CN116993531B - Optimization method and system for shower room product production process - Google Patents
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Abstract
The invention provides a method and a system for optimizing a shower room product production process, which relate to the technical field of process optimization, and the method comprises the following steps: based on big data, obtaining a product component set of the shower room product; obtaining a user shower room demand list; obtaining a production optimization analysis result; judging whether the production optimization analysis result meets the preset production optimization or not; when the production optimization analysis result meets the preset production optimization, obtaining a component production optimization instruction; constructing a component production optimization space; the method comprises the steps of obtaining a shower room component production optimization decision, optimizing a shower room product production process according to the shower room component production optimization decision, solving the technical problem that the compliance of the shower room product performance and the user requirement is not high due to the fact that production process parameters are uniform in the prior art, achieving the technical effects of improving the compliance of the shower room product performance and the user requirement and reducing production cost.
Description
Technical Field
The invention relates to the technical field of process optimization, in particular to a method and a system for optimizing a shower room product production process.
Background
The shower room product comprises various components such as a shower head, a high-pressure pipe, shower room glass and the like, the existing shower room product is produced by manufacturers according to specified standards, the production process parameters are uniform, a user needs to purchase corresponding products according to requirements, and the requirements of the user and the performances of the shower room product are difficult to agree.
In summary, the prior art has the technical problem that the product performance of the shower room is not high in compliance with the requirements of users due to the fact that the production process parameters are uniform.
Disclosure of Invention
The invention provides a method and a system for optimizing a shower room product production process, which are used for solving the technical problem that the performance of the shower room product is not high in compliance with the requirements of users due to unified production process parameters in the prior art.
According to a first aspect of the present invention there is provided a method of optimising the production process of a shower stall product comprising: based on big data, obtaining a product component set of a shower room product, wherein the product component set comprises M product components, and M is a positive integer greater than 1; based on the product component set, constructing a shower room demand acquisition table, and acquiring shower room product demands of a first user according to the shower room demand acquisition table to obtain a shower room demand table of the user; carrying out production optimization analysis on the product component set based on the user shower room demand table to obtain a production optimization analysis result, wherein the production optimization analysis result comprises M component production optimizations; judging whether the production optimization analysis result meets the preset production optimization or not; when the production optimization analysis result meets the preset production optimization, obtaining a component production optimization instruction, wherein the component production optimization instruction has a shower room optimization component identifier; constructing a component production optimization space based on the component production optimization instruction; and carrying out component production optimization analysis according to the component production optimization space based on the user shower room demand list and the shower room optimization component identifier to obtain a shower room component production optimization decision, and carrying out optimization of a shower room product production process according to the shower room component production optimization decision.
According to a second aspect of the present invention there is provided a system for optimisation of a shower enclosure product manufacturing process comprising: the system comprises a product component set acquisition module, a product component set acquisition module and a control module, wherein the product component set acquisition module is used for acquiring a product component set of a shower room product based on big data, the product component set comprises M product components, and M is a positive integer greater than 1; the product demand acquisition module is used for constructing a shower room demand acquisition table based on the product component set, acquiring the shower room product demand of a first user according to the shower room demand acquisition table, and acquiring a shower room demand table of the user; the production optimization analysis module is used for carrying out production optimization analysis on the product component set based on the user shower room demand table to obtain a production optimization analysis result, wherein the production optimization analysis result comprises M component production optimizations; the analysis result judging module is used for judging whether the production optimization analysis result meets the preset production optimization or not; the component production optimization instruction acquisition module is used for acquiring a component production optimization instruction when the production optimization analysis result meets the preset production optimization, and the component production optimization instruction is provided with a shower room optimization component identifier; the optimization space construction module is used for constructing a component production optimization space based on the component production optimization instruction; the production optimization analysis module is used for carrying out component production optimization analysis according to the component production optimization space based on the user shower room demand list and the shower room optimization component identification, obtaining a shower room component production optimization decision, and carrying out optimization of a shower room product production process according to the shower room component production optimization decision.
According to the optimization method of the shower room product production process adopted by the invention, a product component set of the shower room product is obtained based on big data, a shower room demand collection table is constructed, the shower room product demand of a first user is collected according to the shower room demand collection table, the user shower room demand table is obtained, the product component set is subjected to production optimization analysis, a production optimization analysis result is obtained, whether the production optimization analysis result meets the preset production optimization is judged, when the production optimization analysis result meets the preset production optimization, a component production optimization instruction is obtained, a component production optimization space is constructed based on the component production optimization instruction, component production optimization analysis is performed, a shower room component production optimization decision is obtained, and the shower room product production process is optimized according to the shower room component production optimization decision, so that the optimization of the shower room product production process is realized, the compliance of the shower room product performance and the user demand is improved, and the technical effect of reducing the production cost is achieved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
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In order to more clearly illustrate the invention or the technical solutions of the prior art, the following brief description will be given of the drawings used in the description of the embodiments or the prior art, it being obvious that the drawings in the description below are only exemplary and that other drawings can be obtained from the drawings provided without the inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an optimization method of a shower room product production process according to an embodiment of the present invention;
FIG. 2 is a flow chart of obtaining a production optimization resolution result according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for obtaining a shower enclosure assembly production optimization decision in an embodiment of the invention;
fig. 4 is a schematic structural diagram of an optimizing system for a shower room product production process according to an embodiment of the present invention.
Reference numerals illustrate: the system comprises a product component set acquisition module 11, a product demand acquisition module 12, a production optimization analysis module 13, an analysis result judgment module 14, a component production optimization instruction acquisition module 15, an optimization space construction module 16 and a production optimization analysis module 17.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Example 1
Fig. 1 is a diagram of an optimization method of a shower room product production process according to an embodiment of the present invention, where the method includes:
step S100: based on big data, obtaining a product component set of a shower room product, wherein the product component set comprises M product components, and M is a positive integer greater than 1;
specifically, the development of modern internet and internet of things technologies is mature, and based on the development, a product component set of shower room products can be screened from massive big data in the internet, wherein the product component set comprises M product components, such as a shower head, a triangular valve, a high-pressure pipe and the like, and M is a positive integer greater than 1.
Step S200: based on the product component set, constructing a shower room demand acquisition table, and acquiring shower room product demands of a first user according to the shower room demand acquisition table to obtain a shower room demand table of the user;
specifically, the shower room demand refers to the demands of users on the performance and the size of M product components of a product component set, such as the size, the number of water outlets, the distribution density and the like of a shower head, based on the demands, the product components and the user demands are respectively used as two list attributes of a table to obtain a shower room demand acquisition table, a webpage or an applet is generated according to the shower room demand acquisition table based on the prior art and is sent to the users, and then the shower room demand acquisition table acquires the shower room product demand of a first user to obtain a shower room demand table of the user.
Step S300: carrying out production optimization analysis on the product component set based on the user shower room demand table to obtain a production optimization analysis result, wherein the production optimization analysis result comprises M component production optimizations;
as shown in fig. 2, step S300 of the embodiment of the present invention further includes:
step S310: traversing the product component set to obtain a first product component;
step S320: based on the first product component, obtaining first component demand information according to the user shower room demand list;
step S330: performing production realizability analysis based on the first component demand information to obtain a first component production realizability coefficient;
step S340: calculating the first component production realizability coefficient based on a production optimization analysis function to obtain a first component production optimization, and adding the first component production optimization to the production optimization analysis result.
The step S330 of the embodiment of the present invention further includes:
step S331: based on big data, obtaining a component demand realizability analysis record library;
step S332: taking sample assembly demand information as index leaf nodes, taking sample assembly production realizability coefficients as response leaf nodes, and building a demand realizability analysis tree according to an assembly demand realizability analysis record library;
step S333: inputting the first component demand information into the demand realizability analysis tree, and obtaining the first component production realizability coefficient.
Specifically, the product component set is traversed to obtain a first product component, the first product component generally refers to any component in the product component set, such as a shower head, a high-pressure pipe, a water heater, glass and the like, and based on the first product component, demand matching is performed in the user shower room demand table to obtain first component demand information, such as the size of the water heater and the like.
Further, based on the first component demand information, performing production availability analysis to obtain a first component production availability coefficient, where the first component production availability coefficient characterizes the degree to which the first component demand information can be achieved, and the specific process is as follows:
based on big data, obtain the component demand and can realize degree analysis record storehouse, contain a plurality of sample subassembly demand information and a plurality of sample subassembly that correspond in the component demand can realize degree coefficient of production in the analysis record storehouse, for example the water heater volume of user's demand is 6 liters, based on prior art analysis, can be totally the water heater volume be 6 liters demand, its sample piece production can realize degree coefficient is 100%, if the water heater volume of user's demand is 20 liters, the case of producing 20 liters of water heater is fewer in the prior art, its sample piece production can realize degree coefficient is 50%, specifically can be according to actual conditions by the person skilled in the art, and combine historical experience to set for. Further, sample component demand information is taken as index leaf nodes, sample component production realizability coefficients are taken as response leaf nodes, a demand realizability analysis tree is built according to the component demand realizability analysis record library, in a simple way, a plurality of sample component demand information in the component demand realizability analysis record library is taken as a first node, classification is carried out downwards for a plurality of times until each lowest layer of classification result only comprises one sample component demand information, the classification is stopped, each classification result is taken as the index leaf nodes, and a plurality of corresponding sample component production realizability coefficients are mapped onto the classification result to be taken as response leaf nodes, so that the demand realizability analysis tree is built. And further inputting the first component demand information into the demand realizability analysis tree, and acquiring a sample component production realizability coefficient corresponding to the sample component demand information identical to the first component demand information as the first component production realizability coefficient. Therefore, the realizability analysis of the shower room component is realized, and a data base is provided for the subsequent process optimization.
Further, calculating the first component production availability coefficient based on a production optimization resolution function to obtain a first component production optimization, wherein the production optimization resolution function is as follows:
wherein opt represents the production optimization degree of the first component, R represents the production realizability coefficient of the first component, R 0 Characterizing the achievable degree constraint value of component production can be set by self, namely, in popular terms, the achievable degree constraint value range of component productionAnd the production process of the shower room product component is optimized in the enclosure, and the process is not required to be optimized again in the range of the achievable degree constraint value of the component production.
And finally, adding the first component production optimization degree to the production optimization degree analysis result, acquiring component production optimization degrees corresponding to other components of the product component set by adopting the same method, and adding the component production optimization degrees to the production optimization degree analysis result, so that analysis of the production optimization degree is realized, and support is provided for the subsequent optimization of the shower room product production process.
Step S400: judging whether the production optimization analysis result meets the preset production optimization or not;
step S500: when the production optimization analysis result meets the preset production optimization, obtaining a component production optimization instruction, wherein the component production optimization instruction has a shower room optimization component identifier;
specifically, the preset production optimization degree is set firstly, and the preset production optimization degree is set by a person skilled in the art in combination with the actual situation, so that whether the production optimization degree analysis result meets the preset production optimization degree is judged, that is, only when the production optimization degree analysis result meets the preset production optimization degree, the process optimization of the shower room product is of more practical significance, for example, the assembly production optimization degree displayed by the production optimization degree analysis result is too small, the effect which can be achieved by the process optimization is not obvious, and the meaning of the process optimization is not great. When the production optimization analysis result meets the preset production optimization, a component production optimization instruction is obtained, wherein the component production optimization instruction is an instruction for controlling and executing production process optimization, and the component production optimization instruction has a shower room optimization component identifier, that is, all components in a product component set need to be judged in terms of the production optimization analysis result, and further the components capable of carrying out production process optimization are determined to be marked, so that the subsequent process optimization is facilitated.
Step S600: constructing a component production optimization space based on the component production optimization instruction;
the step S600 of the embodiment of the present invention further includes:
step S610: obtaining an assembly optimization requirement based on the user shower room requirement table and the shower room optimization assembly identifier;
step S620: determining a component optimization production index set based on the component optimization requirements;
step S630: acquiring an index range based on the component optimized production index set to obtain a component optimized production index range set;
step S640: traversing the assembly optimization production index range set to perform multiple random values to obtain an assembly optimization production index particle set;
step S650: and generating the component production optimization space according to the component optimization production index particle set.
Specifically, based on the user shower room demand list and the shower room optimization component identification, component optimization requirements are obtained, wherein the component optimization requirements comprise components needing to be optimized and corresponding user shower room demands. And further determining a component optimized production index set based on the component optimized requirement, wherein the component optimized production index set comprises any one of the optimization indexes corresponding to the components to be optimized, such as the technological parameters to be adjusted, such as the size, the shape, the hardness and the like of the components to be optimized, such as the indexes of the die size, the calcination temperature and the like when the components are produced. And acquiring an index range based on the component optimized production index set to obtain the component optimized production index range set, namely determining the numerical range corresponding to each technological parameter colloquially. And further traversing the assembly optimization production index range set for carrying out random value taking for a plurality of times to obtain a plurality of groups of different assembly optimization production indexes to form the assembly optimization production index particle set, wherein the number of the assembly optimization production indexes in the assembly optimization production index particle set cannot be too small, otherwise, the process optimization result cannot reach the optimal effect, therefore, a data volume threshold can be set, and after the data volume in the assembly optimization production index particle set reaches the data volume threshold, the random value taking in the assembly optimization production index range set is stopped. And the component production optimization space is constructed by optimizing the production index particle group of the component, so that technical support is provided for the production process optimization of the shower room product, the performance of the shower room product is improved, and the fitting degree of the product performance and the user requirement is ensured.
Step S700: and carrying out component production optimization analysis according to the component production optimization space based on the user shower room demand list and the shower room optimization component identifier to obtain a shower room component production optimization decision, and carrying out optimization of a shower room product production process according to the shower room component production optimization decision.
As shown in fig. 3, step S700 of the embodiment of the present invention further includes:
step S710: obtaining P assembly optimization production particles based on the assembly production optimization space, wherein P is a positive integer greater than 1;
step S720: traversing the P assembly optimization production particles to perform fitness analysis based on the assembly optimization requirements to obtain P particle fitness;
step S730: based on the P particle fitness, optimizing production particles according to the P components, and obtaining a plurality of winning component optimized production particles meeting preset particle fitness;
step S740: and screening the optimized production particles of the plurality of winning components based on preset cost constraint to obtain the optimized production decision of the shower room components.
The step S720 of the embodiment of the present invention further includes:
step S721: building a particle fitness analysis model, wherein the particle fitness analysis model comprises multidimensional particle fitness analysis indexes, and the multidimensional particle fitness analysis indexes comprise predicted production cost and predicted production demand matching degree;
step S722: obtaining P particle fitness analysis source data based on the assembly optimization requirements and the P assembly optimization production particles;
step S723: inputting the P particle fitness analysis source data into the particle fitness analysis model to obtain P particle fitness analysis results;
step S724: and traversing the P particle fitness analysis results to perform weighted calculation based on preset fitness analysis weighting characteristics to obtain the P particle fitness.
Specifically, P component optimization production particles are obtained based on the component production optimization space, wherein P is a positive integer greater than 1, and P characterizes the number of component optimization production particles in the component production optimization space, and each component optimization production particle comprises a plurality of component production optimization index parameters. And traversing the P assembly optimization production particles to perform fitness analysis based on the assembly optimization requirements to obtain P particle fitness, namely, simply, assuming that the P assembly optimization production particles are used for optimizing an assembly production process, and obtaining the performance of the optimized assembly as the particle fitness. And further optimizing production particles according to the P components based on the P particle fitness, and obtaining a plurality of winning component optimized production particles meeting the preset particle fitness, wherein the preset particle fitness is set by a person skilled in the art according to actual conditions. Further, the plurality of winning components are screened based on preset cost constraints, in short, the cost required by the plurality of winning components to optimize production particles is calculated, and the winning components with the minimum cost are obtained to be used as the shower room component production optimization decision. Therefore, the optimization of the production process is realized, and the effect of improving the fit degree of the product performance of the shower room and the requirements of users is achieved.
Specifically, based on the component optimization requirement, traversing the P component optimization production particles to perform fitness analysis, and obtaining P particle fitness according to the following process: the method comprises the steps of building a particle fitness analysis model, wherein the particle fitness analysis model is a neural network model in machine learning, the particle fitness analysis model comprises multidimensional particle fitness analysis indexes, the multidimensional particle fitness analysis indexes comprise prediction production cost and prediction production demand matching degree, the prediction production cost is the cost corresponding to assembly optimization production particles, the prediction production demand matching degree is determined according to actual conditions, the optimization of assembly production processes is carried out on the P assembly optimization production particles, and then the similarity degree of the optimized assembly performance and assembly optimization requirements is simply obtained by respectively carrying out fitness analysis from two dimensions, specifically, training and testing can be carried out on the particle fitness analysis model based on training data corresponding to two indexes respectively in the prior art, so that the particle fitness analysis model meeting the requirements is obtained, the input of the particle fitness analysis model is particle fitness analysis source data, and the output is particle fitness analysis result. And obtaining P particle fitness analysis source data based on the assembly optimization requirements and the P assembly optimization production particles, wherein each particle fitness analysis source data comprises the assembly optimization requirements and one random assembly optimization production particle. Inputting the P particle fitness analysis source data into the particle fitness analysis model to obtain P particle fitness analysis results, wherein each particle fitness analysis result comprises the fitness of two indexes corresponding to the predicted production cost fitness and the predicted production requirement matching degree. And further traversing the P particle fitness analysis results based on preset fitness analysis weighting characteristics, and performing weighting calculation to obtain the P particle fitness, wherein the preset fitness analysis weighting characteristics refer to weight distribution characteristics of two indexes of the predicted production cost and the predicted production demand matching degree, and can be determined according to actual conditions, if the production cost is emphasized more, the weight coefficient of the predicted production cost is set to be larger, if the production demand matching degree is emphasized more, the weight coefficient of the predicted production demand matching degree is set to be larger, and can also be set to be 0.5, and the weight coefficient is set by a person skilled in the art. And finally, based on the set preset fitness analysis weighting characteristics, respectively carrying out weighting calculation on the fitness corresponding to each of the two indexes in the P particle fitness analysis results, and taking the weighting calculation result as the P particle fitness. Therefore, the adaptability of the assembly to the production particles is analyzed, and the process optimization effect is improved.
Based on the analysis, the invention provides an optimization method of a shower room product production process, in the embodiment, based on big data, a product component set of the shower room product is obtained, a shower room demand acquisition table is constructed, the shower room product demand of a first user is acquired according to the shower room demand acquisition table, a user shower room demand table is obtained, production optimization analysis is carried out on the product component set, a production optimization analysis result is obtained, whether the production optimization analysis result meets the preset production optimization degree is judged, when the production optimization analysis result meets the preset production optimization degree, a component production optimization instruction is obtained, a component production optimization space is constructed based on the component production optimization instruction, component production optimization analysis is carried out, a shower room component production optimization decision is obtained, and the shower room product production process is optimized according to the shower room component production optimization decision, so that the optimization of the shower room product production process is realized, and the technical effects of improving the compliance of the shower room product performance and the user demand and simultaneously reducing the production cost are achieved.
Example two
Based on the same inventive concept as the optimization method of the shower room product production process in the foregoing embodiment, as shown in fig. 4, the present invention further provides an optimization system of the shower room product production process, where the system includes:
the product component set acquisition module 11 is used for acquiring a product component set of a shower room product based on big data, wherein the product component set comprises M product components, and M is a positive integer greater than 1;
the product demand acquisition module 12 is used for constructing a shower room demand acquisition table based on the product component set, acquiring the shower room product demand of a first user according to the shower room demand acquisition table, and obtaining a shower room demand table of the user;
the production optimization analysis module 13 is configured to perform production optimization analysis on the product component set based on the user shower room demand table, so as to obtain a production optimization analysis result, where the production optimization analysis result includes M component production optimizations;
the analysis result judging module 14 is configured to judge whether the analysis result of the production optimization degree meets a preset production optimization degree or not;
the component production optimization instruction obtaining module 15, where the component production optimization instruction obtaining module 15 is configured to obtain a component production optimization instruction when the production optimization resolution result meets the preset production optimization, and the component production optimization instruction has a shower room optimization component identifier;
an optimization space construction module 16, wherein the optimization space construction module 16 is used for constructing a component production optimization space based on the component production optimization instruction;
the production optimization analysis module 17 is used for carrying out component production optimization analysis according to the component production optimization space based on the user shower room demand list and the shower room optimization component identification, obtaining shower room component production optimization decisions, and carrying out optimization of shower room product production process according to the shower room component production optimization decisions.
Further, the production optimization resolution module 13 is further configured to:
traversing the product component set to obtain a first product component;
based on the first product component, obtaining first component demand information according to the user shower room demand list;
performing production realizability analysis based on the first component demand information to obtain a first component production realizability coefficient;
calculating the first component production realizability coefficient based on a production optimization analysis function to obtain a first component production optimization, and adding the first component production optimization to the production optimization analysis result.
Further, the production optimization resolution module 13 is further configured to:
based on big data, obtaining a component demand realizability analysis record library;
taking sample assembly demand information as index leaf nodes, taking sample assembly production realizability coefficients as response leaf nodes, and building a demand realizability analysis tree according to an assembly demand realizability analysis record library;
inputting the first component demand information into the demand realizability analysis tree, and obtaining the first component production realizability coefficient.
Further, the production optimization resolution module 13 further includes:
the production optimization resolution function is as follows:
wherein opt represents the production optimization degree of the first component, R represents the production realizability coefficient of the first component, R 0 Characterizing component production realizability constraint values.
Further, the optimization space construction module 16 is further configured to:
obtaining an assembly optimization requirement based on the user shower room requirement table and the shower room optimization assembly identifier;
determining a component optimization production index set based on the component optimization requirements;
acquiring an index range based on the component optimized production index set to obtain a component optimized production index range set;
traversing the assembly optimization production index range set to perform multiple random values to obtain an assembly optimization production index particle set;
and generating the component production optimization space according to the component optimization production index particle set.
Further, the production optimization analysis module 17 is further configured to:
obtaining P assembly optimization production particles based on the assembly production optimization space, wherein P is a positive integer greater than 1;
traversing the P assembly optimization production particles to perform fitness analysis based on the assembly optimization requirements to obtain P particle fitness;
based on the P particle fitness, optimizing production particles according to the P components, and obtaining a plurality of winning component optimized production particles meeting preset particle fitness;
and screening the optimized production particles of the plurality of winning components based on preset cost constraint to obtain the optimized production decision of the shower room components.
Further, the production optimization analysis module 17 is further configured to:
building a particle fitness analysis model, wherein the particle fitness analysis model comprises multidimensional particle fitness analysis indexes, and the multidimensional particle fitness analysis indexes comprise predicted production cost and predicted production demand matching degree;
obtaining P particle fitness analysis source data based on the assembly optimization requirements and the P assembly optimization production particles;
inputting the P particle fitness analysis source data into the particle fitness analysis model to obtain P particle fitness analysis results;
and traversing the P particle fitness analysis results to perform weighted calculation based on preset fitness analysis weighting characteristics to obtain the P particle fitness.
The specific example of the optimization method of the production process of the shower room product in the first embodiment is also applicable to the optimization system of the production process of the shower room product in the present embodiment, and the optimization system of the production process of the shower room product in the present embodiment is clearly known to those skilled in the art from the foregoing detailed description of the optimization method of the production process of the shower room product, so that the details thereof will not be described herein for brevity.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (7)
1. A method for optimizing a shower room product manufacturing process, the method comprising:
based on big data, obtaining a product component set of a shower room product, wherein the product component set comprises M product components, and M is a positive integer greater than 1;
based on the product component set, constructing a shower room demand acquisition table, and acquiring shower room product demands of a first user according to the shower room demand acquisition table to obtain a shower room demand table of the user;
carrying out production optimization analysis on the product component set based on the user shower room demand table to obtain a production optimization analysis result, wherein the production optimization analysis result comprises M component production optimizations;
judging whether the production optimization analysis result meets the preset production optimization or not;
when the production optimization analysis result meets the preset production optimization, obtaining a component production optimization instruction, wherein the component production optimization instruction has a shower room optimization component identifier;
constructing a component production optimization space based on the component production optimization instruction;
based on the user shower room demand list and the shower room optimizing component identification, carrying out component production optimizing analysis according to the component production optimizing space to obtain a shower room component production optimizing decision, and carrying out optimization of a shower room product production process according to the shower room component production optimizing decision;
the method for analyzing the production optimization degree of the product assembly set based on the user shower room demand list, obtaining a production optimization degree analysis result, comprises the following steps:
traversing the product component set to obtain a first product component;
based on the first product component, obtaining first component demand information according to the user shower room demand list;
performing production realizability analysis based on the first component demand information to obtain a first component production realizability coefficient;
calculating the first component production realizability coefficient based on a production optimization analysis function to obtain a first component production optimization, and adding the first component production optimization to the production optimization analysis result.
2. The method of claim 1, wherein performing a production availability analysis based on the first component demand information to obtain a first component production availability factor comprises:
based on big data, obtaining a component demand realizability analysis record library;
taking sample assembly demand information as index leaf nodes, taking sample assembly production realizability coefficients as response leaf nodes, and building a demand realizability analysis tree according to an assembly demand realizability analysis record library;
inputting the first component demand information into the demand realizability analysis tree, and obtaining the first component production realizability coefficient.
3. The method of claim 1, wherein the production optimization resolution function is:
wherein opt represents the production optimization degree of the first component, R represents the production realizability coefficient of the first component, R 0 Characterizing component production realizability constraint values.
4. The method of claim 1, wherein constructing a component production optimization space based on the component production optimization instructions comprises:
obtaining an assembly optimization requirement based on the user shower room requirement table and the shower room optimization assembly identifier;
determining a component optimization production index set based on the component optimization requirements;
acquiring an index range based on the component optimized production index set to obtain a component optimized production index range set;
traversing the assembly optimization production index range set to perform multiple random values to obtain an assembly optimization production index particle set;
and generating the component production optimization space according to the component optimization production index particle set.
5. The method of claim 4, wherein performing component production optimization analysis from the component production optimization space based on the user shower room demand list and the shower room optimization component identification comprises:
obtaining P assembly optimization production particles based on the assembly production optimization space, wherein P is a positive integer greater than 1;
traversing the P assembly optimization production particles to perform fitness analysis based on the assembly optimization requirements to obtain P particle fitness;
based on the P particle fitness, optimizing production particles according to the P components, and obtaining a plurality of winning component optimized production particles meeting preset particle fitness;
and screening the optimized production particles of the plurality of winning components based on preset cost constraint to obtain the optimized production decision of the shower room components.
6. The method of claim 5, wherein traversing the P component optimized production particles for fitness analysis based on the component optimization requirements, obtaining P particle fitness comprises:
building a particle fitness analysis model, wherein the particle fitness analysis model comprises multidimensional particle fitness analysis indexes, and the multidimensional particle fitness analysis indexes comprise predicted production cost and predicted production demand matching degree;
obtaining P particle fitness analysis source data based on the assembly optimization requirements and the P assembly optimization production particles;
inputting the P particle fitness analysis source data into the particle fitness analysis model to obtain P particle fitness analysis results;
and traversing the P particle fitness analysis results to perform weighted calculation based on preset fitness analysis weighting characteristics to obtain the P particle fitness.
7. An optimization system for a shower room product manufacturing process, characterized by performing an optimization method of a shower room product manufacturing process as claimed in claims 1-6, said system comprising:
the system comprises a product component set acquisition module, a product component set acquisition module and a control module, wherein the product component set acquisition module is used for acquiring a product component set of a shower room product based on big data, the product component set comprises M product components, and M is a positive integer greater than 1;
the product demand acquisition module is used for constructing a shower room demand acquisition table based on the product component set, acquiring the shower room product demand of a first user according to the shower room demand acquisition table, and acquiring a shower room demand table of the user;
the production optimization analysis module is used for carrying out production optimization analysis on the product component set based on the user shower room demand table to obtain a production optimization analysis result, wherein the production optimization analysis result comprises M component production optimizations;
the analysis result judging module is used for judging whether the production optimization analysis result meets the preset production optimization or not;
the component production optimization instruction acquisition module is used for acquiring a component production optimization instruction when the production optimization analysis result meets the preset production optimization, and the component production optimization instruction is provided with a shower room optimization component identifier;
the optimization space construction module is used for constructing a component production optimization space based on the component production optimization instruction;
the production optimization analysis module is used for carrying out component production optimization analysis according to the component production optimization space based on the user shower room demand table and the shower room optimization component identification to obtain a shower room component production optimization decision, and carrying out optimization of a shower room product production process according to the shower room component production optimization decision;
the production optimization resolution module is further configured to:
traversing the product component set to obtain a first product component;
based on the first product component, obtaining first component demand information according to the user shower room demand list;
performing production realizability analysis based on the first component demand information to obtain a first component production realizability coefficient;
calculating the first component production realizability coefficient based on a production optimization analysis function to obtain a first component production optimization, and adding the first component production optimization to the production optimization analysis result.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109102161A (en) * | 2018-07-19 | 2018-12-28 | 青岛萨纳斯智能科技股份有限公司 | A kind of wisdom production and manufacturing management method |
| CN114529204A (en) * | 2022-02-22 | 2022-05-24 | 刘昌先 | Modularized production process control and management method and system |
| CN114819577A (en) * | 2022-04-18 | 2022-07-29 | 杭州昌邦科技有限公司 | Production planning and scheduling integrated optimization method facing uncertainty of market demand |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109102161A (en) * | 2018-07-19 | 2018-12-28 | 青岛萨纳斯智能科技股份有限公司 | A kind of wisdom production and manufacturing management method |
| CN114529204A (en) * | 2022-02-22 | 2022-05-24 | 刘昌先 | Modularized production process control and management method and system |
| CN114819577A (en) * | 2022-04-18 | 2022-07-29 | 杭州昌邦科技有限公司 | Production planning and scheduling integrated optimization method facing uncertainty of market demand |
Non-Patent Citations (1)
| Title |
|---|
| 基于组织-性能预测的集装箱热轧板工艺优化;贾涛;胡恒法;曹光明;刘振宇;王国栋;;钢铁(11);全文 * |
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