CN113379314B - Intelligent annual production plan supervision method based on reasoning algorithm - Google Patents
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Abstract
The invention discloses an intelligent supervision method for annual production plans based on an inference algorithm, which comprises the following steps: by extracting the arrangement information of the test plan and the work ticket from the 6+1 production management system, the annual production plan is supervised and supervised, and the intelligent analysis and accurate matching of the arrangement data of the production plan are supported by using the cross exploration, dimension integration and splitting method and combining an intelligent reasoning algorithm. The invention monitors the consistency of the system pre-test plan by associating the production plan work order, the equipment test period time and the like; according to the equipment test period, monitoring whether the compiled test plan exceeds the limit and the number of the exceeding limit; and according to the equipment ledgers and the equipment test period, supervising the compiled test plan and whether the test object is missed.
Description
Technical Field
The invention relates to the technical field of intelligent supervision of annual production plans, in particular to an intelligent supervision method of annual production plans based on an inference algorithm.
Background
The preventive test of the power equipment is an important link in the operation and maintenance work of the power equipment, and is one of effective means for ensuring the safe operation of the power equipment. For many years, high-voltage power equipment of a power enterprise is basically tested according to the requirements of a standard DL/T596-1996 electric equipment preventive test procedure, and the current south-oriented network has issued a latest electric equipment overhaul test procedure CSG-2017006, so that the operation condition of the electric equipment can be accurately diagnosed, and the method plays an important role in timely finding and diagnosing equipment risks.
The annual production planning work order, work ticket and equipment test cycle time of the existing power grid 6+1 production management system are poor in consistency, and missing information is easy to cause, so that the production plan cannot be accurately completed, and the efficiency is low.
Disclosure of Invention
The invention aims to solve the technical problems that: an intelligent annual production plan supervision method based on an inference algorithm is provided to solve the technical problems existing in the prior art.
The technical scheme adopted by the invention is as follows: an intelligent supervision method for annual production plans based on an inference algorithm comprises the following steps: the annual production plan is supervised and supervised by extracting the arrangement information of the test plan and the work ticket from the 6+1 production management system, and the intelligent analysis and accurate matching are carried out on the arrangement data of the production plan by combining an intelligent reasoning algorithm through the cross exploration, dimension integration and splitting method, so that the plan supervision is realized.
Planning supervision includes three aspects: 1) The supervision system pre-tests the plan consistency by associating the production plan work order, the work order and the equipment test cycle time; 2) According to the equipment test period, monitoring whether the compiled test plan exceeds the limit and the number of the exceeding limit; 3) And according to the equipment ledgers and the equipment test period, supervising the compiled test plan and whether the test object is missed.
The annual production plan intelligent supervision method based on the reasoning algorithm comprises the following specific steps:
step 1: acquiring preventive test work plans and work ticket data from a production system: carding data (pre-test plan of high-voltage, chemical and electrical testing profession), work ticket information and defect data related to a main equipment preventive test plan, and acquiring required data from a production system according to a carding result;
step 2: test plan management: distinguishing equipment information from different professions, extracting the equipment information from equipment operation and maintenance periods of a maintenance and modification module in a production system, mainly checking whether equipment is subjected to a system production plan or not, and checking whether a station account is complete or not in the reverse;
step 3: planning execution management: and (5) associating a power failure application form: for a production plan requiring power failure, associating a power failure application form, and checking details of the power failure application form; work ticket and system pre-test plan inconsistency supervision: the production plan is used for removing the associated work ticket, such as the production plan of a period unit (1 month), and when the current day is cut off, a corresponding work ticket should be provided in the system every month; through statistical analysis, if the work ticket is found to be absent, the work ticket is considered to be inconsistent with the system pre-test plan; test report and system pre-test plan inconsistency supervision: the production plan is used for removing the associated test report, such as the production plan of a period unit (1 month), the current day is cut off, and the test report is uploaded from the last month (5 working days are required to be uploaded after the test is completed, and the actual situation can be considered to be relaxed to 1 month), so that a corresponding work ticket is required to be provided in the system each month; through statistical analysis, if the work ticket is found to be absent, the work ticket is considered to be inconsistent with the system pre-test plan; planning out of date: in different dimensions (ground city bureau, transformer substation), comparing the planned starting time and the planned ending time of the production plan with the actual starting time and the actual ending time of the plan to judge whether the time exceeds the time and the number of the time exceeds the time;
step 4: and (5) reminding the equipment of exceeding the period: the equipment is out of date: in different dimensions (ground city bureau, transformer substation), according to the equipment test period, reminding the equipment of the over-period, for example, the last test day of a certain equipment is 2019-10-14, the period is 1 year, if the test is not started by 2020-10-14 days, reminding the equipment of the over-period until the equipment is tested. Meanwhile, early warning grades are classified according to the conditions of the equipment (equipment importance, equipment health, risk assessment algorithm and the like); major/emergency defect display: displaying the number of major emergency defects of the equipment in the dimension of the equipment, and individually checking the details of each major/emergency defect; the latest patrol plan shows: the latest patrol plan of the equipment can be displayed; developing hand filling functions: the reasons for the over-period of the equipment, the management and control measures and the next power failure planning time are manually filled by the clients.
The cross exploration method comprises the following steps: .
The intelligent reasoning algorithm is as follows: .
The invention has the beneficial effects that: compared with the prior art, the invention extracts the arrangement information of the test plan and the work ticket from the 6+1 production management system, supervises and supervises the annual production plan, intelligently supervises the annual production plan based on an inference algorithm, and intelligently analyzes and accurately matches the arrangement data of the production plan by combining the intelligent inference algorithm by using a cross exploration, dimension integration and splitting method, thereby achieving the quality improvement of the following three plan supervision:
(1) The supervision system pre-tests the plan consistency by associating production plan work orders, work tickets, equipment test cycle time and the like;
(2) According to the equipment test period, monitoring whether the compiled test plan exceeds the limit and the number of the exceeding limit;
(3) And according to the equipment ledgers and the equipment test period, supervising the compiled test plan and whether the test object is missed.
Drawings
Fig. 1 is a flow chart of the present invention.
Detailed Description
The invention will be further described with reference to specific examples.
Example 1: an intelligent supervision method for annual production plans based on an inference algorithm comprises the following steps: the annual production plan is supervised and supervised by extracting the arrangement information of the test plan and the work ticket from the 6+1 production management system, and the intelligent analysis and accurate matching are carried out on the arrangement data of the production plan by combining an intelligent reasoning algorithm through the cross exploration, dimension integration and splitting method, so that the plan supervision is realized.
Planning supervision includes three aspects: 1) The supervision system pre-tests the plan consistency by associating the production plan work order, the work order and the equipment test cycle time; 2) According to the equipment test period, monitoring whether the compiled test plan exceeds the limit and the number of the exceeding limit; 3) And according to the equipment ledgers and the equipment test period, supervising the compiled test plan and whether the test object is missed.
The annual production plan intelligent supervision method based on the reasoning algorithm comprises the following specific steps:
step 1: acquiring preventive test work plans and work ticket data from a production system: carding data (pre-test plan of high-voltage, chemical and electrical testing profession), work ticket information and defect data related to a main equipment preventive test plan, and acquiring required data from a production system according to a carding result;
step 2: test plan management: distinguishing equipment information from different professions, extracting the equipment information from equipment operation and maintenance periods of a maintenance and modification module in a production system, mainly checking whether equipment is subjected to a system production plan or not, and checking whether a station account is complete or not in the reverse;
step 3: planning execution management: and (5) associating a power failure application form: for a production plan requiring power failure, associating a power failure application form, and checking details of the power failure application form; work ticket and system pre-test plan inconsistency supervision: the production plan is used for removing the associated work ticket, such as the production plan of a period unit (1 month), and when the current day is cut off, a corresponding work ticket should be provided in the system every month; through statistical analysis, if the work ticket is found to be absent, the work ticket is considered to be inconsistent with the system pre-test plan; test report and system pre-test plan inconsistency supervision: the production plan is used for removing the associated test report, such as the production plan of a period unit (1 month), the current day is cut off, and the test report is uploaded from the last month (5 working days are required to be uploaded after the test is completed, and the actual situation can be considered to be relaxed to 1 month), so that a corresponding work ticket is required to be provided in the system each month; through statistical analysis, if the work ticket is found to be absent, the work ticket is considered to be inconsistent with the system pre-test plan; planning out of date: in different dimensions (ground city bureau, transformer substation), comparing the planned starting time and the planned ending time of the production plan with the actual starting time and the actual ending time of the plan to judge whether the time exceeds the time and the number of the time exceeds the time;
step 4: and (5) reminding the equipment of exceeding the period: the equipment is out of date: in different dimensions (ground city bureau, transformer substation), according to the equipment test period, reminding the equipment of the over-period, for example, the last test day of a certain equipment is 2019-10-14, the period is 1 year, if the test is not started by 2020-10-14 days, reminding the equipment of the over-period until the equipment is tested. Meanwhile, early warning grades are classified according to the conditions of the equipment (equipment importance, equipment health, risk assessment algorithm and the like); major/emergency defect display: displaying the number of major emergency defects of the equipment in the dimension of the equipment, and individually checking the details of each major/emergency defect; the latest patrol plan shows: the latest patrol plan of the equipment can be displayed; developing hand filling functions: the reasons for the over-period of the equipment, the management and control measures and the next power failure planning time are manually filled by the clients.
Cross-probe method:
in dimension modeled data warehouses, there is an operation called drug Across, which chinese translates into "cross-probe".
In Bus Architecture (Bus Architecture) based dimension modeling, most of the dimension tables are shared by fact tables. For example, "marketing transaction fact table" and "inventory snapshot fact table" would have the same dimension tables, "date dimension", "product dimension" and "store dimension". At this time, if there is a fact that it is desired to compare sales and inventory in a common dimension, two SQL's are required to be issued to find sales data and inventory data counted in the dimension, respectively. The data is then merged by externally connecting based on the common dimension. This operation of issuing multiple SQL's and then merging is cross-probing.
While the need for such cross-probing is common, there is a modeling approach to avoid cross-probing, namely merging fact tables (Consolidated Fact Table). Merging fact tables refers to a modeling method that combines facts at the same granularity in different fact tables. I.e., a fact table is newly built whose dimensions are a set of the same dimensions of two or more fact tables, facts being facts of interest in several fact tables. The data of this fact table is from the same staring Area as the data of the other fact tables.
Merging fact tables is better than cross-probing in both performance and ease of use, but the fact tables that are combined must be at the same granularity and dimension level.
Reasoning mode and classification of intelligent reasoning algorithm:
classification by inference logic basis:
deduction reasoning: deductive reasoning is the conclusion underlying these known knowledge that is appropriate for a particular situation, starting from the known general knowledge. Is a general to individual reasoning method, the core of which is three-section theory,
induction reasoning: is an individual to general reasoning method. The reasoning process that concludes the general conclusions from a sufficient number of cases.
Default reasoning: default reasoning, also called default reasoning, is the reasoning that is performed assuming that certain conditions are already in possession of the knowledge in case of incomplete knowledge.
Based on the certainty of knowledge used in reasoning
Deterministic reasoning: deterministic reasoning means that the knowledge used in reasoning is accurate and the conclusions drawn are also definite, with true or false values, and no third case.
Uncertainty reasoning: uncertainty reasoning means that the knowledge used in reasoning is not all accurate, nor is the conclusion drawn exactly positive, with the true value lying between true and false.
Monotonicity in the reasoning process
Monotonic reasoning: the conclusion drawn is in a monotonically increasing trend and is approaching the final goal.
Non-monotonic reasoning: due to the addition of new knowledge, not only does there be no enhancement to the conclusion that has been drawn, but it is negated.
Control strategy for reasoning:
inference direction: forward and reverse directions;
solving a strategy, namely one solution, all solutions and an optimal solution;
conflict resolution: sorting the positive objects and sorting the matching degree;
restriction strategy: depth, width, time, space.
The foregoing is merely illustrative of the present invention, and the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the scope of the present invention, and therefore, the scope of the present invention shall be defined by the scope of the appended claims.
Claims (7)
1. An annual production plan intelligent supervision method based on an inference algorithm is characterized in that: the method comprises the following steps: the annual production plan is supervised and supervised by extracting the arrangement information of the test plan and the work ticket from the 6+1 production management system, and the intelligent analysis and accurate matching are carried out on the arrangement data of the production plan by combining an intelligent reasoning algorithm through the cross exploration, dimension integration and splitting method, so that the plan supervision is realized; the annual production plan intelligent supervision method based on the reasoning algorithm comprises the following specific steps:
step 1: acquiring preventive test work plans and work ticket data from a production system: data related to a preventive test plan of the carding master device, work ticket information and defect data, and acquiring required data from a production system according to a carding result;
step 2: test plan management: distinguishing equipment information from different professions, extracting the equipment information from equipment operation and maintenance periods of a maintenance and modification module in a production system, mainly checking whether equipment is subjected to a system production plan or not, and checking whether a station account is complete or not in the reverse;
step 3: planning execution management: and (5) associating a power failure application form: for a production plan requiring power failure, associating a power failure application form, and checking details of the power failure application form; work ticket and system pre-test plan inconsistency supervision: removing the associated work ticket by using the production plan; through statistical analysis, if the work ticket is found to be absent, the work ticket is considered to be inconsistent with the system pre-test plan; test report and system pre-test plan inconsistency supervision: using a production plan to disassociate test reports; through statistical analysis, if the work ticket is found to be absent, the work ticket is considered to be inconsistent with the system pre-test plan; planning out of date: in the dimensions of different local municipalities and substations, comparing the planned starting time and the planned ending time of the production plan with the actual starting time and the actual ending time of the plan to judge whether the time exceeds the time and the number of the time exceeds the time;
step 4: and (5) reminding the equipment of exceeding the period: the equipment is out of date: reminding the equipment of the overtime according to the equipment test period in the dimensionalities of different local municipalities and substations, and meanwhile, classifying the early warning grades of the equipment of the overtime according to the equipment importance of the equipment per se condition by an equipment health degree and risk assessment algorithm; major/emergency defect display: displaying the number of major emergency defects of the equipment in the dimension of the equipment, and individually checking the details of each major/emergency defect; the latest patrol plan shows: the latest tour plan of the equipment can be displayed.
2. The intelligent supervision method for annual production plans based on an inference algorithm according to claim 1, wherein the method comprises the following steps: the planning supervision method comprises three aspects: 1) The supervision system pre-tests the plan consistency by associating the production plan work order, the work order and the equipment test cycle time; 2) According to the equipment test period, monitoring whether the compiled test plan exceeds the limit and the number of the exceeding limit; 3) And according to the equipment ledgers and the equipment test period, supervising the compiled test plan and whether the test object is missed.
3. The intelligent supervision method for annual production plans based on an inference algorithm according to claim 1, wherein the method comprises the following steps: the primary equipment preventive test plan in step 1 includes the pre-test plan of high voltage, chemical and electrical testing professions.
4. The intelligent supervision method for annual production plans based on an inference algorithm according to claim 1, wherein the method comprises the following steps: the step 4 also comprises the hand filling function: the reasons for the over-period of the equipment, the management and control measures and the next power failure planning time are manually filled by the clients.
5. The intelligent supervision method for annual production plans based on an inference algorithm according to claim 1, wherein the method comprises the following steps: the cross-probe method is replaced by a merged fact table.
6. The intelligent supervision method for annual production plans based on an inference algorithm according to claim 1, wherein the method comprises the following steps: the intelligent reasoning algorithm adopts deductive reasoning, inductive thrust or default reasoning.
7. The intelligent supervision method for annual production plans based on an inference algorithm according to claim 6, wherein: the control strategy of reasoning includes the direction of reasoning: forward and reverse directions; solving a strategy, namely one solution, all solutions and an optimal solution; conflict resolution: sorting the positive objects and sorting the matching degree; restriction strategy: depth, width, time, space.
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