CN112734147A - Method and device for equipment evaluation management - Google Patents
Method and device for equipment evaluation management Download PDFInfo
- Publication number
- CN112734147A CN112734147A CN201911029673.9A CN201911029673A CN112734147A CN 112734147 A CN112734147 A CN 112734147A CN 201911029673 A CN201911029673 A CN 201911029673A CN 112734147 A CN112734147 A CN 112734147A
- Authority
- CN
- China
- Prior art keywords
- time
- working
- statistical
- working time
- ending
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000011156 evaluation Methods 0.000 title claims abstract description 25
- 238000012545 processing Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 10
- 230000002159 abnormal effect Effects 0.000 claims description 9
- 238000007726 management method Methods 0.000 description 21
- 238000010586 diagram Methods 0.000 description 12
- 230000008859 change Effects 0.000 description 8
- 230000006870 function Effects 0.000 description 8
- 238000004891 communication Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 4
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
Abstract
The invention discloses a method and a device for equipment evaluation management, and relates to the technical field of warehouse logistics. One embodiment of the method comprises: acquiring working time data of equipment, wherein the working time data comprises first working time for the equipment to execute each task; judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period; evaluating the device based on the second operating time and the first operating time that is not split. The method and the device can comprehensively and objectively evaluate the equipment, and are high in accuracy.
Description
Technical Field
The invention relates to the technical field of warehouse logistics, in particular to a method and a device for equipment evaluation management.
Background
In measuring whether the equipment workload in the warehouse is saturated or not, the operating time of the equipment is generally evaluated. Currently, the operating time of a plant is usually estimated by the production time.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
(1) in the prior art, the difference of the working time of the equipment at different moments is ignored, the more comprehensive and objective reaction on the working time or the utilization rate of the equipment cannot be realized, and the evaluation result is more comprehensive;
(2) and calculating the deviation of the working time of the equipment by using an estimation mode.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for device evaluation management, which can comprehensively and objectively evaluate a device and have high accuracy.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of device evaluation management, including:
acquiring working time data of equipment, wherein the working time data comprises first working time for the equipment to execute each task;
judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period;
evaluating the device based on the second operating time and the first operating time that is not split.
Optionally, the first operating time comprises: a start time and an end time for executing the task; the statistical time period refers to a time range between two adjacent statistical time points; judging whether the first working time spans a statistical time period or not, comprising the following steps:
taking a statistical time point which is before the starting time and is closest to the starting time as a starting time point corresponding to the starting time, and taking a statistical time point which is before the ending time and is closest to the ending time as an ending time point corresponding to the ending time; or, taking a statistical time point which is after the start time and is closest to the start time as a start time point corresponding to the start time, and taking a statistical time point which is after the end time and is closest to the end time as an end time point corresponding to the end time;
judging whether the starting time point corresponding to the starting time is the same as the ending time point corresponding to the ending time; if yes, the first working time does not span the statistical time period; otherwise, the first working time spans the statistical time period.
Optionally, evaluating the device based on the second working time and the first non-split working time includes:
and determining the working time length or the utilization rate of the equipment in each statistical time period in the preset time range based on the second working time of the equipment in the preset time range and the first non-split working time.
Optionally, after acquiring the operating time data of the device, the method further includes: and eliminating abnormal first working time in the working time data.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for device evaluation management, including:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring working time data of the device, and the working time data comprises first working time for the device to execute each task;
the splitting module is used for judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period;
an evaluation module that evaluates the device based on the second operating time and the first operating time that is not split.
Optionally, the first operating time comprises: a start time and an end time for executing the task; the statistical time period refers to a time range between two adjacent statistical time points; the splitting module judges whether the first working time spans a statistical time period, and comprises the following steps:
taking a statistical time point which is before the starting time and is closest to the starting time as a starting time point corresponding to the starting time, and taking a statistical time point which is before the ending time and is closest to the ending time as an ending time point corresponding to the ending time; or, taking a statistical time point which is after the start time and is closest to the start time as a start time point corresponding to the start time, and taking a statistical time point which is after the end time and is closest to the end time as an end time point corresponding to the end time;
judging whether the starting time point corresponding to the starting time is the same as the ending time point corresponding to the ending time; if yes, the first working time does not span the statistical time period; otherwise, the first working time spans the statistical time period.
Optionally, the evaluating module evaluates the device based on the second working time and the first non-split working time, including:
and determining the working time length or the utilization rate of the equipment in each statistical time period in the preset time range based on the second working time of the equipment in the preset time range and the first non-split working time.
Optionally, the obtaining module is further configured to: after the working time data of the equipment is acquired, the abnormal first working time in the working time data is removed.
According to a third aspect of the embodiments of the present invention, there is provided an electronic device for device evaluation management, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method provided by the first aspect of the embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method provided by the first aspect of embodiments of the present invention.
One embodiment of the above invention has the following advantages or benefits: the working time of the statistical time period is divided into the working time of the non-statistical time period, and the equipment is evaluated based on the working time of the non-statistical time period, so that the equipment can be comprehensively and objectively evaluated, and the accuracy is high.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic diagram of a main flow of a method of device evaluation management according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating results of a method for device assessment management in an alternative embodiment of the invention;
FIG. 3 is a schematic diagram of the main modules of an apparatus for equipment assessment management according to an embodiment of the present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
According to an aspect of an embodiment of the present invention, there is provided a method of device evaluation management.
Fig. 1 is a schematic diagram of a main flow of a device evaluation management method according to an embodiment of the present invention, and as shown in fig. 1, the device evaluation management method includes: step S101, step S102, and step S103.
In step S101, work time data of a device is acquired, where the work time data includes a first work time for the device to perform each task.
The first operating time includes: the start time and the end time for executing the task may further include the task type. Taking an Automated Guided Vehicle (AGV) device as an example, in a warehouse, AGVs mainly perform a rack transporting task of warehouse-out, warehouse-in, and inventory. Therefore, the working time of the AGV is the sum of the time for executing the ex-warehouse, in-warehouse and inventory tasks. In the practical application process, a data table recording all tasks (such as warehouse-out, warehouse-in, inventory, charging, parking and the like) of the AGV can be maintained, and the table records the type of the tasks executed by the AGV, the starting time of the executed tasks and the finishing time of the completion of the tasks. And calculating the difference value between the start time of executing the task and the finish time of completing the task, namely the working time of the AGV. It should be noted that the device in the present invention may refer to not only an AGV device, but also other devices, such as an unmanned aerial vehicle device, a charging device for charging an unmanned aerial vehicle or an AGV, and the like.
Optionally, after acquiring the operating time data of the device, the method further includes: and eliminating abnormal first working time in the working time data. One skilled in the art can define the abnormal data in advance, so as to eliminate the abnormal data in the working time data according to the predefined definition. Illustratively, the average time for an AGV to perform a task (ex, in, and inventory) is about 4 minutes, where 90% of the tasks can be completed in an hour. Therefore, data that executes a task for more than 1 hour may be defined in advance as abnormal data. And after the working time data of the equipment is acquired, eliminating the first working time with the working time length exceeding 1 hour in all the first working times.
S102, judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period;
the statistical time period refers to a time range between two adjacent statistical time points. Illustratively, the statistical time period is one hour, one day, one month, one year, or the like. The statistical time points refer to a start time point and an end time point of the statistical time period, and the start time point and the end time point can be set in a user-defined mode, for example, the statistical time period is one hour, and the corresponding statistical time points are 20:32:09 and 21:32: 09. It should be noted that the statistical time point may also be an integer time point, for example, the statistical time period is one hour, and the corresponding statistical time points are 00:00:00 and 01:00: 00.
And when the time range spanned by the starting time and the ending time point of the first working time is larger and the starting time and the ending time point are not in the same statistical time period, judging that the first working time spans the statistical time period.
Optionally, the determining whether the first working time spans the statistical time period includes:
taking a statistical time point which is before the starting time of the first working time and is closest to the starting time of the first working time as a starting time point corresponding to the starting time of the first working time, and taking a statistical time point which is before the ending time of the first working time and is closest to the ending time of the first working time as an ending time point corresponding to the ending time of the first working time; or taking a statistical time point which is after the start time of the first working time and is closest to the start time of the first working time as a start time point corresponding to the start time of the first working time, and taking a statistical time point which is after the end time of the first working time and is closest to the end time of the first working time as an end time point corresponding to the end time of the first working time;
judging whether the starting time point corresponding to the starting time of the first working time is the same as the ending time point corresponding to the ending time of the first working time; if yes, the first working time does not span the statistical time period; otherwise, the first working time spans the statistical time period.
For example, the statistical time point is an hour point, the statistical time period is one hour, and the first operating time of the AGV device is shown in table 1.
TABLE 1 first operating time of AGV device
And converting the starting time and the ending time into a starting time point and an ending time point, wherein if a forward rounding mode is adopted, the starting time point corresponding to the starting time is 2018/08/2610: 00:00, the ending time point corresponding to the ending time is 2018/08/2611: 00:00, and the starting time point and the ending time point are different and span a statistical time period of the first working time in the table 1.
For another example, the counted time point is an hour point, the counted time period is one hour, and the first operating time of the AGV device is shown in table 2.
TABLE 2 first operating time of AGV device
And converting the starting time and the ending time into a starting time point and an ending time point, wherein if a forward rounding mode is adopted, the starting time point corresponding to the starting time is 2018/08/2610: 00:00, the ending time point corresponding to the ending time is 2018/08/2610: 00:00, and the first working time in the table 2 is the same as the starting time point and the ending time point and does not span a statistical time period.
In some embodiments, splitting the first work time into a plurality of second work times that do not span a statistical time period comprises:
copying a plurality of first working hours, data _1, data _2, … … and data _ n; n is the number of the first working time spanning the statistical time period;
the end time of data _1 is set to: after the starting time of the first working time, obtaining a first second working time at a statistical time point which is closest to the starting time of the first working time;
setting the start time of the data _ i as the end time of the data _ (i-1), and setting the end time of the data _ i as: obtaining an ith second working time at a statistical time point which is after the start time of the data _ i and is closest to the start time of the data _ i, wherein i is 2, 3, … … or n-1;
the start time of data _ n is set to: and obtaining the nth second working time at the statistical time point which is closest to the end time of the data _ (n-1) after the end time of the data _ (n-1).
Illustratively, the time unit is seconds. Taking the first working time in table 1 as an example, the first working time spans two statistical time periods, and therefore needs to be split into two second working times, which includes the following specific steps:
copying two first working hours, data _1 and data _ 2;
the end time of data _1 is set to: after the starting time of the first working time, obtaining a first second working time at a statistical time point which is closest to the starting time of the first working time;
the start time of data _2 is set to: and obtaining a second working time according to the end time of the data _ 1.
See tables 3 and 4 for the second working time after splitting.
TABLE 3 first and second hours after splitting
TABLE 4 second working hours after splitting
For each working time, the time difference between the ending time and the starting time in the working time is the working duration corresponding to the working time. Taking table 3 as an example, the time difference between the start time 2018/08/2610: 56:03 and the end time 2018/08/2611: 00:00 is 3 minutes and 57 seconds, and the operating time period is 3 minutes and 57 seconds.
In other embodiments, splitting the first operating time into a plurality of second operating times that do not span a statistical time period comprises:
copying a plurality of first working hours, data _1, data _2, … … and data _ n; n is the number of the first working time spanning the statistical time period;
the end time of data _1 is set to: after the starting time of the first working time, counting a time point-a time unit which is closest to the starting time of the first working time to obtain a first second working time;
setting the start time of the data _ i as a statistical time point which is closest to the end time of the data _ (i-1) after the end time of the data _ i, and setting the end time of the data _ i as: obtaining an ith second working time at a statistical time point which is after the start time of the data _ i and is closest to the start time of the data _ i, wherein i is 2, 3, … … or n-1;
the start time of data _ n is set to: and obtaining the nth second working time at the statistical time point which is closest to the end time of the data _ (n-1) after the end time of the data _ (n-1).
The time units may be seconds, hours, days, etc. Illustratively, the time unit is seconds. Taking the first working time in table 1 as an example, the first working time spans two statistical time periods, and therefore needs to be split into two second working times, which includes the following specific steps:
copying two first working hours, data _1 and data _ 2;
the end time of data _1 is set to: after the starting time of the first working time, counting the time point-1 second closest to the starting time of the first working time to obtain a first second working time;
the start time of data _2 is set to: and obtaining a second working time at the statistical time point which is closest to the end time of the data _ (n-1) after the end time of the data _ 1.
See tables 5 and 6 for the second working time after splitting.
TABLE 5 first and second hours after splitting
TABLE 6 second working time after splitting
After one first working time is split into a plurality of second working times, the end time of the last second working time obtained by splitting is the working time corresponding to the working time; for each remaining second working time, the time difference between the ending time and the starting time in the working time plus one time unit is the working time length corresponding to the working time. Taking Table 5 as an example, the time difference between start time 2018/08/2610: 56:03 and end time 2018/08/2610: 59:59 is 3 minutes 56 seconds, and the operating time period is 3 minutes 57 seconds.
In the practical application process, when the order of magnitude of the task execution record of the equipment is larger, the function can be written in a programming mode, so that data exist in the function in a traversing mode, a data set is split, and the splitting efficiency can be improved. Specifically, the method comprises the following steps:
(1) establishing four variables in the first working time, wherein the four variables are respectively as follows: start time point, end time point, and flag and second. The starting time point is a statistical time point corresponding to the starting time. For example, the starting time point is converted into rounded-forward hour data by the starting time, such as: 2018/08/2610: 56:03 to 2018/08/2610: 00: 00. The ending time point is a statistical time point corresponding to the ending time, for example, the ending time point is converted into rounded-forward hour data. The flag is a mark for judging whether the starting hour is equal to the ending hour, and if so, the flag is 0; if not, the flag is 1; second defaults to 0, aiding in supplementing the missing one time unit (e.g., 1 second) in step (2).
(2) And taking out the first working time when the flag is 1, and copying the first working time to obtain data1, data2, … … and datan. The end time of change data1 is: the latest statistical time point-one time unit after the starting time point of the current first working time, second is set to one time unit. The start time of the change data2 is a statistical time point closest to the end time of data1 after the end time of data1, and so on for the change data3 to data (n-1). And for datan, changing the statistical time point with the starting time being the data (n-1) ending time and the closest distance to the data (n-1) ending time, and changing the ending time point with the ending time being the corresponding ending time point of the current first working time.
(3) And merging all the split second working time data1, data2, … … and datan and the un-split first working time to obtain a data set, and updating the start hour, the end hour and the flag according to the new data set. And (5) executing the step 2 and the step 3 until all the flags are 0.
Illustratively, the statistical time point is an hour point, the statistical time period is one hour, and the time unit is seconds. Take the first operating time of devices 100282 and 100283 in table 7 as an example.
First operating time of devices 100282 and 100283 in Table 7
Splitting the first working time into a plurality of second working times which do not cross the statistical time period, wherein the steps comprise:
(1) establishing four variables in the first working time, wherein the four variables are respectively as follows: start time point, end time point, and flag and second. The starting time point is converted into hour data rounded up in the past by the starting time, such as: 2018/08/2610: 56:03 to 2018/08/2610: 00: 00. The ending time point is the time of the ending and is converted into the hour data rounded up before. The flag is a mark for judging whether the starting hour is equal to the ending hour, and if so, the flag is 0; if not, the flag is 1; second defaults to 0, assisting in replenishing the missing 1 second in step (2). See table 8 for data after variables were established.
TABLE 8 data after variables are established
(2) And taking out the first working time (namely the second first working time) when the flag is 1, and copying the data1 and the data 2. The end time of change data1 is (end hour-1 second), and second is set to 1. The start time of change data2 is the end hour. See tables 8 and 9 for modified data.
TABLE 8 data1
Table 9 data2
(3) And merging all the split second working time data1, data2 and flag which are 1 to obtain a data set, and referring to table 10.
Table 10 merged data set
S103, evaluating the equipment based on the second working time and the first non-split working time.
The evaluation index can be selectively set according to actual conditions. For example, the operating time, the utilization rate of the equipment are evaluated, or the average operating time, the utilization rate, etc. of all the equipment are evaluated.
Optionally, evaluating the device based on the second working time and the first non-split working time includes:
and determining the working time length or the utilization rate of the equipment in each statistical time period in the preset time range based on the second working time of the equipment in the preset time range and the first non-split working time.
For example, taking device 100283 in table 10 as an example, the operation duration is (end time-start time) + second in each operation duration. According to the starting hour recorded by the trolley task, the total working time of each trolley per hour can be counted, and the working time details of each trolley counted per hour can be obtained.
For example, when calculating the overall utilization of all the devices in the warehouse, the number of all the vehicles in the warehouse is acquired, and is not limited to the number of all the devices performing the task. Therefore, to know the number of all the devices in the warehouse, the number of all the devices in the warehouse needs to be counted from the device information total table of the warehouse. And according to the working time of the equipment and the total equipment number, the equipment utilization rate per hour can be counted.
If the utilization rate of each device is calculated, the utilization rate of each device per hour is equal to the working time (h)/1 × 100% of each vehicle per hour.
And if the overall utilization rate of all the equipment in the warehouse is calculated, the overall utilization rate of all the equipment in the warehouse is the sum of the working time of each equipment per hour (h)/(1) of all the trolleys in the warehouse) and 100%.
According to the above method, the hourly device utilization rate details can be counted, and the hourly utilization rate detail data can be drawn into a statistical chart, as shown in fig. 2 below. With the combination of fig. 2, the peak-to-peak time interval of the utilization rate of the equipment and the change situation of the utilization rate can be seen more intuitively, which is helpful for better judging whether the workload situation of the equipment and the quantity of the equipment are sufficient or not. The method can comprehensively, visually and comprehensively reflect the change condition of the equipment utilization rate in each statistical time period of the AGV in the warehouse, and further carry out adaptive scheduling and planning on the equipment according to the change condition.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for implementing the above method.
Fig. 3 is a schematic diagram of main blocks of an apparatus for device evaluation management according to an embodiment of the present invention, and as shown in fig. 3, an apparatus 300 for device evaluation management includes:
an obtaining module 301, configured to obtain working time data of a device, where the working time data includes a first working time for the device to execute each task;
the splitting module 302 is used for judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period;
an evaluation module 303 that evaluates the device based on the second operating time and the first operating time that is not split.
Optionally, the first operating time comprises: a start time and an end time for executing the task; the statistical time period refers to a time range between two adjacent statistical time points; the splitting module judges whether the first working time spans a statistical time period, and comprises the following steps:
taking a statistical time point which is before the starting time and is closest to the starting time as a starting time point corresponding to the starting time, and taking a statistical time point which is before the ending time and is closest to the ending time as an ending time point corresponding to the ending time; or, taking a statistical time point which is after the start time and is closest to the start time as a start time point corresponding to the start time, and taking a statistical time point which is after the end time and is closest to the end time as an end time point corresponding to the end time;
judging whether the starting time point corresponding to the starting time is the same as the ending time point corresponding to the ending time; if yes, the first working time does not span the statistical time period; otherwise, the first working time spans the statistical time period.
Optionally, the evaluating module evaluates the device based on the second working time and the first non-split working time, including:
and determining the working time length or the utilization rate of the equipment in each statistical time period in the preset time range based on the second working time of the equipment in the preset time range and the first non-split working time.
Optionally, the obtaining module is further configured to: after the working time data of the equipment is acquired, the abnormal first working time in the working time data is removed.
According to a third aspect of the embodiments of the present invention, there is provided an electronic device for device evaluation management, including:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method provided by the first aspect of the embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method provided by the first aspect of embodiments of the present invention.
Fig. 4 illustrates an exemplary system architecture 400 to which the method of device assessment management or apparatus of device assessment management of embodiments of the present invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405. The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 401, 402, 403. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for device evaluation management provided by the embodiment of the present invention is generally executed by the server 405, and accordingly, the device for device evaluation management is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 501.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor comprising: the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring working time data of the device, and the working time data comprises first working time for the device to execute each task; the splitting module is used for judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period; an evaluation module that evaluates the device based on the second operating time and the first operating time that is not split. Where the names of these modules do not in some cases constitute a limitation of the module itself, for example, a split module may also be described as a "module that evaluates the device based on the second operating time and the first operating time that is not split".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring working time data of equipment, wherein the working time data comprises first working time for the equipment to execute each task; judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period; evaluating the device based on the second operating time and the first operating time that is not split.
According to the technical scheme of the embodiment of the invention, the equipment can be comprehensively and objectively evaluated by dividing the working time crossing the statistical time period into the working time not crossing the statistical time period and evaluating the equipment based on the working time not crossing the statistical time period, and the accuracy is high.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of device assessment management, comprising:
acquiring working time data of equipment, wherein the working time data comprises first working time for the equipment to execute each task;
judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period;
evaluating the device based on the second operating time and the first operating time that is not split.
2. The method of claim 1, wherein the first operating time comprises: a start time and an end time for executing the task; the statistical time period refers to a time range between two adjacent statistical time points; judging whether the first working time spans a statistical time period or not, comprising the following steps:
taking a statistical time point which is before the starting time and is closest to the starting time as a starting time point corresponding to the starting time, and taking a statistical time point which is before the ending time and is closest to the ending time as an ending time point corresponding to the ending time; or, taking a statistical time point which is after the start time and is closest to the start time as a start time point corresponding to the start time, and taking a statistical time point which is after the end time and is closest to the end time as an end time point corresponding to the end time;
judging whether the starting time point corresponding to the starting time is the same as the ending time point corresponding to the ending time; if yes, the first working time does not span the statistical time period; otherwise, the first working time spans the statistical time period.
3. The method of claim 1, wherein evaluating the device based on the second operating time and the first operating time that is not split comprises:
and determining the working time length or the utilization rate of the equipment in each statistical time period in the preset time range based on the second working time of the equipment in the preset time range and the first non-split working time.
4. The method of claim 1, wherein after obtaining the operating time data for the device, further comprising: and eliminating abnormal first working time in the working time data.
5. An apparatus for equipment evaluation management, comprising:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring working time data of the device, and the working time data comprises first working time for the device to execute each task;
the splitting module is used for judging whether the first working time spans a statistical time period; if so, splitting the first working time into a plurality of second working times which do not span the statistical time period;
an evaluation module that evaluates the device based on the second operating time and the first operating time that is not split.
6. The apparatus of claim 5, wherein the first operating time comprises: a start time and an end time for executing the task; the statistical time period refers to a time range between two adjacent statistical time points; the splitting module judges whether the first working time spans a statistical time period, and comprises the following steps:
taking a statistical time point which is before the starting time and is closest to the starting time as a starting time point corresponding to the starting time, and taking a statistical time point which is before the ending time and is closest to the ending time as an ending time point corresponding to the ending time; or, taking a statistical time point which is after the start time and is closest to the start time as a start time point corresponding to the start time, and taking a statistical time point which is after the end time and is closest to the end time as an end time point corresponding to the end time;
judging whether the starting time point corresponding to the starting time is the same as the ending time point corresponding to the ending time; if yes, the first working time does not span the statistical time period; otherwise, the first working time spans the statistical time period.
7. The apparatus of claim 5, wherein the evaluation module evaluates the device based on the second operating time and the first operating time that is not split comprises:
and determining the working time length or the utilization rate of the equipment in each statistical time period in the preset time range based on the second working time of the equipment in the preset time range and the first non-split working time.
8. The apparatus of claim 5, wherein the acquisition module is further to: after the working time data of the equipment is acquired, the abnormal first working time in the working time data is removed.
9. An electronic device for device assessment management, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911029673.9A CN112734147A (en) | 2019-10-28 | 2019-10-28 | Method and device for equipment evaluation management |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911029673.9A CN112734147A (en) | 2019-10-28 | 2019-10-28 | Method and device for equipment evaluation management |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112734147A true CN112734147A (en) | 2021-04-30 |
Family
ID=75589134
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911029673.9A Pending CN112734147A (en) | 2019-10-28 | 2019-10-28 | Method and device for equipment evaluation management |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112734147A (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110154360A1 (en) * | 2009-12-17 | 2011-06-23 | Fujitsu Limited | Job analyzing method and apparatus |
| US20130212521A1 (en) * | 2010-10-11 | 2013-08-15 | Teachscape, Inc. | Methods and systems for use with an evaluation workflow for an evidence-based evaluation |
| US20140143773A1 (en) * | 2012-11-21 | 2014-05-22 | International Business Machines Corporation | Method and system for running a virtual appliance |
| US20140207504A1 (en) * | 2013-01-21 | 2014-07-24 | International Business Machines Corporation | System and method of calculating task efforts and applying the results for resource planning |
| CN106781454A (en) * | 2016-11-25 | 2017-05-31 | 东软集团股份有限公司 | The appraisal procedure and device of driving behavior |
| CN107122865A (en) * | 2017-05-02 | 2017-09-01 | 泰康保险集团股份有限公司 | Method, system and the terminal device estimated are counted by flow |
| JP2018180589A (en) * | 2017-04-03 | 2018-11-15 | 株式会社ジェイテクト | Workability evaluation system |
| CN109002377A (en) * | 2018-07-26 | 2018-12-14 | 郑州云海信息技术有限公司 | A kind of processor detection method, processor detection device and computer equipment |
| CN109345109A (en) * | 2018-09-26 | 2019-02-15 | 中国平安人寿保险股份有限公司 | A kind of Stakeholder Evaluation method and terminal device based on classification prediction model |
| CN109996258A (en) * | 2017-12-31 | 2019-07-09 | 中国移动通信集团辽宁有限公司 | Wireless network utilization appraisal procedure, calculates equipment and storage medium at device |
| CN110019932A (en) * | 2017-10-31 | 2019-07-16 | 北京国双科技有限公司 | The method and device of data processing |
| CN110019367A (en) * | 2017-12-28 | 2019-07-16 | 北京京东尚科信息技术有限公司 | A kind of method and apparatus of statistical data feature |
| CN110320825A (en) * | 2018-03-28 | 2019-10-11 | 北京京东尚科信息技术有限公司 | A kind of method and apparatus counting equipment state |
-
2019
- 2019-10-28 CN CN201911029673.9A patent/CN112734147A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110154360A1 (en) * | 2009-12-17 | 2011-06-23 | Fujitsu Limited | Job analyzing method and apparatus |
| US20130212521A1 (en) * | 2010-10-11 | 2013-08-15 | Teachscape, Inc. | Methods and systems for use with an evaluation workflow for an evidence-based evaluation |
| US20140143773A1 (en) * | 2012-11-21 | 2014-05-22 | International Business Machines Corporation | Method and system for running a virtual appliance |
| US20140207504A1 (en) * | 2013-01-21 | 2014-07-24 | International Business Machines Corporation | System and method of calculating task efforts and applying the results for resource planning |
| CN106781454A (en) * | 2016-11-25 | 2017-05-31 | 东软集团股份有限公司 | The appraisal procedure and device of driving behavior |
| JP2018180589A (en) * | 2017-04-03 | 2018-11-15 | 株式会社ジェイテクト | Workability evaluation system |
| CN107122865A (en) * | 2017-05-02 | 2017-09-01 | 泰康保险集团股份有限公司 | Method, system and the terminal device estimated are counted by flow |
| CN110019932A (en) * | 2017-10-31 | 2019-07-16 | 北京国双科技有限公司 | The method and device of data processing |
| CN110019367A (en) * | 2017-12-28 | 2019-07-16 | 北京京东尚科信息技术有限公司 | A kind of method and apparatus of statistical data feature |
| CN109996258A (en) * | 2017-12-31 | 2019-07-09 | 中国移动通信集团辽宁有限公司 | Wireless network utilization appraisal procedure, calculates equipment and storage medium at device |
| CN110320825A (en) * | 2018-03-28 | 2019-10-11 | 北京京东尚科信息技术有限公司 | A kind of method and apparatus counting equipment state |
| CN109002377A (en) * | 2018-07-26 | 2018-12-14 | 郑州云海信息技术有限公司 | A kind of processor detection method, processor detection device and computer equipment |
| CN109345109A (en) * | 2018-09-26 | 2019-02-15 | 中国平安人寿保险股份有限公司 | A kind of Stakeholder Evaluation method and terminal device based on classification prediction model |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110019367B (en) | Method and device for counting data characteristics | |
| CN109298948B (en) | Distributed computing method and system | |
| US20210312359A1 (en) | Method and device for scheduling automated guided vehicle | |
| CN109345166B (en) | Method and apparatus for generating information | |
| CN111930306A (en) | Data processing method and device | |
| CN113220705A (en) | Slow query identification method and device | |
| CN113312553A (en) | Method and device for determining user label | |
| CN112446651A (en) | Method and device for monitoring transportation equipment | |
| CN112734147A (en) | Method and device for equipment evaluation management | |
| CN107682432B (en) | Spark-based data processing system and method | |
| CN107678839B (en) | Priority-based client follow-up method, system and readable storage medium | |
| CN115827646A (en) | Index configuration method and device and electronic equipment | |
| CN113722007B (en) | Configuration method, device and system of VPN branch equipment | |
| CN114612212A (en) | Business processing method, device and system based on risk control | |
| CN114924937A (en) | Batch task processing method and device, electronic equipment and computer readable medium | |
| US11283859B1 (en) | System, method, and computer program for performing distributed outsourced computing | |
| CN114257521A (en) | Flow prediction method, device, electronic equipment and storage medium | |
| CN111767351B (en) | Method and device for determining parking spot of transfer robot | |
| CN110187987B (en) | Method and apparatus for processing requests | |
| CN113760176A (en) | Data storage method and device | |
| CN111768065A (en) | Method and device for distributing goods sorting tasks | |
| CN109978644B (en) | Information processing method, device and system | |
| CN113535768A (en) | Production monitoring method and device | |
| CN113434754A (en) | Method and device for determining recommended API (application program interface) service, electronic equipment and storage medium | |
| CN113129473B (en) | Data acquisition method, device and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |