CN115358537A - Multi-model multi-frame-number-based production capacity balancing method - Google Patents

Abstract

The invention relates to a multimachine-based multi-frame production capacity balancing method, which comprises the following steps of: step one, constructing a manufacturing capability model based on a manufacturing resource list; step two, based on the aircraft production process, dividing the capacity balance process into a main production plan capacity balance process and a WO manufacturing plan capacity balance process according to a two-stage plan; the main production plan capacity balance refers to coarse capacity balance, and the WO manufacturing plan capacity balance refers to fine capacity balance. The invention realizes the mode of adjusting the capacity by data drive, predicts the performability of the plan, balances the punctual matching capacity of key materials and the punctual delivery capacity of multiple machines and shelves, and solves the contradiction between the supply and demand of production capacity in a scientific way. The invention realizes the data interconnection and intercommunication and resource information sharing of distributed, heterogeneous, large-scale and multi-organization environments based on the application of a multi-Agent distribution scheduling model, and the provided algorithm method realizes more effective sharing, cooperation, management and scheduling of resources and services.

Description

Multi-model multi-frame-number-based production capacity balancing method

Technical Field

The invention relates to the technical field of production scheduling, in particular to a production capacity balancing method based on multiple models and multiple frames.

Background

First, terms related to the present invention are described as follows:

MPS main production plan: refers to a plan for determining the production amount of each specific model product in each specific time period (e.g., weekly) based on the production outline information, taking into account the actual production capacity in the specific time period (e.g., monthly). The main production plan directly comprises a production plan of the product and may also comprise a production plan of some components according to the actual situation of the enterprise; the main production plan is a basis for making a product assembly, test and maintenance operation plan, and is also a basis for making a component matching demand plan and other related material demand plans.

The work center: generally refers to a production operation unit for directly changing the material form or property, and can also be extended to be a general term of production resources to be considered when making a production plan. The production plan service object for developing capacity balance can be determined according to the actual conditions of the enterprise, and can be a processing branch, a production line and a production unit, or a group of production workers, a group of equipment, even a certain piece of equipment, a certain person and the like, which can be collectively called as a work center.

And (3) crude capacity balance: and (3) roughly predicting whether the capacity of the main production plan is overloaded or not according to monthly output by combining partial productivity of resources such as manpower, tool equipment, equipment and the like on a workshop site, and realizing an adjustment process aiming at the key bottleneck capacity.

Fine capability balance: and combining the productivity of the overall resources such as manpower, tool equipment and equipment on the workshop site, finely measuring whether the capacity of the aircraft assembly plan is overloaded or not, and realizing the adjustment process aiming at the key bottleneck capacity.

And (3) main production planning: and finally delivering the monthly production plan of the product.

EBOM: the product structure is described from the aspect of functions in a design-oriented mode, belongs to a product structure list output in a product design stage, and comprises all states of technical preparation of a certain product model.

MBOM: i.e., a manufacturing bill of materials, a reflection of the structure of the product being produced, such as the hierarchical relationship of parts, components, or the actual assembly process.

And (4) an option standard: standard data specified for the manufactured objects (products, parts, etc.) in terms of production terms and production quantities;

and (3) MRP operation: the method refers to reverse planning by taking each article as a planning object and taking a finishing period as a time reference according to the subordinate and quantity relation of each level of the article in the product structure.

The process comprises the following steps: a particular step in the manufacture, or use of the article to achieve a particular result.

WO: the work order and the MRP operation result are used for recording the manufacturing plan of the single frame which is sent to the workshop by the production management part of the aeronautical manufacturing enterprise and takes the self-made piece as the object.

Actual capacity/occupancy capacity: the machining time length in the planning period does not include a part exceeding the planning period;

loading: the total length of time that the resource is actually processed includes the portion that exceeds the planning period.

Under the comprehensive production expansion development policy of 'small core and large cooperation' of an aviation industrial host factory, the production mode of the airplane is changed from a multi-variety small batch to a multi-variety large batch. Due to the complex process and the long production period of the airplane, the yield of the airplane is improved while the economic value of the airplane is fully exerted on the premise of limited production resources. Therefore, balancing the capacity load of various resources on a multi-machine multi-production plan and avoiding the phenomenon of a large number of wave crests and wave troughs is a problem which needs to be solved urgently at present.

Disclosure of Invention

In view of this, embodiments of the present invention provide a multi-model multi-frame based capacity balancing method to formulate a capacity allocation manner capable of maximizing the yield and economic benefits.

In order to realize the purpose, the technical scheme of the invention is as follows: a multi-model multi-frame based production capacity balancing method comprises the following steps:

step one, constructing a manufacturing capability model based on a manufacturing resource list;

step two, based on the aircraft production process, dividing the capacity balance process into a main production plan capacity balance process and a WO manufacturing plan capacity balance process according to the capacity balance process of the two-stage plan; the main production plan capability balance refers to coarse capability balance, and the WO manufacturing plan capability balance refers to fine capability balance.

Further, the first step specifically includes:

step 1.1, acquiring basic data of manufacturing resources, and providing an operation basis for the balance of the coarse/fine capacity;

and step 1.2, acquiring working calendar data of the manufacturing resources, and providing an operation basis for the balance of the thickness/fineness capacity.

Further, the second step specifically includes:

step 2.1, balancing the capacity of the main production plan: the method supports the balance of material demand planning capacity based on the capacity of a work center, is used for measuring and calculating the recent product demand and simulates material demand planning data;

step 2.2, WO planning capability balance: supporting the balance of material demand planning capacity based on manufacturing resource capacity, wherein the fine capacity balance is used for measuring and calculating product demand information of an issued main production plan; calculating the capacity value of whether the material plan conforms to various required manufacturing resources; the measurement result is used as the basis for adjusting the resource capacity and planning the completion time.

Further, the step 2.1 of capacity balancing of the main production plan: the method supports the balance of the planning capacity of the material demand based on the capacity of the work center, is used for measuring and calculating the recent product demand, simulates the planning data of the material demand, and specifically comprises the following steps:

substep 1: initializing multi-model multi-frame planning data;

substep 2: initializing manufacturing capability model data;

substep 3: initializing data of a professional factory work center;

substep 4: initializing resource calendar and factory calendar data;

substep 5: initializing MBOM data;

substep 6: calling a cooperative scheduler to start coarse capability balance operation;

substep 7: feeding back a coarse capability balance result and issuing a capability balance suggestion;

substep 8: and adjusting resources, calling the cooperative scheduler to recalculate, and starting a new round of coarse capability balance.

Further, the step 2.2WO planning capability balance supports material demand planning capability balance based on manufacturing resource capability, and the fine capability balance is used for measuring and calculating product demand information of an issued main production plan; calculating the capacity value of whether the material plan conforms to various required manufacturing resources; the measurement result is used as the basis for adjusting the resource capacity and planning the completion time. The method specifically comprises the following steps:

substep 1: initializing multi-model multi-frame WO planning data;

substep 2: initializing manufacturing capability model data;

substep 3: initializing resource calendar and factory calendar data;

substep 4: initializing MBOM data;

substep 5: calling a cooperative scheduler to start detailed capability balance operation;

substep 6: feeding back a fine capability balance operation result and issuing a capability balance suggestion;

substep 7: and adjusting resources, calling the cooperative scheduler to recalculate, and starting a new round of detailed capability balance.

Has the advantages that:

under the guidance of a digital technology, the invention quantifies and visualizes the production capacity, realizes the mode of adjusting the capacity by data drive, predicts the plan performability, balances the punctual matching capacity of key materials and the multimachine type multiple-frame punctual delivery capacity, and solves the contradiction between the supply and demand of the production capacity in a scientific way.

The invention realizes the data interconnection and intercommunication and resource information sharing of distributed, heterogeneous, large-scale and multi-organization environments based on the application of a multi-Agent distribution scheduling model, and the provided algorithm method realizes more effective sharing, cooperation, management and scheduling of resources and services.

Drawings

FIG. 1 is a production planning capacity balancing business modeling diagram;

FIG. 2 is a flow chart of coarse capacity balancing/PCC product capacity control;

FIG. 3 is a flow chart of fine capacity balance/MCC material capacity balance.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and based on the embodiments of the present invention, all other embodiments obtained by a person skilled in the art without creative efforts belong to the protection scope of the present invention.

According to the embodiment of the invention, the method for balancing the production capacity based on the multi-model multi-rack is provided, and comprises the following steps:

the method comprises the following steps: a manufacturing capability model is built based on the manufacturing resource inventory.

Substep 1: resource capability base data;

and constructing resource capacity basic data suitable for coarse/fine capacity balance.

Referring to fig. 1, the resource capacity basic data includes two types, namely basic data of manufacturing resources and calendar data of the manufacturing resources, while the manufacturing resources involved this time include five types, namely equipment, tools, personnel and fields, and since the particularity of each type of manufacturing resources is managed in different systems, the data in the manufacturing resource basic data correlation table stored in the system needs to be extracted from other systems managing the manufacturing resources through interfaces.

Manufacturing resource basic data: the method comprises the steps of manufacturing resource basic data of equipment, manufacturing resource basic data of tools, manufacturing resource basic data of personnel and manufacturing resource basic data of fields, and storing and managing basic attributes of various resources.

Resource working calendar data: when the system is in capability balance operation, the production outline of the current highest version corresponding to the planning material number is extracted in a correlation mode according to the planning data to be measured and calculated. Meanwhile, the relevant field information of the manufacturing resources required by the plan is set in the required process file, the manufacturing resources required by the process file include 5 types of equipment, tools, personnel and fields, and each type of manufacturing resources can be recorded by setting different attributes according to multiple dimensions (according to time dimension, organization dimension and resource dimension), which is shown in fig. 2.

And substep 2: and setting basic data of the work center, and constructing resource capacity basic data suitable for fine capacity balance.

Because only partial resource capacity is considered in the rough capacity balance, the work center is used as a virtual container for loading key resource capacity and is used for initializing the bottleneck capacity, capacity increase or redundancy capacity balance is carried out aiming at the bottleneck capacity, after the capacity balance is carried out again, the work center identifies new bottleneck capacity again to realize capacity adjustment, and capacity balance is carried out continuously in a circulating mode.

Step two: calling a cooperative scheduler, namely starting a rough capacity balance operation flow of a main plan, wherein the cooperative server is a system service assembly which is based on a multi-Agent distribution scheduling model and integrates a mixed scheduling mechanism of a multi-Agent algorithm and a rule algorithm and a scheduling strategy; the method comprises the following specific steps:

substep 1: initializing main production plan data;

and the main production plan dynamically changes the plan state in the manufacturing process, and plan data initialization is carried out before each coarse capacity balance operation, wherein the plan state is the completed state which is not included in the coarse capacity balance operation.

And substep 2: initializing manufacturing capability model data;

initializing a factory calendar;

initializing a key resource calendar;

initializing a work center;

initializing the MBOM production view according to the change of the EBOM;

and initializing MBOM period standard data according to the change of the EBOM.

Substep 3: invoking the cooperative scheduler, starting the coarse capability balancing operation, referring to fig. 3, the specific steps are as follows:

operation step 1: automatically establishing data priority according to rules;

according to the scheduled delivery urgency degree, the system automatically establishes a production schedule priority;

according to the information of BOM, AO, resource state, etc., the system automatically establishes the distribution priority of the material consumption resource which is hung under the plan.

And an operation step 2: calling a cooperative scheduler to complete the resource occupation matching of the plan according to the priority;

the plan initialization data is matched according to the high plan priority, and if a plurality of items of data with high plan priority exist in one manufacturing resource, the data are matched according to the high material priority.

And during matching, the planned start time of the planned data is used as the start time of daily processing capacity data occupying the manufacturing resources, the duration data of the material data occupying the resources is used as the processing cycle data, and finally the time period of the planned data occupying the manufacturing resources is calculated.

The estimated manufacturing resource occupying time zone represents that the capacity of the manufacturing resource is satisfied if the estimated manufacturing resource occupying time zone is completely included in the planned completion time zone, and represents that the capacity of the manufacturing resource is not satisfied if the estimated manufacturing resource occupying time zone is not included.

And operation step 3: recording a planned balance start time and a balance end time;

for each resource planned to be used, calculating the machining time = single piece machining time X (the number of planned demands/the number of machining batches/the number of required resources); according to the quantity of resources required by the process, the earliest available resources are selected in a circulating manner, and the selected resources are occupied in working hours; and during occupation, the machining time is filled according to the equivalent amount, the starting time and the ending time of the time period are stored in a time axis object of the resource, the subsequent planning avoids the existing working time, and simultaneously the starting time and the ending time after the planning is balanced and the deadline time when the current working time exceeds the planning completion time are recorded, so that the subsequent system can conveniently identify and give out corresponding adjustment suggestions for use.

And 4, an operation step: circulating one by one until the last plan finishes the resource occupation;

and (4) performing capability test operation on all the plan data meeting the conditions according to the operation steps 1-3.

Substep 4: manufacturing resource load versus capacity;

and (4) measuring and calculating the task requirements and the actual delivery capacity of each production branch factory in the planning period aiming at the bottleneck parts with the delivery problems. During balancing, the actual task requirements are evaluated from the aspects of human resource use, product percent of pass and the like, and then the actual task requirements are compared and analyzed with the existing capacity to obtain a balance conclusion.

According to the capability gaps of the bottleneck resources/equipment and the bottleneck components, providing a measure plan and a cooperation plan:

the measure plan comprises the steps of improving the processing efficiency, optimizing the process, improving the quality index, increasing the production shift, prolonging the production time, increasing the quantity of equipment/resources and the like.

The collaboration plan includes both corporate-external collaboration and corporate-internal collaboration. In principle, a cooperation plan provided by balance of annual component matching demand plan capability is mainly an external cooperation plan; the internal cooperation is more used for cooperation requirements generated in the scheduling stage of the production operation plan, and the problem of insufficient external cooperation period is solved.

The method comprises the following specific steps:

demand capacity = ∑ daily shift x number of jobs per shift x key work center efficiency x key work center utilization (hours/days);

load capacity = sigma material yield = standard work hours of key work center occupied;

1) And (3) comparing the results: demand capacity = load capacity

Adjusting the suggestion: none.

2) And (3) comparing the results: demand capacity > load capacity

Adjusting the suggestion: optimizing the relation between the work center and the corresponding resources, increasing the number of manufacturing resources, increasing the processing time, improving the process, and dividing or combining the processing operation.

3) And (3) comparing the results: demand capacity < load capacity

Adjustment suggestion: optimizing the relation between the working center and the corresponding resources, reducing the number of resources, reducing the processing time, improving the process, and dividing or combining the processing operation.

Substep 5: manufacturing resource load and capacity adjustment;

and adjusting resources, recalculating and starting a new round of rough capability balance operation according to the comparison result of the load and the capability of the manufacturing resources.

Substep 6: based on the main plan with satisfied capability, MRP operation is realized, and a WO plan is generated.

Step three: invoking the cooperative scheduler to start the detailed capability balance operation flow of the wo plan

Substep 1: initializing WO planning data;

MRP operation is carried out once, WO plan data are initialized once, and the initialized data are used every time fine capability balance operation is called.

Substep 2: initializing manufacturing capability model data;

and (3) considering global resources without considering a work center, wherein the overall processing logic is consistent with a rough capacity balance operation flow based on a main plan in the step two-substep 2 manufacturing capacity model data initialization.

Substep 3: calling a cooperative scheduler and starting detailed capability balance operation;

after the capability balance of bottleneck resources/equipment and bottleneck components is developed by each professional production plant, the unbalanced products are measured, calculated and balanced according to the actual task requirements and the production capability of each type. And in balancing, the actual task requirements are evaluated by comprehensively considering the aspects of plan performance rate, resource load rate, task conflict condition, product qualification rate and the like, whether the capacity meets the matched delivery requirements of the components is judged, and the capacity requirements in each planning period are analyzed.

1) Data initialization, data preprocessing, resource initialization, an initialization plan and a resource calendar initialization;

2) A system scheduler is called, resource processing equivalent and resource processing continuity are considered, resource occupation and balance are carried out according to the shift in an effective working day, resource balance is realized, and an operation result is persisted;

3) Generating statistical summary data, processing resources in each month in a circulating way, and calculating the total processing capacity (total working hours in the whole month), the actual processing capacity (actually planned and occupied working hours) and planned and occupied working capacities (the working hours arranged in the MRP planned time) of the resources in the month;

4) Generating suggested data, and suggesting to increase the shift system from the start date of the resource plan for the plan of the pull-off period after balance, and only prompting the earliest adjusting date of the resource if the same resource pulls off in a plurality of plans; and for the resources of the key work center which are in the off-date period, generating a suggested plan adjusting days according to the off-date time.

The overall processing logic is substantially similar to the "main plan based rough capacity balancing algorithm flow of step two-substep 3 rough capacity balancing algorithm".

Substep 4: manufacturing resource load versus capacity;

load = yield of sigma material = standard man-hour of occupied resource;

capability = daily shift × number of jobs per shift × resource efficiency × resource utilization rate (hour/day);

capacity > = load, machining requirement is met, or capacity is abundant;

if the capacity is less than the load, the processing requirement is not met, and the capacity is insufficient and is not feasible.

Substep 5: manufacturing resource load and capacity adjustment;

and adjusting the resources, recalculating and starting a new round of detailed capability balance operation according to the comparison result of the load and the capability of the manufacturing resources. The overall processing logic is consistent with "step two master plan based rough capacity balancing algorithm flow-substep 5 manufacturing resource load and capacity adjustment".

The present invention describes a multi-model multi-frame based capacity balancing method for aviation manufacturing industry, and if those skilled in the art do not depart from the technical principle of the present invention, the insubstantial obvious changes or improvements can be made according to the present invention, and all that should fall within the protection scope of the claims of the present invention.

Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, but various changes may be apparent to those skilled in the art, and it is intended that all inventive concepts utilizing the inventive concepts set forth herein be protected without departing from the spirit and scope of the present invention as defined and limited by the appended claims.

Claims (5)

1. A multi-model multi-frame based production capacity balancing method is characterized by comprising the following steps:

step one, constructing a manufacturing capability model based on a manufacturing resource list;

step two, based on the aircraft production process, dividing the capacity balance process into a main production plan capacity balance process and a WO manufacturing plan capacity balance process according to the capacity balance process of the two-stage plan; the main production plan capability balance refers to coarse capability balance, and the WO manufacturing plan capability balance refers to fine capability balance.

2. The multi-model multi-chassis based capacity balancing method as claimed in claim 1, wherein said step one comprises:

step 1.1, acquiring basic data of manufacturing resources, and providing an operation basis for the balance of the coarse/fine capacity;

and 1.2, acquiring working calendar data of manufacturing resources, and providing an operation basis for the balance of the thickness/fineness capacity.

3. The multi-model multi-rack based throughput balancing method according to claim 1, wherein said second step specifically comprises:

step 2.1, balancing the capacity of the main production plan: the method supports the balance of material demand planning capacity based on the capacity of a work center, and is used for measuring and calculating the recent product demand and simulating material demand planning data;

step 2.2, WO planning capability balancing: the capacity balance of the material demand plan based on the manufacturing resource capacity is supported, and the fine capacity balance is used for measuring and calculating the product demand information of the issued main production plan; calculating the capacity value of whether the material plan conforms to various required manufacturing resources; the measurement result is used as the basis for adjusting the resource capacity and planning the completion time.

4. The multi-model multi-chassis based capacity balancing method of claim 3, wherein said step 2.1 master production plan capacity balancing: the method supports the balance of material demand planning capacity based on the capacity of a work center, is used for measuring and calculating the recent product demand, simulates material demand planning data, and specifically comprises the following steps:

substep 1: initializing multi-model multi-frame planning data;

and substep 2: initializing manufacturing capability model data;

substep 3: initializing data of a professional factory work center;

and substep 4: initializing resource calendar and factory calendar data;

substep 5: initializing MBOM data;

substep 6: calling a cooperative scheduler and starting coarse capability balance operation;

substep 7: feeding back a coarse capability balance result and issuing a capability balance suggestion;

substep 8: and adjusting resources, calling the cooperative scheduler to recalculate, and starting a new round of coarse capability balance.

5. The multi-model multi-chassis based production capacity balancing method of claim 4, wherein the step 2.2WO planning capacity balancing supports material demand planning capacity balancing based on manufacturing resource capacity, and the fine capacity balancing is used for measuring and calculating product demand information of an issued main production plan; measuring and calculating the capacity value of whether the material plan conforms to various required manufacturing resources; the measurement and calculation result is used as a basis for adjusting the resource capacity and planning completion time, and specifically comprises the following steps:

substep 1: initializing multi-model multi-frame WO planning data;

substep 2: initializing manufacturing capability model data;

substep 3: initializing resource calendar and factory calendar data;

substep 4: initializing MBOM data;

substep 5: calling a cooperative scheduler to start detailed capability balance operation;

substep 6: feeding back a fine capability balance operation result and issuing a capability balance suggestion;

substep 7: and adjusting resources, calling the cooperative scheduler to recalculate, and starting a new round of detailed capability balance.

Images