CN111552241A - Assembly production line simulation model optimization method - Google Patents
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Abstract
The invention provides an assembly line simulation model optimization method, which belongs to the field of production line simulation model optimization, and is characterized in that each procedure in an assembly line simulation model is endowed with an execution priority, and the relationship between the execution priority and the acquisition sequence during resource allocation is established and determined; determining that the process execution priority combination is associated with the product production cycle, wherein the execution priority combinations of different processes correspond to different product production cycles, and the shortest product production cycle can be found by searching the optimal execution priority combination of the processes; and giving a specific execution priority combination iterative optimization method of the working procedure, and finding the optimal execution priority combination by the method.
Description
Technical Field
The invention relates to the field of production line simulation models, in particular to an optimization method of an assembly production line simulation model.
Background
Since modern manufacturing lines have become extremely complex, the performance of the production line is affected by various factors such as the production flow of products, the layout of the production line, the allocation of human resources, the performance of equipment, the failure rate of equipment, the performance of logistics system and the performance of supply chain system, and it is very difficult to effectively evaluate the production line system by a single algorithm. In this context, discrete event simulation theory and corresponding simulation software have emerged. The production line system can be modeled and simulated through discrete event simulation software, relevant elements of the production line system are incorporated into a model, the operation rules of the elements are extracted and abstracted, and the elements are represented by mathematical distribution or programming language. The established production line system model is subjected to simulation operation, the information of the production time of the system, the busy degree of each element, the production bottleneck and the like can be analyzed, meanwhile, the influence of the production line elements such as the change of the number of people on the production line efficiency can be analyzed, and the suggestion of production line adjustment is given.
At present, in the field of product assembly by adopting a production line, assembly relation is generally performed in series, a next procedure can be performed after the previous procedure is performed, products flow among different stations, a product process path is fixed, the requirements for various resources in the product assembly process are clear, and an assembly production line simulation model can be established according to the actual assembly process of the products.
However, for a complex product assembly line, such as an aircraft assembly line, a spacecraft assembly line, etc., each assembly unit performs a small part of work, and there may be multiple assembly units working at the same time, which means that products cannot flow in the assembly units because there are multiple assembly units requesting the same product in the model at the same time, which cannot be realized when the simulation model of the assembly line is built. Because the assembly unit network in the assembly line simulation model is usually very large, the number of the assembly units may reach hundreds to thousands, and the assembly units are overlapped greatly in space, the modeling cannot be performed according to the actual physical positions of the assembly units, and therefore the assembly line simulation model construction of such complex products cannot be realized by using the traditional assembly line simulation modeling means.
Therefore, researchers have proposed a new assembly line simulation model, which includes a logical simulation layer and a physical simulation layer, wherein the logical simulation layer includes an assembly line simulation unit model and a dependency relationship between the assembly line simulation unit models, and the physical simulation layer includes an assembly station, consumable resources and recycling resources, and further proposed specific steps of constructing the assembly line simulation model.
The model divides the simulation model of the assembly production line into a physical simulation layer and a logical simulation layer, and can express the position movement of a product in a real space and the running state of an assembly process of the product on each station; the simulation model of the assembly line can be constructed for the assembly line of complex products such as aircrafts and spacecrafts, wherein the products do not move or only move among a plurality of fixed stations and a plurality of assembly units work at the same time; the influence of the recycled resources and the consumable resources on the running state of the assembly production line can be reflected; the influence of the dependency relationship among different procedures on the running state of the assembly production line can be reflected. The influence of space limitation on the running state of the assembly line can be reflected.
The assembly line simulation model consists of a physical simulation layer and a logic simulation layer.
The physical simulation layer can express the physical position of the product in a real space, the movement generated in the assembly process and the change of the product.
The physical simulation layer is composed of a plurality of stations, circularly used resources and consumable resources.
A station represents a stage in the product assembly process where the physical location of the product is relatively fixed and where some assembly, testing, debugging or inspection work is done. The assembly process of the product can be divided into a plurality of stations, and after the work of the previous station is finished, the product is moved to the next station.
The work in the station can be divided into a plurality of working procedures, the completion of all the working procedures indicates that the work of the station is finished, and the product can be moved to the next station.
The products move between the stations in sequence without crossing the stations.
The recycling resources comprise resources which can be recycled and reused in the assembly process of the product, and comprise equipment, tools, personnel and the like.
In particular, the operation space is used as a recycling resource, the space available for assembly operation on the product is divided into a plurality of units, each unit can accommodate certain personnel or equipment for assembly operation, and each unit is defined as a recycling resource.
The recycling resources may be applied and released periodically during product assembly.
The consumable resources comprise parts, finished products, standard parts, consumable materials and the like which are needed to be used in the assembly process of the product.
The consumable resource may be applied during the product assembly process.
The logic simulation layer can express the dependency relationship among all the processes in each station, the process execution sequence, the application and release of the processes to the recycling resources, the application of the processes to the consumable resources, and the state judgment of the process starting execution, waiting and execution completion.
In the logical simulation layer, the stations in the physical simulation layer are mapped into a set of a series of procedures with certain interdependence relation.
The inter-process dependence is as follows:
1. each process has one or more pre-processes except the first process, and the process has an execution condition only when all the pre-processes of the one process are executed;
2. each process has 0 or more post-processes, which can be calculated from the pre-processes of the other processes.
Before a process is started to execute, executing condition judgment is carried out, and the executing condition judgment comprises the following steps:
1. all the front procedures of the procedure are finished;
2. the required recycling resources are applied for the process, and the required recycling resources are required to be in an available state and are not occupied by other processes;
3. the process applies for the required consumable resources, which must be available in sufficient quantity.
If the execution condition is not satisfied before the process starts executing, the process is in a waiting state.
And after all the process execution conditions are met, starting the process, informing the post-process that the process can be started after the process is executed for a certain time, and releasing occupied recycled resources.
And after all the working procedures of one station are finished, the work of the station is finished, the product is moved to the next station, and after all the work of the station is finished, the assembly process of the product is finished.
The production cycle of the product and the productivity of the production line can be evaluated by utilizing the model, but an effective optimization method is still lacked for how to adjust the simulation model to improve the productivity of the production line.
At present, aiming at the problem of optimizing the productivity of the production line, an empirical method or an experimental verification method is still adopted, for example, according to the actual running condition of the production line and the simulation condition of a model, certain production line parameters such as the configuration number of production line personnel, the process flow, the equipment number and the like are adjusted, then the simulation result or the data analysis result is observed, and the parameters are correspondingly adjusted until an expected result is achieved.
Disclosure of Invention
The invention aims to: an assembly line simulation model optimization method is provided, each procedure in the assembly line simulation model is endowed with an execution priority, and the relationship between the execution priority and the acquisition sequence during resource allocation is established and determined; determining that the process execution priority combination is associated with the product production cycle, wherein the execution priority combinations of different processes correspond to different product production cycles, and the shortest product production cycle can be found by searching the optimal execution priority combination of the processes; and giving a specific execution priority combination iterative optimization method of the working procedure, and finding the optimal execution priority combination by the method.
The technical scheme adopted by the invention is as follows:
an assembly line simulation model optimization method, each process in the assembly line simulation model is assigned with an execution priority, represented by a number, the priority represents the distribution sequence of the process when the process simultaneously applies for the same resource with other processes, and when simulation is carried out, the process with high priority should preferentially obtain the resource;
and searching a combination S of priority numbers of each procedure, wherein under the condition of S, the shortest production cycle of the product obtained by the operation of the simulation model is obtained, and the specific steps of searching the optimal solution are as follows:
step 1: operating the simulation model according to the current priority digital combination S to obtain a product production period P and an initial system temperature Tmax;
step 2: generating a new priority number combination S1 by randomly selecting two procedures from the original priority number combination, exchanging the priority numbers of the two procedures, and running a simulation model to obtain a product production period P1;
and step 3: if P1 < P, accepting a new number combination S1, if P1 is more than or equal to P, accepting S1 with a certain probability, wherein the probability is calculated by comparing the value V of Exp (- (P1-P)/T) with a random number between 0 and 1, and if V is more than the random number, accepting S1, reducing the temperature T, and after the temperature T1 is equal to T r;
and 4, step 4: repeating the steps 2 and 3 until a preset product production cycle threshold value or a preset lower temperature limit Tmin is met;
wherein r represents a reduction rate, and is set according to requirements and used for controlling the speed of cooling; tmax represents the initial temperature of the system, and the initial temperature of the system is in a high temperature state; tmin represents the system termination temperature and if the system temperature reaches Tmin, the search is stopped.
In the scheme, firstly, a system initial temperature Tmax is manually set or automatically generated in step 1, the temperature T, the system initial temperature Tmax and the system termination temperature Tmin in the scheme are set to limit the iteration times of the scheme, wherein Tmax, Tmin and the reduction rate r of each iteration are preset according to requirements, Tmax is generally set to be 1, when the scheme meeting the preset product production cycle threshold cannot be found, the converted temperature T1 is compared with Tmin, if T1 is less than or equal to Tmin, the iteration repeated searching for the priority digit combination S for enough times is carried out, and the iteration repeated searching for the priority digit combination S cannot be found, so that the iteration repeated searching for the product can be directly stopped; of course, at T1> Tmin, the product production cycle P1 corresponding to the new priority digit combination S1 found at this time satisfies the preset product production cycle threshold, and the priority digit combination S1 at this time is the finally determined priority digit combination S.
For better implementation of the present solution, further, the determining manner of the initial priority includes, but is not limited to, the following three manners:
mode 1: calculating the sum of the number of the front working procedures and the number of the rear working procedures of each working procedure, recording the sum as N, and assigning a priority initial value to each working procedure according to the descending order of the number of the N; the larger the N is, the higher the priority is, the maximum process priority number N is 1, and then the priority numbers are sequentially increased;
mode 2: calculating the execution time of each procedure, recording as T, descending according to the numerical size of T, and assigning a priority initial value to each procedure; the process with the larger T is, the higher the priority is, the process with the largest T has the priority number of 1, and then the priority numbers are sequentially increased;
mode 3: marking M ═ α × N + β × T, wherein α and β are weights, and assigning a priority initial value to each process in descending order according to the numerical size of M; the larger M process, the higher the priority, the maximum M process priority number is 1, and then the priority numbers are sequentially incremented.
For better implementation of the present solution, further, the execution priority is represented by a natural number.
In order to better implement the scheme, further, the assembly line simulation model consists of a physical simulation layer and a logic simulation layer, wherein the physical simulation layer expresses the physical position of the product in a real space, the movement generated in the assembly process and the change of the product; the physical simulation layer consists of a plurality of stations, circularly used resources and consumable resources;
the logic simulation layer expresses the dependency relationship among all the procedures in each station, the procedure execution sequence, the application and release of the recycled resources by the procedures and the application of the consumable resources by the procedures, and also expresses the state judgment of the starting, waiting and finishing of the procedures.
For better implementation of the scheme, the station represents a certain stage in the product assembly process, at which the physical position of the product is relatively fixed, and at which some assembly, test, debugging and/or inspection work is completed;
the assembly process of the product can be divided into a plurality of stations, and after the work of the previous station is finished, the product is moved to the next station;
the work in the station can be divided into a plurality of working procedures, the completion of all the working procedures indicates that the work of the station is finished, and the product can be moved to the next station. The products move between the stations in sequence without crossing the stations.
For better implementation of the scheme, further, the recycled resources include resources that can be recycled and reused in the assembly process of the product, and the recycled resources can be periodically applied and released in the assembly process of the product.
In order to better implement the scheme, the operation space is further used as a recycling resource, the space available for assembly operation on the product is divided into a plurality of units, each unit can accommodate certain personnel or equipment for assembly operation, and each unit is defined as a recycling resource.
In order to better implement the scheme, the station position in the physical simulation layer is further mapped into a series of process set with certain interdependence relation in the logic simulation layer.
In order to better implement the present solution, further, the dependency relationship between the processes mainly includes:
dependency 1: each process has one or more pre-processes except the first process, and the process has an execution condition only when all the pre-processes of the one process are executed;
dependency 2: each process has 0 or more post-processes, which can be calculated from the pre-processes of the other processes.
In order to better implement the scheme, further, before a process starts to be executed, execution condition judgment is carried out, wherein the execution condition mainly comprises the following conditions:
execution condition 1: all the front procedures of the procedure are finished;
execution condition 2: the required recycling resources are applied for the process, and the required recycling resources are required to be in an available state and are not occupied by other processes;
execution condition 3: the process applies for the required consumable resources, which must be available in sufficient quantity.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the invention provides an optimization method of an assembly line simulation model, which assigns an execution priority to each procedure in the assembly line simulation model, establishes and determines the relation between the execution priority and the acquisition sequence during resource allocation;
2. the method for optimizing the simulation model of the assembly production line determines that the association exists between the process execution priority combination and the product production cycle, the execution priority combinations of different processes correspond to different product production cycles, and the shortest product production cycle can be found by searching the optimal execution priority combination of the processes;
3. the invention provides a simulation model optimization method for an assembly production line, which provides a specific execution priority combination iterative optimization method for a process, and an optimal execution priority combination can be found through the method.
Drawings
In order to more clearly illustrate the technical solution, the drawings needed to be used in the embodiments are briefly described below, and it should be understood that, for those skilled in the art, other related drawings can be obtained according to the drawings without creative efforts, wherein:
fig. 1 is a schematic flow diagram of the present invention.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, 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 should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and therefore should not be considered as a limitation to the scope of protection. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The present invention will be described in detail with reference to fig. 1.
Example 1:
an assembly line simulation model optimization method, each process in the assembly line simulation model is assigned with an execution priority, represented by a number, the priority represents the distribution sequence of the process when the process simultaneously applies for the same resource with other processes, and when simulation is carried out, the process with high priority should preferentially obtain the resource;
and searching a combination S of priority numbers of each procedure, wherein under the condition of S, the shortest production cycle of the product obtained by the operation of the simulation model is obtained, and the specific steps of searching the optimal solution are as follows:
step 1: operating the simulation model according to the current priority digital combination S to obtain a product production period P and an initial system temperature Tmax;
step 2: generating a new priority number combination S1 by randomly selecting two procedures from the original priority number combination, exchanging the priority numbers of the two procedures, and running a simulation model to obtain a product production period P1;
and step 3: if P1 < P, accepting a new number combination S1, if P1 is more than or equal to P, accepting S1 with a certain probability, wherein the probability is calculated by comparing the value V of Exp (- (P1-P)/T) with a random number between 0 and 1, and if V is more than the random number, accepting S1, reducing the temperature T, and after the temperature T1 is equal to T r;
and 4, step 4: repeating the steps 2 and 3 until a preset product production cycle threshold value or a preset lower temperature limit Tmin is met;
wherein r represents a reduction rate, and is set according to requirements and used for controlling the speed of cooling; tmax represents the initial temperature of the system, and the initial temperature of the system is in a high temperature state; tmin represents the system termination temperature and if the system temperature reaches Tmin, the search is stopped.
The working principle is as follows: in the scheme, firstly, a system initial temperature Tmax is manually set or automatically generated in step 1, the temperature T, the system initial temperature Tmax and the system termination temperature Tmin in the scheme are set to limit the iteration times of the scheme, wherein Tmax, Tmin and the reduction rate r of each iteration are preset according to requirements, Tmax is generally set to be 1, when the scheme meeting the preset product production cycle threshold cannot be found, the converted temperature T1 is compared with Tmin, if T1 is less than or equal to Tmin, the iteration repeated searching for the priority digit combination S for enough times is carried out, and the iteration repeated searching for the priority digit combination S cannot be found, so that the iteration repeated searching for the product can be directly stopped; of course, at T1> Tmin, the product production cycle P1 corresponding to the new priority digit combination S1 found at this time satisfies the preset product production cycle threshold, and the priority digit combination S1 at this time is the finally determined priority digit combination S.
Each procedure in the assembly line simulation model is represented by a number and is endowed with an execution priority to represent the priority order of all the procedures for obtaining resources, in the process of determining the minimum value of the production period P of the product, the judgment modes in the steps 2 and 3 are repeatedly adopted, the internal logic is that the pseudo-random conversion procedure is repeated to carry out sequence conversion of the procedures to form the production sequence of the product under different procedure orders, and then a priority digital combination S which meets a preset production period or a preset lower temperature limit is found in the production sequences of various products, so that the production period P of the product corresponding to the priority digital combination S meets the preset requirement.
Example 2:
on the basis of the above embodiment 1, the present invention determines the initial priority in three ways including, but not limited to:
mode 1: calculating the sum of the number of the front working procedures and the number of the rear working procedures of each working procedure, recording the sum as N, and assigning a priority initial value to each working procedure according to the descending order of the number of the N; the larger the N is, the higher the priority is, the maximum process priority number N is 1, and then the priority numbers are sequentially increased;
mode 2: calculating the execution time of each procedure, recording as T, descending according to the numerical size of T, and assigning a priority initial value to each procedure; the process with the larger T is, the higher the priority is, the process with the largest T has the priority number of 1, and then the priority numbers are sequentially increased;
mode 3: marking M ═ α × N + β × T, wherein α and β are weights, and assigning a priority initial value to each process in descending order according to the numerical size of M; the larger M process, the higher the priority, the maximum M process priority number is 1, and then the priority numbers are sequentially incremented.
For better implementation of the present solution, further, the execution priority is represented by a natural number.
Other parts of this embodiment are the same as those of embodiment 1, and thus are not described again.
Example 3:
on the basis of any one of the embodiments 1-2, the assembly line simulation model consists of a physical simulation layer and a logic simulation layer, wherein the physical simulation layer expresses the physical position of a product in a real space, the movement of the product in the assembly process and the change of the product; the physical simulation layer consists of a plurality of stations, circularly used resources and consumable resources;
the logic simulation layer expresses the dependency relationship among all the procedures in each station, the procedure execution sequence, the application and release of the recycled resources by the procedures and the application of the consumable resources by the procedures, and also expresses the state judgment of the starting, waiting and finishing of the procedures.
For better implementation of the scheme, the station represents a certain stage in the product assembly process, at which the physical position of the product is relatively fixed, and at which some assembly, test, debugging and/or inspection work is completed;
the assembly process of the product can be divided into a plurality of stations, and after the work of the previous station is finished, the product is moved to the next station;
the work in the station can be divided into a plurality of working procedures, the completion of all the working procedures indicates that the work of the station is finished, and the product can be moved to the next station. The products move between the stations in sequence without crossing the stations.
For better implementation of the scheme, further, the recycled resources include resources that can be recycled and reused in the assembly process of the product, and the recycled resources can be periodically applied and released in the assembly process of the product.
In order to better implement the scheme, the operation space is further used as a recycling resource, the space available for assembly operation on the product is divided into a plurality of units, each unit can accommodate certain personnel or equipment for assembly operation, and each unit is defined as a recycling resource.
In order to better implement the scheme, the station position in the physical simulation layer is further mapped into a series of process set with certain interdependence relation in the logic simulation layer.
In order to better implement the present solution, further, the dependency relationship between the processes mainly includes:
dependency 1: each process has one or more pre-processes except the first process, and the process has an execution condition only when all the pre-processes of the one process are executed;
dependency 2: each process has 0 or more post-processes, which can be calculated from the pre-processes of the other processes.
In order to better implement the scheme, further, before a process starts to be executed, execution condition judgment is carried out, wherein the execution condition mainly comprises the following conditions:
execution condition 1: all the front procedures of the procedure are finished;
execution condition 2: the required recycling resources are applied for the process, and the required recycling resources are required to be in an available state and are not occupied by other processes;
execution condition 3: the process applies for the required consumable resources, which must be available in sufficient quantity.
Other parts of this embodiment are the same as any of embodiments 1-2 described above, and thus are not described again.
Example 4:
on the basis of any one of the embodiments 1 to 3, the simulation model of the assembly line of an assembly station is optimized, and the following steps are sequentially performed:
1. defining the number of assembling stations;
the assembly stations are divided according to the assembly flow of the product production line, and are divided into 4 stations in the example.
2. Defining the number of processes in each station;
the number of processes is divided according to the assembling process to be performed in the product station, and the number of processes is 20 in this example.
3. Defining the dependency relationship between the procedures;
the dependency between the processes in this example is shown in table 1 below:
TABLE 1
4. Defining the types and the quantity of consumable resources and recycling resources;
the kind and quantity of the resources are defined according to the requirements in the product assembly production process, and the kind and quantity of the resources in this embodiment are as follows in table 2:
| serial number | Resource type | Resource name | Number of | |
| 1 | Recycling resources | Cabin space 1_1 | 1 | |
| 2 | Recycling resources | Cabin space 1_2 | 1 | |
| 3 | Recycling resources | Cabin space 1_3 | 1 | |
| 4 | Recycling resources | Cabin space 1_4 | 1 | |
| 5 | Recycling resources | Cabin space 1_5 | 1 | |
| 6 | | Personnel | 6 |
TABLE 2
5. And defining the requirement rule of each process on the resources.
The rule of the demand of the process on the resources in this embodiment is as follows:
TABLE 3
6. Operating a simulation model and evaluating the production cycle of the product;
according to the modeling method described in embodiment 3, a production line simulation model is constructed, and each process is assigned with an initial value, in this example, the process initial values are all assigned to 0, that is, the execution priorities are the same. Operating the simulation model to obtain a product with the production cycle as follows: 2567 minutes (42.8 hours).
7. And searching the optimal production cycle of the product.
The optimal procedure execution priority number combination and product production cycle are solved according to the flow shown in fig. 1.
The optimal process execution priority number combination is as follows 4:
| name (R) | Execution priority number |
| ST00 | [3] |
| WS01 | [7] |
| OP01 | [5] |
| OP02 | [8] |
| WS02 | [1] |
| OP03 | [9] |
| OP04 | [10] |
| OP05 | [6] |
| OP06 | [6] |
| WS03 | [9] |
| OP07 | [8] |
| OP08 | [8] |
| OP09 | [4] |
| OP10 | [2] |
| OP11 | [8] |
| OP12 | [6] |
| OP13 | [8] |
| OP14 | [7] |
| OP15 | [8] |
| OP16 | [2] |
| OP17 | [8] |
| OP18 | [1] |
| OP19 | [3] |
| OP20 | [7] |
And (3) running the simulation model under the condition of the optimal process execution priority number combination to obtain a product production cycle of 2234 minutes (37.2 hours), wherein the product production cycle is shortened by 12.9% compared with the default priority condition.
Other parts of this embodiment are the same as any of embodiments 1 to 3, and thus are not described again.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications and equivalent variations of the above embodiments according to the technical spirit of the present invention are included in the scope of the present invention.
Claims (10)
1. An assembly line simulation model optimization method is characterized in that: each procedure in the assembly line simulation model is assigned with an execution priority, the execution priority is represented by a number, the priority represents the distribution sequence of the procedure when the procedure simultaneously applies for the same resource with other procedures, and when simulation is carried out, the procedure with high priority should preferentially obtain the resource;
and searching a combination S of priority numbers of each procedure, wherein under the condition of S, the shortest production cycle of the product obtained by the operation of the simulation model is obtained, and the specific steps of searching the optimal solution are as follows:
step 1: operating the simulation model according to the current priority digital combination S to obtain a product production period P and an initial system temperature Tmax;
step 2: generating a new priority number combination S1 by randomly selecting two procedures from the original priority number combination, exchanging the priority numbers of the two procedures, and running a simulation model to obtain a product production period P1;
and step 3: if P1 < P, accepting a new number combination S1, if P1 is more than or equal to P, accepting S1 with a certain probability, wherein the probability is calculated by comparing the value V of Exp (- (P1-P)/T) with a random number between 0 and 1, if V is more than the random number, accepting S1, reducing the temperature T, and after the temperature T1= T r is reduced;
and 4, step 4: repeating the steps 2 and 3 until a preset product production cycle threshold value or a preset lower temperature limit Tmin is met;
wherein r represents a reduction rate, and is set according to requirements and used for controlling the speed of cooling; tmax represents the initial temperature of the system, and the initial temperature of the system is in a high temperature state; tmin represents the system termination temperature and if the system temperature reaches Tmin, the search is stopped.
2. The assembly line simulation model optimization method according to claim 1, wherein: the determination method of the initial value of the priority digit combination S includes, but is not limited to, the following three methods:
mode 1: calculating the sum of the number of the front working procedures and the number of the rear working procedures of each working procedure, recording the sum as N, and assigning a priority initial value to each working procedure according to the descending order of the number of the N; the larger the N is, the higher the priority is, the maximum process priority number N is 1, and then the priority numbers are sequentially increased;
mode 2: calculating the execution time of each procedure, recording as T, descending according to the numerical size of T, and assigning a priority initial value to each procedure; the process with the larger T is, the higher the priority is, the process with the largest T has the priority number of 1, and then the priority numbers are sequentially increased;
mode 3: marking M = alpha N + beta T, wherein alpha and beta are weights, and assigning a priority initial value to each process in descending order according to the numerical size of M; the larger M process, the higher the priority, the maximum M process priority number is 1, and then the priority numbers are sequentially incremented.
3. The assembly line simulation model optimization method according to claim 1, wherein: the execution priority is represented by a natural number.
4. The assembly line simulation model optimization method according to claim 1, wherein: the assembly line simulation model consists of a physical simulation layer and a logical simulation layer, wherein the physical simulation layer expresses the physical position of a product in a real space, the movement generated in the assembly process and the change of the product; the physical simulation layer consists of a plurality of stations, circularly used resources and consumable resources;
the logic simulation layer expresses the dependency relationship among all the procedures in each station, the procedure execution sequence, the application and release of the recycled resources by the procedures and the application of the consumable resources by the procedures, and also expresses the state judgment of the starting, waiting and finishing of the procedures.
5. The assembly line simulation model optimization method according to claim 4, wherein: the station represents a certain stage in the assembly process of the product, and at the stage, the physical position of the product is relatively fixed, and some assembly, test, debugging and/or inspection work is completed at the position;
the assembly process of the product can be divided into a plurality of stations, and after the work of the previous station is finished, the product is moved to the next station;
the work in the station can be divided into a plurality of working procedures, the completion of all the working procedures indicates that the work of the station is finished, and the product can be moved to the next station;
the products move between the stations in sequence without crossing the stations.
6. The assembly line simulation model optimization method according to claim 4, wherein: the recycling resources comprise resources which can be recycled and reused in the assembly process of the product, and can be periodically applied and released in the assembly process of the product.
7. The assembly line simulation model optimization method according to claim 4 or 6, wherein: the operation space is used as a recycling resource, the space on the product for assembly operation is divided into a plurality of units, each unit can accommodate certain personnel or equipment for assembly operation, and each unit is defined as a recycling resource.
8. The assembly line simulation model optimization method according to claim 4, wherein: in the logical simulation layer, the stations in the physical simulation layer are mapped into a set of a series of procedures with certain interdependence relation.
9. The assembly line simulation model optimization method of claim 8, wherein: the dependency relationship among the procedures mainly comprises:
dependency 1: each process has one or more pre-processes except the first process, and the process has an execution condition only when all the pre-processes of the one process are executed;
dependency 2: each process has 0 or more post-processes, which can be calculated from the pre-processes of the other processes.
10. The assembly line simulation model optimization method according to claim 8 or 9, wherein: before a process is started to execute, executing condition judgment is carried out, wherein the executing condition mainly comprises the following conditions:
execution condition 1: all the front procedures of the procedure are finished;
execution condition 2: the required recycling resources are applied for the process, and the required recycling resources are required to be in an available state and are not occupied by other processes;
execution condition 3: the process applies for the required consumable resources, which must be available in sufficient quantity.
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