professions, workers in the working areas, vehicles and important materials are displayed in real time, and bearing capacity analysis and early warning are realized. The bearing capacity analysis adopts color early warning, and three colors of green, yellow and red are used for distinguishing the saturation degree of the bearing capacity, wherein green represents that the bearing capacity is sufficient, yellow represents that the bearing capacity is nearly saturated, and red represents that the bearing capacity is saturated. The color early warning makes the carrying capacity of the person and the vehicle more visual, and the mouse floats on the team, so that the real-time busy idle state of all people in the team can be displayed.
Besides, the early warning detailed information can be rolled and prompted on the bearing capacity analysis interface, and the bearing capacity analysis can also carry out statistics and display on bearing capacity state statistics, work task query statistics and personnel work statistics. The module can inquire the statistics of personnel, the state and bearing capacity duty ratio of the vehicle, work tasks and personnel workload. The quantitative analysis of production data is realized.
Fig. 7 is a schematic structural diagram of an intelligent overall device for producing bearing capacity according to an exemplary embodiment of the present application. As shown in fig. 7, the intelligent integrated device 70 for producing the bearing capacity includes: an information acquisition module 71 for acquiring schedulable personnel information, schedulable vehicle information, and schedulable material information; a load calculating module 72 for calculating a production load capacity according to the schedulable personnel information, the schedulable vehicle information, and the schedulable material information; and a resource scheduling module 73, configured to schedule resource allocation corresponding to the production task according to the production bearing capacity.
According to the intelligent overall device for producing the bearing capacity, the information of schedulable personnel, the schedulable vehicle information and the schedulable material information are acquired through the information acquisition module 71; the load bearing calculation module 72 calculates the production load bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; the resource scheduling module 73 schedules resource allocation corresponding to the production task according to the production bearing capacity; the production bearing capacity is calculated according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information, and the resource allocation corresponding to the production task is scheduled, so that the intelligent matching of the resources with the production plan and the temporary overhaul work is realized, the key technical problems that the resource coordination arrangement is difficult, the operation risk prevention and control is difficult and the like under the conditions of heavy production tasks and a large number of overhaul sites are effectively solved, and the intelligent management and control level of the electric overhaul work is effectively improved.
In an embodiment, the information acquisition module 71 may be further configured to: counting personnel operation information, vehicle occupation information and material occupation information; and determining schedulable personnel information, schedulable vehicle information and schedulable material information according to the personnel counting operation information, the vehicle occupation information and the material occupation information.
In one embodiment, as shown in fig. 7, the intelligent integrated device 70 for producing bearing capacity may further include: a check calculation module 74 for calculating a bearing capacity check value and a safety check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; the bearing capacity check value represents the bearing capacity of personnel, vehicles and materials, and the safety check value represents the operation safety coefficient of the operation personnel. Correspondingly, the bearer calculation module 72 may be further configured to: and according to the bearing capacity check value and the safety check value, weighting and summing to obtain the production bearing capacity.
In an embodiment, the bearer calculation module 72 may be further configured to: and calculating the production bearing capacity according to the bearing capacity check value and the safety check value.
In one embodiment, the check computation module 74 may be further configured to: according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information, calculating a personnel bearing capacity check value, a vehicle bearing capacity check value and a material bearing capacity check value; and calculating the bearing capacity check value according to the personnel bearing capacity check value, the vehicle bearing capacity check value and the material bearing capacity check value.
In one embodiment, the check computation module 74 may be further configured to: and calculating to obtain a safety check value according to the skill level of all schedulable personnel.
In one embodiment, as shown in fig. 7, the intelligent integrated device 70 for producing bearing capacity may further include: the task acquisition module 75 is configured to acquire a production task. Correspondingly, the resource scheduling module 73 may be further configured to: and scheduling the resource allocation corresponding to the production task according to the production bearing capacity and the resource requirement corresponding to the production task.
In one embodiment, as shown in fig. 7, the intelligent integrated device 70 for producing bearing capacity may further include: the alert notification module 76 is configured to issue an alert notification when the schedulable person information indicates that the schedulable person number is less than the preset person number, the schedulable vehicle information indicates that the schedulable vehicle number is less than the preset vehicle number, or the schedulable material information indicates that the schedulable material number is less than the preset material number.
Next, an electronic device according to an embodiment of the present application is described with reference to fig. 8. The electronic device may be either or both of the first device and the second device, or a stand-alone device independent thereof, which may communicate with the first device and the second device to receive the acquired input signals therefrom.
Fig. 8 illustrates a block diagram of an electronic device according to an embodiment of the application.
As shown in fig. 8, the electronic device 10 includes one or more processors 11 and a memory 12.
The processor 11 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.
Memory 12 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 11 to implement the methods of the various embodiments of the present application described above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, and the like may also be stored in the computer-readable storage medium.
In one example, the electronic device 10 may further include: an input device 13 and an output device 14, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
When the electronic device is a stand-alone device, the input means 13 may be a communication network connector for receiving the acquired input signals from the first device and the second device.
In addition, the input device 13 may also include, for example, a keyboard, a mouse, and the like.
The output device 14 may output various information to the outside, including the determined distance information, direction information, and the like. The output means 14 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device 10 that are relevant to the present application are shown in fig. 8 for simplicity, components such as buses, input/output interfaces, etc. are omitted. In addition, the electronic device 10 may include any other suitable components depending on the particular application.
The computer program product may write program code for performing operations of embodiments of the present application in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the application to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (10)
1. An intelligent overall method for producing bearing capacity, which is characterized by comprising the following steps:
acquiring schedulable personnel information, schedulable vehicle information and schedulable material information;
calculating production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; and
and scheduling the resource allocation corresponding to the production task according to the production bearing capacity.
2. The intelligent orchestration method for production load capacity according to claim 1, wherein after the schedulable personnel information, the schedulable vehicle information, and the schedulable material information are acquired, the intelligent orchestration method for production load capacity further comprises:
calculating a bearing capacity check value and a safety check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; the bearing capacity check value represents the bearing capacity of personnel, vehicles and materials, and the safety check value represents the operation safety coefficient of the operation personnel;
the calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information comprises:
and calculating the production bearing capacity according to the bearing capacity check value and the safety check value.
3. The intelligent orchestration method for production capacities according to claim 2, wherein calculating the production capacities from the capacities check values and the safety check values comprises:
and obtaining the production bearing capacity by weighted summation according to the bearing capacity check value and the safety check value.
4. The intelligent orchestration method for producing a load-bearing capacity according to claim 2, wherein calculating a load-bearing capacity check value and a safety check value according to the schedulable personnel information, the schedulable vehicle information, and the schedulable material information includes:
calculating a personnel bearing capacity check value, a vehicle bearing capacity check value and a material bearing capacity check value according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; and
and calculating the bearing capacity check value according to the personnel bearing capacity check value, the vehicle bearing capacity check value and the material bearing capacity check value.
5. The intelligent orchestration method for producing a load-bearing capacity according to claim 2, wherein calculating a load-bearing capacity check value and a safety check value according to the schedulable personnel information, the schedulable vehicle information, and the schedulable material information includes:
and calculating the safety check value according to the skill level of all schedulable personnel.
6. The intelligent orchestration method for production bearing capacity according to claim 1, wherein before the scheduling of resource allocation corresponding to production tasks according to the production bearing capacity, the intelligent orchestration method for production bearing capacity further comprises:
acquiring the production task;
the scheduling the resource allocation corresponding to the production task according to the production bearing capacity comprises the following steps:
and scheduling the resource allocation corresponding to the production task according to the production bearing capacity and the resource requirement corresponding to the production task.
7. The intelligent orchestration method for production capacity according to claim 1, wherein the obtaining schedulable personnel information, schedulable vehicle information, and schedulable supplies information includes:
counting personnel operation information, vehicle occupation information and material occupation information; and
and determining the schedulable personnel information, the schedulable vehicle information and the schedulable material information according to the personnel counting operation information, the vehicle occupation information and the material occupation information.
8. The intelligent orchestration method for production load capacity according to claim 1, wherein after the calculation of production load capacity according to the schedulable personnel information, the schedulable vehicle information, and the schedulable material information, the intelligent orchestration method for production load capacity further comprises:
and sending out an alarm notice when the schedulable personnel information indicates that the schedulable personnel number is lower than the preset personnel number, or the schedulable vehicle information indicates that the schedulable vehicle number is lower than the preset vehicle number, or the schedulable material information indicates that the schedulable material number is lower than the preset material number.
9. An intelligent overall device for producing bearing capacity, comprising:
the information acquisition module is used for acquiring schedulable personnel information, schedulable vehicle information and schedulable material information;
the bearing calculation module is used for calculating the production bearing capacity according to the schedulable personnel information, the schedulable vehicle information and the schedulable material information; and
and the resource scheduling module is used for scheduling the resource allocation corresponding to the production task according to the production bearing capacity.
10. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to perform the intelligent orchestration method of production capacity according to any one of the preceding claims 1-8.
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| CN202310710965.9A CN117094487A (en) | 2023-06-15 | 2023-06-15 | Intelligent overall method and device for bearing capacity production and electronic equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117634851A (en) * | 2024-01-23 | 2024-03-01 | 广州市勤思网络科技有限公司 | Ship-personnel scheduling method and device applied to sand production of ship |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117634851A (en) * | 2024-01-23 | 2024-03-01 | 广州市勤思网络科技有限公司 | Ship-personnel scheduling method and device applied to sand production of ship |
| CN117634851B (en) * | 2024-01-23 | 2024-07-16 | 广州市勤思网络科技有限公司 | Ship-personnel scheduling method and device applied to sand production of ship |
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