CN-115983086-B - Vertical numerical control honing machine module configuration method for carbon emission

CN115983086BCN 115983086 BCN115983086 BCN 115983086BCN-115983086-B

Abstract

The embodiment of the application provides a method for configuring a vertical numerical control honing machine module for carbon emission. The method comprises the steps of obtaining product configuration information of a vertical numerical control honing machine, determining concepts in the product configuration information, relations among the concepts and configuration constraint information, obtaining requirement information of clients, establishing a corresponding optimal configuration model according to the relation among the requirement information, the concepts and the configuration constraint information, determining basic facts and rules in the optimal configuration model according to a preset rule inference machine, screening candidate instance sets meeting the requirements of the clients according to the basic facts and rules, selecting instance sets which are in different types of modules and meet constraint conditions contained in the configuration constraint information from the candidate instance sets, combining the instance sets to obtain a final configuration instance, and solving a process by establishing configuration knowledge modeling-candidate module reasoning-configuration optimization, so that the defect of high subjectivity is overcome, and simultaneous optimization of cost and carbon emission can be realized.

Inventors

DENG LIKANG
WANG KAI
ZHANG ZHILING
LIU XINYING
SUN CHANGZHENG
LIU ZHIGUO
BAI JINHUA
GAO LEI
YANG NAN
ZHOU GUANGHUI
LIU XIAOFENG
ZHANG CHAO
SHAO YUBIN
LI JINTAO
TIAN XIAOJUN
ZHANG XINYU
ZHENG HAOYUE

Assignees

国投生物科技投资有限公司
国投生物能源(铁岭)有限公司

Dates

Publication Date: 20260505
Application Date: 20211014

Claims (8)

1. A method of configuring a vertical type numerical control honing machine module for carbon discharge, the method comprising: obtaining product configuration information of the vertical numerical control honing machine; Determining concepts in the product configuration information, and relation among the concepts and configuration constraint information; Acquiring the demand information of a customer; Establishing a corresponding optimal configuration model according to the requirement information, the concepts, the relations among the concepts and the configuration constraint information, wherein establishing the corresponding optimal configuration model according to the requirement information, the concepts, the relations among the concepts and the configuration constraint information comprises determining an optimal variable and determining an optimal target; determining basic facts and rules in the optimal configuration model according to a preset rule inference engine; screening a candidate instance set conforming to the requirement information according to the basic facts and the rules; Selecting modules in different categories from the candidate instance sets and combining the instance sets meeting the constraint conditions contained in the configuration constraint information to obtain a final configuration instance; Wherein the determining the optimization objective comprises calculating by the formula (3): formula (3); Wherein, the Representing the minimum of the carbon emission amount and the total cost amount, Carbon emissions representing configuration scheme X; representing the total cost of configuration scheme X, the carbon emissions of which are calculated by equation (4): (4); Wherein, the Representing the number of modules contained in a vertical numerical control honing machine product; representing the total number of module examples contained in the i-th module; Representing module instances Carbon emissions of (2); The total cost of configuration X, including the cost and assembly cost of the constituent modules of configuration X, is calculated by equation (5): (5); Wherein, the Representing the total cost of the vertical numerical control honing machine product configuration scheme X; representing the total number of modules contained in the vertical numerical control honing machine product; representing the total number of module instances contained in the i-th type module; Representing module instances Whether the selected value is selected, wherein the selected value is 1, otherwise, the selected value is 0; Representing module instances Cost of (2); Representing the average assembly cost between modules.
2. The method of claim 1, wherein the product configuration information comprises at least one of a configuration scheme, a module, an interface, an attribute, a resource, a constraint, and a customer requirement, and wherein the relationship between concepts comprises at least one of a composition relationship, a subclass relationship, an interface relationship, an attribute relationship, a connection relationship, a consumption and supply relationship of the resource, and a constraint relationship.
3. The method of claim 1, wherein said determining basic facts and rules in the optimal configuration model according to a preset rule inference engine comprises: Converting the instance information in the product configuration into basic facts in rule pushing; Converting the body information in the body into rules in a preset rule base; wherein the ontology information includes at least one of relationships between ontologies, axiom, and semantic web rule language constraints.
4. The method of claim 3, wherein the semantic web rule language constraints comprise at least one of compatibility constraints, interface constraints, resource constraints, and customer requirements constraints.
5. A method according to claim 3, wherein the inference engine comprises an ontology inference engine, the inference method comprising: Acquiring user demand information, and inputting the demand information as a demand instance into a configuration body; constraining the requirement information of the client through the semantic web rule language; and determining a candidate module collection meeting the constraint according to the ontology reasoning engine.
6. The method of claim 1, wherein the determining an optimization variable comprises: Determining boolean variables To optimize variables for representing module instances The Boolean variable is calculated by a formula (1): formula (1); Wherein, the Representing the number of module categories that the product contains, The optimization variable X in the form of a vector representing the total number of module instances of the i-th type module and the product configuration problem is calculated by the formula (2): formula (2); Wherein, the The optimization variables are represented as N module class numbers, and the total number of module instances of the N-th class of modules is N.
7. The method according to claim 1, characterized in that the method comprises: Determining an optimal pareto set through a multi-objective optimization algorithm, and determining an optimal solution in the optimal pareto set; Determining a multi-objective configuration optimization scheme through a non-dominant ranking genetic algorithm; and determining an optimal configuration model according to the optimal solution and the optimal scheme.
8. The method of claim 1, wherein determining the constraint on the product configuration comprises determining at least one of a selection constraint, a necessity constraint, an incompatibility constraint, a price constraint, and a lead time constraint for the product configuration.

Description

Vertical numerical control honing machine module configuration method for carbon emission Technical Field The application relates to the technical field of honing machine module configuration, in particular to a method for configuring a vertical numerical control honing machine module for carbon emission. Background In the technical field of modularized configuration of a numerical control honing machine, at present, the research on modularized configuration design of the numerical control honing machine usually only considers factors such as cost, performance and the like to carry out module combination when carrying out modularized configuration, but ignores carbon emission factors, so that the existing configuration cannot obtain carbon emission information of a module, and cannot effectively support the acquisition of a low-carbon module configuration scheme. Under the condition of lacking carbon emission information support, the designed product may have higher carbon emission and cannot meet the requirement of environmental protection and low carbon. And the configuration solving process becomes complicated, the configuration solving space increases rapidly, and it takes a long time for the prior art to solve such a configuration process. Disclosure of Invention An object of an embodiment of the present application is to provide a module configuration method of a vertical type numerical control honing machine for carbon discharge capable of reducing carbon discharge amount during use of the honing machine. In order to achieve the above object, a first aspect of the present application provides a module configuration method of a vertical type numerical control honing machine for carbon emission, comprising obtaining product configuration information of the vertical type numerical control honing machine; determining concepts in the product configuration information, relations among the concepts and configuration constraint information; Acquiring the demand information of a customer; establishing a corresponding optimal configuration model according to the requirement information, the concepts and the relation among the concepts and the configuration constraint information; Determining basic facts and rules in the optimal configuration model according to a preset rule inference engine; screening a candidate instance set meeting the requirements of clients according to the basic facts and rules; Among the candidate instance sets, the instance sets of modules in different categories and satisfying the constraints contained in the configuration constraint information are selected and combined to obtain the final configuration instance. According to the technical scheme, the product configuration information is firstly obtained, and then the corresponding optimal configuration model is established according to the product configuration information and the client demand information. And determining a candidate instance set according to an inference engine and an inference method, selecting an instance set containing constraint conditions from the candidate instance set, and determining a final configuration instance. The multi-layer configuration solving flow of configuration knowledge modeling, candidate module reasoning and configuration optimization is established, the defect of strong subjectivity is overcome, and therefore simultaneous optimization of cost and carbon emission can be achieved. Additional features and advantages of embodiments of the application will be set forth in the detailed description which follows. Drawings The accompanying drawings are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain, without limitation, the embodiments of the application. In the drawings: Fig. 1A schematically illustrates a flow chart of a vertical type numerical control honing machine module configuration method for carbon discharge according to an embodiment of the application; FIG. 1B schematically illustrates a configuration solution overall framework schematic according to an embodiment of the present application; Fig. 2 schematically shows concepts and their associated relationship diagrams in the field of product configuration according to an embodiment of the application; FIG. 3 schematically illustrates a schematic diagram of a solution system built from a rule inference engine in accordance with an embodiment of the present application; FIG. 4 schematically illustrates a method of specifically encoding a chromosome according to an embodiment of the present application; FIG. 5 schematically shows a schematic of a crossover process of gene exchange sites according to an embodiment of the application; FIG. 6 schematically illustrates a variation process diagram of two variation points according to an embodiment of the p