Warehousing work order task whole-process intelligent supervision method and system

Abstract

The invention relates to the technical field of warehouse supervision, and particularly discloses a warehouse work order task whole-process intelligent supervision method and system, and the method comprises the following steps: obtaining work order tasks and task information in a work period of the warehouse work order tasks, and calculating the execution stability rate of the work order tasks; a period execution stable signal or a period optimization recheck signal is obtained; calculating a path deviation rate and comparing the path deviation rate with a path deviation rate threshold value; obtaining a work order task path normal signal or a work order task path abnormal signal; calculating a task processing time deviation rate and comparing the task processing time deviation rate with a task processing time deviation rate threshold value to obtain a work order task execution abnormal signal or a work order task double-monitoring signal; calculating an execution deviation performance value of the work order task and comparing the execution deviation performance value with an execution deviation performance qualified value; the execution verification qualification signal or the work order task execution abnormal signal is obtained and generated, the accuracy and timeliness of warehousing work are improved, and an executor or execution equipment in the warehousing work order task execution process is effectively supervised.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse supervision, and in particular to a method and system for intelligently supervising the entire process of warehouse work order tasks. Background Art

[0002] Warehousing is an important part of modern logistics, plays a vital role in the logistics system, and is the focus of manufacturers' research and planning. Efficient and reasonable warehousing can help manufacturers speed up the flow of materials, reduce costs, ensure the smooth progress of production, and achieve effective control and management of resources. The development of warehousing has gone through different historical periods and stages, from primitive manual warehousing to current intelligent warehousing. Through the support of various high-tech technologies for warehousing, the efficiency of warehousing has been greatly improved.

[0003] In the process of warehouse management, the efficiency of warehouse work order execution is extremely important. Efficient work order task execution indirectly creates profits for the company. Therefore, supervision during the execution of warehouse work order tasks is also an important link. However, the existing supervision is through manual supervision or video monitoring, which cannot timely and accurately discover problems in the execution of warehouse work orders, and cannot provide a strong and effective basis for the supervision of warehouse work order tasks. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for intelligently supervising the entire process of warehouse work order tasks to solve the problems in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for intelligently supervising the entire process of a warehouse work order task comprises the following steps:

[0007] Obtain the work order tasks within the warehouse work order task work cycle T and mark them as i, where i is 1, 2, 3...; obtain the task information in the work order tasks and mark them as n, where n is 1, 2, 3...; obtain the task basic data of each task information in the work order tasks and the execution information data of the work order task i; calculate the execution stability rate ZTon of the work order tasks within the warehouse work order task work cycle T;

[0008] Compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy; obtain a cycle execution stability signal or a cycle optimization review signal;

[0009] Based on the cycle optimization review signal, obtain the basic data and execution information data of the work order task under the work order task completion signal to be optimized, and calculate the path deviation rate LP i; and compare it with the path deviation rate threshold LPy; obtain a normal signal of the work order task path or an abnormal signal of the work order task path;

[0010] Based on the normal signal of the work order task path, obtain the task information under the normal signal of the work order task path; calculate and obtain the task processing time deviation rate TP i ; and compare it with the task processing time deviation rate threshold TPy to obtain the work order task execution abnormality signal or the work order task dual monitoring signal;

[0011] Based on the dual monitoring signals of the work order task, the path deviation rate LP of the work order task under the dual monitoring signals of the work order task is obtained i and task processing time deviation rate TP i ;

[0012] By SZXP i =β×LP i +γ×TP i Calculate the execution deviation performance value SZXP of the work order task i ; Where β is the path planning deviation performance coefficient, and γ is the task execution deviation performance coefficient; where β+γ=1, and both β and γ are greater than 0;

[0013] Then, the deviation performance value SZXP will be executed i Compare with the execution deviation performance qualified value SXZPy; obtain the generated execution verification qualified signal or the work order task execution abnormality signal.

[0014] As a further solution of the present invention: the task basic data includes the task unit completion time t (i，n) 、Mission target coordinate position D(x, y) (i，n) and task processing working time value GT (i，n) ;

[0015] The execution information data includes the total execution time of the work order ZS i , Work order execution travel time value ZX i And the total value of the work order execution trip LS i ;

[0016] The calculation method of the execution stability rate ZT of the work order task is:

[0017] Traverse and calculate the work order task work cycle T of the warehouse work order task work time execution efficiency ratio SQB i ;

[0018] The efficiency ratio of the work order task in the warehouse work order task cycle T is SQB i Compare with the working time execution efficiency ratio threshold SQY in turn;

[0019] If the working time execution efficiency is higher than SQB i If it is less than or equal to the working time execution efficiency ratio threshold SQY, a normal signal of work order task completion is obtained;

[0020] If the working time execution efficiency is higher than SQB i If it is greater than the working time execution efficiency ratio threshold SQY, a signal for the work order task completion to be optimized is obtained;

[0021] Get the number of normal completion signals of work order tasks within the warehouse work order task working cycle T, and record it as kon;

[0022] pass Calculate and obtain the execution stability rate ZT of the work order tasks within the warehouse work order task working cycle T.

[0023] As a further solution of the present invention: the work order task has a working time execution efficiency ratio SQB i ; is calculated as:

[0024] By MZ i =∑t (i，n) Calculate the total time MZ of the task target for work order task i i ; That is, calculate the maximum time value that each execution information in the work order task takes to complete individually;

[0025] Based on the total time consumed by the task target MZ i and the total work order execution time ZS i ,pass Calculate the work time execution efficiency ratio SQB of work order task i i .

[0026] As a further solution of the present invention: comparing the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy;

[0027] If the execution stability rate ZTon is greater than or equal to the execution stability rate threshold ZTy; a periodic execution stability signal is generated;

[0028] If the execution stability rate ZTon is less than the execution stability rate threshold ZTy, a cycle optimization review signal is generated.

[0029] As a further solution of the present invention: the path deviation rate LP i The calculation method is:

[0030] Obtain the basic task data including the task target coordinate position D (x, y) (i，n) ; At the same time, obtain the execution information data including the total value of the work order execution trip LS i ;

[0031] Get the starting coordinate point S (x, y) of the work order task i (i，0) ; Traverse and calculate to obtain the optimal total travel value of the work order task under the signal to be optimized and mark it as LY i ;

[0032] Among them, the optimal total trip value LY i Use the exhaustive algorithm to calculate the starting coordinate point S (x, y) of the work order task i (i，0) Passing all task target coordinate positions D(x, y) (i，n) The total path value set {LZJ i}, at this time, LY i =minLZJ i ;

[0033] pass Calculate the path deviation rate LP of the work order task under the work order task completion signal to be optimized i .

[0034] As a further solution of the present invention: the path deviation rate LP of the work order task under the work order task completion signal to be optimized is calculated as follows: i Compare with the path deviation rate threshold LPy;

[0035] If the path deviation rate LP i If the path deviation rate is less than or equal to the path deviation rate threshold LPy, the work order task completion signal to be optimized is updated to a work order task path normal signal;

[0036] If the path deviation rate LP i If the value is greater than the path deviation rate threshold LPy, the work order task completion signal to be optimized is updated to a work order task path abnormality signal.

[0037] As a further solution of the present invention: the task processing time deviation rate TP i ; is calculated as:

[0038] Get the task information of work order task i under the abnormal signal of work order task path; including the task processing working time value GT in the task (i，n) ; by RZT i =∑GT (i，n) Calculate the total processing time RZT of work order task i i ;

[0039] The total processing time value RZT of task i based on the work order i ; Get the total value of the work order execution time ZS in the execution information data i and the work order execution travel time value ZX i ;

[0040] pass Calculate the task processing time deviation rate TP i .

[0041] As a further solution of the present invention: the task processing time deviation rate TP i Compare with the task processing time deviation rate threshold TPy;

[0042] If the task processing time deviation rate TP i Greater than the task processing time deviation rate threshold TPy; the work order task path normal signal is updated to the work order task execution abnormal signal;

[0043] If the task processing time deviation rate TP i Less than or equal to the task processing time deviation rate threshold TPy; the work order task path normal signal is updated to the work order task dual monitoring signal.

[0044] As a further solution of the present invention: the execution deviation performance value SZXP i Compare with the qualified value SXZPy of execution deviation performance;

[0045] If the execution deviation performance value SZXP i If the execution deviation is less than or equal to the qualified value SXZPy, a qualified execution verification signal is generated;

[0046] If the execution deviation performance value SZXP i If the execution deviation is greater than the qualified value SXZPy, a work order task execution abnormality signal is generated.

[0047] As a further solution of the present invention: a full-process intelligent supervision system for warehouse work order tasks, comprising:

[0048] Data acquisition module: used to obtain the work order tasks within the warehouse work order task work cycle T and mark them as i, where i is 1, 2, 3...; obtain the task information in the work order task and mark them as n, where n is 1, 2, 3...; obtain the task basic data of each task information in the work order task and the execution information data of the work order task i; calculate the execution stability rate ZTon of the work order tasks within the warehouse work order task work cycle T;

[0049] Supervision and judgment module: used to compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy; obtain the cycle execution stability signal or cycle optimization review signal;

[0050] Single item verification module: Based on the periodic optimization review signal, obtain the basic data and execution information data of the work order task under the work order task completion signal to be optimized, and calculate the path deviation rate LP i; and compare it with the path deviation rate threshold LPy; obtain a normal signal of the work order task path or an abnormal signal of the work order task path;

[0051] Based on the normal signal of the work order task path, obtain the task information under the normal signal of the work order task path; calculate and obtain the task processing time deviation rate TP i ; and compare it with the task processing time deviation rate threshold TPy to obtain the work order task execution abnormality signal or the work order task dual monitoring signal;

[0052] Double-item verification module: Based on the dual monitoring signals of the work order task, obtain the path deviation rate LP of the work order task under the dual monitoring signals of the work order task i and task processing time deviation rate TP i ;

[0053] By SZXP i =β×LP i +γ×TP i Calculate the execution deviation performance value SZXP of the work order task i ; Where β is the path planning deviation performance coefficient, and γ is the task execution deviation performance coefficient; where β+γ=1, and both β and γ are greater than 0;

[0054] Then, the deviation performance value SZXP will be executed i Compare with the execution deviation performance qualified value SXZPy; obtain the generated execution verification qualified signal or the work order task execution abnormality signal.

[0055] Beneficial effects of the present invention:

[0056] In the present invention, by calculating the execution information and task information of the work order tasks within the work cycle T of the warehouse work order tasks, it is determined whether there are any abnormalities in the warehouse work order tasks within the work cycle. If unstable execution occurs during the execution of the warehouse work order tasks, it indicates that abnormalities have occurred in the execution of some work order tasks. At this time, by calculating the execution path and execution time of the work order tasks, it is further determined whether there are any abnormalities in the execution of the work order tasks, and supervision reminders are given based on the abnormal situations to ensure that the execution efficiency of the work order tasks meets the requirements, improve the accuracy and timeliness of warehousing work, effectively supervise the executors or execution equipment during the execution of the warehouse work order tasks, and provide adjustment basis;

[0057] At the same time, if the calculation of the path deviation rate, task processing time deviation rate and execution deviation performance value is directly performed, a single task work order can be directly supervised and problems arising during the execution of the task work order can be quickly discovered. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present invention will be further described below in conjunction with the accompanying drawings.

[0059] Figure 1 It is a schematic flow chart of the method of the present invention;

[0060] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] Embodiment 1

[0063] See also Figure 1 As shown, the present invention is a method for intelligently supervising the entire process of a warehouse work order task, comprising the following steps:

[0064] Step 01: Obtain the work order tasks within the warehouse work order task work cycle T, and mark the work order tasks as i, where i is 1, 2, 3, etc.;

[0065] Get the task information in the work order task, and mark the task information as n in sequence, where n is 1, 2, 3, etc.; get the task basic data of each task information in the work order task, where the task basic data includes the task unit completion time t (i，n) 、Mission target coordinate position D(x, y) (i，n) and task processing working time value GT (i，n) ;

[0066] It should be noted that the task unit completion time t (i，n) Refers to the time value of a single execution of each task information in the work order task; the task processing working time value GT (i，n) It refers to the time value of executing work during a single execution of each task information, such as picking, stacking, and stacking, that is, the execution time of warehousing work excluding the path walking time;

[0067] Get the execution information data of work order task i, which includes the total execution time ZS of the work order i , Work order execution travel time value ZX i And the total value of the work order execution trip LS i ;

[0068] It should be noted that the total execution time of the work order is ZS i Refers to the total time it takes to complete the work order task; the work order execution travel time value ZXi Refers to the total execution time of all execution information work in the work order task; the total value of the work order execution trip LS i Refers to the total length of the path walked by the executor or execution equipment after all execution information in the work order task is completed;

[0069] Step 02: Based on the basic task data and execution information data of work order task i, calculate the execution stability rate ZT of the work order task within the warehouse work order task working cycle T; specifically:

[0070] 021: Traverse and calculate the work time execution efficiency ratio SQB of the work order tasks within the work cycle T of the warehouse work order tasks i ;include:

[0071] 0211: Through MZ i =∑t (i，n) Calculate the total time MZ of the task target for work order task i i ; That is, calculate the maximum time value that each execution information in the work order task takes to complete individually;

[0072] 0212: Based on the total time consumed by the task target MZ i and the total work order execution time ZS i ,pass Calculate the work time execution efficiency ratio SQB of work order task i i ; By calculating the formula execution efficiency ratio of the work order task, it can be obtained that the total work order execution time spent on each work order task after optimization accounts for the total time spent on the task target. The smaller the ratio, the better the optimization of the work order task;

[0073] 022: Compare the work time execution efficiency of the work order task within the warehouse work order task work cycle T to SQB i Compare with the working time execution efficiency ratio threshold SQY in turn;

[0074] If the working time execution efficiency is higher than SQB i If the work-hour execution efficiency ratio is less than or equal to the threshold value SQY, a normal signal of the work order task completion is obtained, indicating that the timeliness of the work order task is good;

[0075] If the working time execution efficiency is higher than SQB i If it is greater than the working time execution efficiency ratio threshold SQY, a signal for the work order task completion to be optimized is obtained, indicating that the completion efficiency of the work order task is poor;

[0076] 023: Get the number of normal completion signals of work order tasks within the warehouse work order task working cycle T, and record it as kon;

[0077] pass Calculate and obtain the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T;

[0078] Step 03: Compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy;

[0079] If the execution stability rate ZTon is greater than or equal to the execution stability rate threshold ZTy, a periodic execution stability signal is generated, which means that within the working cycle T of the warehouse work order task, the execution stability rate of the work order task is high, and the proportion of task information in the work order task that is optimized during the execution process meets the requirements of execution stability;

[0080] If the execution stability rate ZTon is less than the execution stability rate threshold ZTy, a cycle optimization review signal is generated; at this time, it means that the execution stability rate of the warehouse work order task is low within the working cycle T, and the execution time of more work order tasks does not meet the optimization standard;

[0081] Therefore, it is necessary to review the execution process of the work order tasks under the work order task completion signal to be optimized within the work cycle to find out where the time-consuming problem in the execution process of the work order task occurs;

[0082] Step 04: Based on the cycle optimization review signal, obtain the basic data and execution information data of the work order task under the work order task completion signal to be optimized; calculate the path deviation rate LP i ;

[0083] The following steps are involved:

[0084] 041: Get the basic data of the task including the coordinate position of the task target D (x, y) (i，n) ; At the same time, obtain the execution information data including the total value of the work order execution trip LS i ;

[0085] 042: Get the starting coordinate point S (x, y) of work order task i (i，0) ; Traverse and calculate to obtain the optimal total travel value of the work order task under the signal to be optimized and mark it as LY i ;

[0086] The task starting coordinate point refers to the location in the warehouse where the executor or execution equipment is located when each task work order starts to be executed;

[0087] Among them, the optimal total trip value LY i Use the exhaustive algorithm to calculate the starting coordinate point S (x, y) of the work order task i (i，0) Passing all task target coordinate positions D(x, y) (i，n) The total path value set {LZJ i}, at this time, LYi =minLZJ i ;

[0088] The total path value set of the task starting coordinate point passing through all task target coordinate positions refers to: the set of all the total path values ​​that the executor or execution device walks from the task starting coordinate point through the task target coordinate positions of all work order tasks to complete the task execution;

[0089] 043: Pass Calculate the path deviation rate LP of the work order task under the work order task completion signal to be optimized i ;

[0090] Step 05: Complete the work order task to be optimized under the signal path deviation rate LP i Compare with the path deviation rate threshold LPy;

[0091] If the path deviation rate LP i If the path deviation rate is less than or equal to the path deviation rate threshold LPy, the work order task completion signal to be optimized is updated to a work order task path normal signal;

[0092] If the path deviation rate LP i If the value is greater than the path deviation rate threshold LPy, the work order task completion signal to be optimized is updated to a work order task path abnormality signal;

[0093] Perform path calculation on the work order task under the cycle optimization review signal, and calculate the path deviation rate of the work order task; then compare the path deviation rate of the work order task with the path deviation rate threshold to further determine whether the work order task deviates from the path optimization when the work time execution efficiency ratio does not meet the standard; at the same time, it can be determined whether the work time execution efficiency ratio does not meet the requirement due to path planning and execution when there is less execution information in the work order task; for example, there is one execution information after the execution information in the work order task, and there is only one path at this time. At this time, the work time execution efficiency ratio may be greater than the work time execution efficiency ratio threshold. Therefore, the calculation of the path deviation rate of the work order task can determine whether the path planning in the work order task is abnormal. If the work order task path is abnormal, remind the executor to execute according to the planned path when walking on the path, or remind the background operator of the execution device to analyze the execution path of the work order task to determine whether waiting or other interference occurs during the process;

[0094] Step 06: Based on the normal signal of the work order task path, obtain the task information under the normal signal of the work order task path; calculate and obtain the task processing time deviation rate TP i ;

[0095] include:

[0096] 061: Get the task information of work order task i under the abnormal signal of work order task path; including the task processing working time value GT in the task (i，n) ; by RZT i =∑GT (i，n) Calculate the total processing time RZT of work order task i i ;

[0097] 062: Total time consumed for task processing based on work order task i RZT i ; Get the total value of the work order execution time ZS in the execution information data i and the work order execution travel time value ZX i ;

[0098] pass Calculate the task processing time deviation rate TP i ;

[0099] When the path deviation rate in the work order task is in a qualified state, in order to further determine the reason why the work order task completion signal to be optimized appears during the work process, at this time, the execution task processing time in the work order task is further analyzed and calculated, and it is determined whether the work order task path is in a normal signal state because the work order task is abnormal during execution, such as the executor or the execution equipment is unstable during work;

[0100] Step 07: Set the task processing time deviation rate TP of the work order task under the normal signal of the work order task path i Compare with the task processing time deviation rate threshold TPy;

[0101] If the task processing time deviation rate TP i is greater than the task processing time deviation rate threshold TPy; the work order task path normal signal is updated to the work order task execution abnormal signal; at this time, it means that during the work order task execution, an execution abnormality occurs, such as the executor slacking off or missing work, or the execution equipment is powered off or waiting for a long time, then the execution process can be supervised;

[0102] If the task processing time deviation rate TP i Less than or equal to the task processing time deviation rate threshold TPy; the work order task path normal signal is updated to the work order task dual monitoring signal; at this time, it means that the path deviation rate and the task processing time deviation rate during the task execution process are both within the normal range. Since the work time execution efficiency of the work order task is relatively large, the execution path and task execution time should be considered at the same time to determine whether the execution process of the work order task is normal;

[0103] Step 08: Based on the dual monitoring signal of the work order task, obtain the path deviation rate LP of the work order task under the dual monitoring signal of the work order task i and task processing time deviation rate TP i ;

[0104] By SZXP i =β×LP i +γ×TP i Calculate the execution deviation performance value SZXP of the work order task i ; Where β is the path planning deviation performance coefficient, and γ is the task execution deviation performance coefficient; where β+γ=1, and both β and γ are greater than 0;

[0105] Then, the deviation performance value SZXP will be executed i Compare with the qualified value SXZPy of execution deviation performance;

[0106] If the execution deviation performance value SZXP i If the value is less than or equal to the qualified execution deviation value SXZPy, a qualified execution verification signal is generated, indicating that the task of the work order is executed normally. At this time, the work order task can be recorded as a normal completion signal of the work order task; then execute 023;

[0107] If the execution deviation performance value SZXP i If the execution deviation is greater than the qualified value SXZPy, a work order task execution abnormality signal is generated; at this time, the execution path and execution process of the work order task are reviewed to determine whether any abnormal conditions occur during the execution process.

[0108] By calculating the execution information and task information of the work order tasks within the work cycle T of the warehouse work order tasks, it is determined whether there are any abnormalities in the warehouse work order tasks within the work cycle. If the execution is unstable during the execution of the warehouse work order tasks, it indicates that the execution of some work order tasks is abnormal. At this time, by calculating the execution path and execution time of the work order tasks, it is further determined whether there are any abnormalities in the execution of the work order tasks, and supervision reminders are given based on the abnormal situations to ensure that the execution efficiency of the work order tasks meets the requirements, improve the accuracy and timeliness of warehousing work, effectively supervise the executors or execution equipment during the execution of the warehouse work order tasks, and provide adjustment basis;

[0109] At the same time, during the working process of the above technical solution, if the path deviation rate, task processing time deviation rate and execution deviation performance value are directly calculated, a single task work order can be directly supervised to quickly discover problems that arise during the execution of the task work order.

[0110] Embodiment 2

[0111] Reference Figure 2 As shown, a full-process intelligent supervision system for warehouse work order tasks includes:

[0112] Data acquisition module: used to obtain the work order tasks within the warehouse work order task work cycle T and mark them as i, where i is 1, 2, 3...; obtain the task information in the work order task and mark them as n, where n is 1, 2, 3...; obtain the task basic data of each task information in the work order task and the execution information data of the work order task i; calculate the execution stability rate ZTon of the work order tasks within the warehouse work order task work cycle T;

[0113] Supervision and judgment module: used to compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy; obtain the cycle execution stability signal or cycle optimization review signal;

[0114] Single item verification module: Based on the periodic optimization review signal, obtain the basic data and execution information data of the work order task under the work order task completion signal to be optimized, and calculate the path deviation rate LP i ; and compare it with the path deviation rate threshold LPy; obtain a normal signal of the work order task path or an abnormal signal of the work order task path;

[0115] Based on the normal signal of the work order task path, obtain the task information under the normal signal of the work order task path; calculate and obtain the task processing time deviation rate TP i ; and compare it with the task processing time deviation rate threshold TPy to obtain the work order task execution abnormality signal or the work order task dual monitoring signal;

[0116] Double-item verification module: Based on the dual monitoring signals of the work order task, obtain the path deviation rate LP of the work order task under the dual monitoring signals of the work order task i and task processing time deviation rate TP i ;

[0117] By SZXP i =β×LP i +γ×TP i Calculate the execution deviation performance value SZXP of the work order task i ; Where β is the path planning deviation performance coefficient, and γ is the task execution deviation performance coefficient; where β+γ=1, and both β and γ are greater than 0;

[0118] Then, the deviation performance value SZXP will be executed i Compare with the execution deviation performance qualified value SXZPy; obtain the generated execution verification qualified signal or the work order task execution abnormality signal.

[0119] By calculating the execution path and execution time of the work order task, we can further determine whether there are any abnormalities in the execution of the work order task, and provide supervision reminders based on the abnormal situation to ensure that the execution efficiency of the work order task meets the requirements, improve the accuracy and timeliness of warehousing work, effectively supervise the executors or execution equipment in the execution process of warehousing work order tasks, and provide adjustment basis.

[0120] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for intelligent supervision of the entire process of warehouse work order tasks, characterized in that: The following steps are involved: Obtain the work order tasks within the warehouse work order task work cycle T and mark them as i, where i is 1, 2, 3...; obtain the task information in the work order tasks and mark them as n, where n is 1, 2, 3...; obtain the task basic data of each task information in the work order tasks and the execution information data of the work order task i; calculate the execution stability rate ZTon of the work order tasks within the warehouse work order task work cycle T; Compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy; obtain a cycle execution stability signal or a cycle optimization review signal; Based on the cycle optimization review signal, obtain the basic data and execution information data of the work order task under the work order task completion signal to be optimized, and calculate the path deviation rate LP i ; and compare it with the path deviation rate threshold LPy; obtain a normal signal of the work order task path or an abnormal signal of the work order task path; Based on the normal signal of the work order task path, obtain the task information under the normal signal of the work order task path; calculate and obtain the task processing time deviation rate TP i ; and compare it with the task processing time deviation rate threshold TPy to obtain the work order task execution abnormality signal or the work order task dual monitoring signal; Based on the dual monitoring signals of the work order task, the path deviation rate LP of the work order task under the dual monitoring signals of the work order task is obtained i and task processing time deviation rate TP i ; By SZXP i =β×LP i +γ×TP i Calculate the execution deviation performance value SZXP of the work order task i ; Where β is the path planning deviation performance coefficient, and γ is the task execution deviation performance coefficient; where β+γ=1, and both β and γ are greater than 0; Then, the deviation performance value SZXP will be executed i Compare with the execution deviation performance qualified value SXZPy; obtain the generated execution verification qualified signal or the work order task execution abnormality signal.

2. According to claim 1, a method for intelligent supervision of the entire process of warehouse work order tasks is characterized in that: The task basic data includes the task unit completion time t (i，n) 、Mission target coordinate position D(x, y) (i，n) and task processing working time value GT (i，n) ; The execution information data includes the total execution time of the work order ZS i , Work order execution travel time value ZX i And the total value of the work order execution trip LS i ; The calculation method of the execution stability rate ZT of the work order task is: Traverse and calculate the work order task work cycle T of the warehouse work order task work time execution efficiency ratio SQB i ; The efficiency ratio of the work order task in the warehouse work order task cycle T is SQB i Compare with the working time execution efficiency ratio threshold SQY in turn; If the working time execution efficiency is higher than SQB i If it is less than or equal to the working time execution efficiency ratio threshold SQY, a normal signal of work order task completion is obtained; If the working time execution efficiency is higher than SQB i If it is greater than the working time execution efficiency ratio threshold SQY, a signal for the work order task completion to be optimized is obtained; Get the number of normal completion signals of work order tasks within the warehouse work order task working cycle T, and record it as kon; pass Calculate and obtain the execution stability rate ZT of the work order tasks within the warehouse work order task working cycle T.

3. According to claim 1, a method for intelligent supervision of the entire process of warehouse work order tasks is characterized in that: The work order task's work time execution efficiency is SQB i ; is calculated as: By MZ i =Σt (i，n) Calculate the total time MZ of the task target for work order task i i ; That is, calculate the maximum time value that each execution information in the work order task takes to complete individually; Based on the total time consumed by the task target MZ i and the total work order execution time ZS i ,pass Calculate the work time execution efficiency ratio SQB of work order task i i .

4. According to claim 1, a method for intelligent supervision of the entire process of warehouse work order tasks is characterized in that: Compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy; If the execution stability rate ZTon is greater than or equal to the execution stability rate threshold ZTy; a periodic execution stability signal is generated; If the execution stability rate ZTon is less than the execution stability rate threshold ZTy, a cycle optimization review signal is generated.

5. According to claim 1, a method for intelligent supervision of the entire process of warehouse work order tasks is characterized in that: The path deviation rate LP i The calculation method is: Obtain the basic task data including the task target coordinate position D (x, y) (i，n) ; At the same time, obtain the execution information data including the total value of the work order execution trip LS i ; Get the starting coordinate point S (x, y) of the work order task i (i，0) ; Traverse and calculate to obtain the optimal total travel value of the work order task under the signal to be optimized and mark it as LY i ; Among them, the optimal total trip value LY i Use the exhaustive algorithm to calculate the starting coordinate point S (x, y) of the work order task i (i，0) Passing all task target coordinate positions D(x, y) (i，n) The total path value set {LZJ i }, at this time, LY i =min{LZJ i }; pass Calculate the path deviation rate LP of the work order task under the work order task completion signal to be optimized i .

6. A method for intelligently supervising the entire process of warehouse work order tasks according to claim 5, characterized in that: The path deviation rate LP of the work order task under the work order task completion signal to be optimized i Compare with the path deviation rate threshold LPy; If the path deviation rate LP i If the path deviation rate is less than or equal to the path deviation rate threshold LPy, the work order task completion signal to be optimized is updated to a work order task path normal signal; If the path deviation rate LP i If the value is greater than the path deviation rate threshold LPy, the work order task completion signal to be optimized is updated to a work order task path abnormality signal.

7. According to claim 1, a method for intelligent supervision of the entire process of warehouse work order tasks is characterized in that: The task processing time deviation rate TP i ; is calculated as: Get the task information of work order task i under the abnormal signal of work order task path; including the task processing working time value GT in the task (i，n) ; by RZT i =ΣGT (i，n) Calculate the total processing time RZT of work order task i i ; The total processing time value RZT of task i based on the work order i ; Get the total value of the work order execution time ZS in the execution information data i and the work order execution travel time value ZX i ; pass Calculate the task processing time deviation rate TP i .

8. A method for intelligently supervising the entire process of warehouse work order tasks according to claim 7, characterized in that: Task processing time deviation rate TP i Compare with the task processing time deviation rate threshold TPy; If the task processing time deviation rate TP i Greater than the task processing time deviation rate threshold TPy; The normal signal of the work order task path is updated to the abnormal signal of the work order task execution; If the task processing time deviation rate TP i Less than or equal to the task processing time deviation rate threshold TPy; The normal signal of the work order task path is updated to the work order task dual monitoring signal.

9. A method for intelligently supervising the entire process of warehouse work order tasks according to claim 1, characterized in that: The deviation performance value SZXP will be executed i Compare with the qualified value SXZPy of execution deviation performance; If the execution deviation performance value SZXP i If the execution deviation is less than or equal to the qualified value SXZPy, a qualified execution verification signal is generated; If the execution deviation performance value SZXP i If the execution deviation is greater than the qualified value SXZPy, a work order task execution abnormality signal is generated.

10. A full-process intelligent supervision system for warehouse work order tasks, characterized in that: The system is used to perform the supervision method as described in any one of claims 1 to 9, comprising: Data acquisition module: used to obtain the work order tasks within the warehouse work order task work cycle T and mark them as i, where i is 1, 2, 3...; obtain the task information in the work order task and mark them as n, where n is 1, 2, 3...; obtain the task basic data of each task information in the work order task and the execution information data of the work order task i; calculate the execution stability rate ZTon of the work order tasks within the warehouse work order task work cycle T; Supervision and judgment module: used to compare the execution stability rate ZTon of the work order task within the warehouse work order task working cycle T with the execution stability rate threshold ZTy; obtain the cycle execution stability signal or cycle optimization review signal; Single item verification module: Based on the periodic optimization review signal, obtain the basic data and execution information data of the work order task under the work order task completion signal to be optimized, and calculate the path deviation rate LP i ; and compare it with the path deviation rate threshold LPy; obtain a normal signal of the work order task path or an abnormal signal of the work order task path; Based on the normal signal of the work order task path, obtain the task information under the normal signal of the work order task path; calculate and obtain the task processing time deviation rate TP i ; and compare it with the task processing time deviation rate threshold TPy to obtain the work order task execution abnormality signal or the work order task dual monitoring signal; Double-item verification module: Based on the dual monitoring signals of the work order task, obtain the path deviation rate LP of the work order task under the dual monitoring signals of the work order task i and task processing time deviation rate TP i ; By SZXP i =β×LP i +γ×TP i Calculate the execution deviation performance value SZXP of the work order task i ; Where β is the path planning deviation performance coefficient, and γ is the task execution deviation performance coefficient; where β+γ=1, and both β and γ are greater than 0; Then, the deviation performance value SZXP will be executed i Compare with the execution deviation performance qualified value SXZPy; obtain the generated execution verification qualified signal or the work order task execution abnormality signal.

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