模具协同制造执行系统中的工序调度研究
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摘要
模具工业是国民经济的重要组成部分,模具制造业的发展水平在一定程度上代表国家制造业的水平。协同制造作为一种先进的制造理念,能够将模具制造企业的相关企业和单元整合起来,构成模具扩展企业(EE),协同完成模具制造业务流程,进而提高模具制造企业的竞争力。本文以注塑模具为研究对象,结合注塑模具制造的特点,分析了在模具制造中引入协同制造理念的必要性,构建了基于SOA(Service-Oriented Architecture,面向服务的体系结构)的模具协同制造执行系统(c-MES)框架,研究了该框架下的模具制造工序调度相关问题。
模具扩展企业具有地域分散、合作紧密、信息交流频繁等特点,需要有一个基于Web、协同高效、智能可靠的制造管理系统。提出了基于SOA的模具c-MES模型。作为分布式集成模式,SOA具有松耦合、可重用、粗粒度、平台无关性等优点,能够满足模具扩展企业信息集成的需要。分析了Web服务的技术特点,讨论了Web服务对实现SOA理念的必要性和可行性。对模具c-MES模型各服务模块的功能给出了详细的描述,研究了各服务模块间的交互调用机制。该模型的应用能够为模具扩展企业中各企业带来更大的绩效提升。
在模具制造过程中合理地对模具工序进行优化调度,对提高生产效率、缩短制造周期具有重要的意义。模具制造工序之间大量存在的各种约束关系,可归纳为先后顺次序约束和组合约束。本文给出了基于关系数据库的工序约束的描述方法。一套模具的不同工件、一个工件的不同工序的制造都可能在扩展企业内的不同企业间进行,此时的调度必须考虑企业间的工件运输时间。本文建立了模具扩展企业间的运输时间参数数据库,并以此为依据,在染色体解码时计算相应工序的作业时间参数。
遗传算法是一种通用的进化算法,论文将结合模具制造的特点,将遗传算法与启发式算法相结合,对模具工序调度进行优化计算。对基于工序的编码和基于工件的编码设计了相应的种群初始化、选择、交叉、变异等遗传算子,同时对算子中的相关参数进行了研究。
采用基于工序编码的遗传算法进行调度计算时,在种群初始化、交叉和变异操作的过程中,不可避免地要生成无效编码。因此,在解码之前,需要对中间过程生成的编码的工序约束进行相应的预调整,算例的计算结果验证了所提出的预调整算法的正确性。制定调度计划需要得到有关制造资源的可利用时间参数,为了便于研究,调度计划的数学计算模型需要对一些参数进行理想化处理。传统的调度计算模型通常假设时间缓冲区是连续的并且长度为无限长。然而,过于理想的计算模型使调度算法的结果并不符合模具的生产实际。本文针对模具制造的非连续时间作业问题给出了相应的解码算法,该算法的调度结果更符合模具制造的实际情况。设计了典型的模具制造验证案例,通过验证,本系统能够得出满意的、符合生产实际的调度方案。
建立了基于SOA的模具c-MES的原型系统,实现了模具工序调度服务模块及相关数据库的功能。本系统具有粗粒度、松耦合、跨平台、基于Web等特性,符合模具协同制造的要求。
Mold industry is an important part of national economics, and the development level of mold manufacturing represents the level of national manufacturing at some degree. As an advanced manufacturing mode, Collaborative Manufacturing (CM) can combine the various mold ralative enterprises and units to a mold Extended Enterprise (EE or E2), and furthermore improve the competitive power of the mold enterprise. The injection mold is the research object in this dissertation. The characteristics of mold manufacturing are studied. The necessity of the importing CM mode to mold manufacturing is analyzed. The mold collaborative manufacturing execution system (c-MES) model based on SOA (Service-Oriented Architecture) is built. The operation scheduling ralatived problem of the mold manufacturing is studied.
Mold EE has the following characteristics: distributed in locality, tight cooperation and frequent information exchange. It needs a Web based, collaborative, high efficient, intelligent and reliable manufacturing management system. The solution is the mold c-MES based on SOA. As a distributed integrated architecture, the SOA has many advantages, such as loose coupling, reusable, coarse-grained, platform-independent, and so on. SOA can meet the needing of information integration for mold EE. The feature of Web Service platform is analyzed. The necessity and feasibility of importing Web Service to mold c-MES are discussed. Every service module’s function of the mold c-MES is described in detail, including the functions it supplies and the mechanism of information interaction among them. The feasibility of mold c-MES model is validated by a real mold manufacturing case. The impletation of this solution can bring more performance increasing to mold EE.
It is important to perform an optimized scheduling on mold operations reasonably when manufacturing them to improve the manufacturing efficiency and shorten the manufacturing period. There are many various constraints among the mold manufacturing operations. They can be classified to two kinds: sequence constraint and combination constraint. The expression method based on relational database is designed. The different workpieces in one mold and the different operations in one workpiece can be made in different places among mold EE. So, the workpiece’s transportation time must be considered. The transportation time database is designed. It can be queried when decoding the chromosome for despatching the job time parameter.
GA is a universal evolutionary algorithm. With the chrasteristics of mold manufacturing considered, the hybrid algorithm of GA and heuristic algorithm is adopted to optimize the mold operation scheduling. The genetic arithmetic operators for operation based representation and workpiece based representation are designed, including the population initialization, reproduction, crossover and mutation. The relative parameters in the arithmetic operators are studied.
When the operation-based chromosome representation is adoped in GA for mold operation scheduling, the invalid chromosome will be generated unavoidably during the computing period of population initialization, reproduction, crossover and mutation of chromosome. So, an adjustment algorithm is proposed to ensure the validity of chromosome before decoding. The feasibility of the algorithm is validated by computing cases. We should get the available time parameters of the machine resource before making the scheduling plan. In order to compute conveniently, the GA mathematics model should be idealized in some extent. Traditional scheduling model supposed that the available time buffer is continuous and has no length limitation. However, this over idealized supposition brings the result out of accord with mold production practice. The decoding algorithm is proposed for various job time properties, and it can bring the computing result in accord with mold production practice much more. The solution is validated by a typical mold manufacturing case, and it can carry out the satisfied scheduling plan which meets the mold production practice.
The mold c-MES prototype system based on SOA is built, and the mold operation scheduling service module and the relative database are implemented. Mold c-MES is coarse-grained, loose coupling, platform-independent, Web based, and it can support the mold CM perfectly.
模具扩展企业具有地域分散、合作紧密、信息交流频繁等特点,需要有一个基于Web、协同高效、智能可靠的制造管理系统。提出了基于SOA的模具c-MES模型。作为分布式集成模式,SOA具有松耦合、可重用、粗粒度、平台无关性等优点,能够满足模具扩展企业信息集成的需要。分析了Web服务的技术特点,讨论了Web服务对实现SOA理念的必要性和可行性。对模具c-MES模型各服务模块的功能给出了详细的描述,研究了各服务模块间的交互调用机制。该模型的应用能够为模具扩展企业中各企业带来更大的绩效提升。
在模具制造过程中合理地对模具工序进行优化调度,对提高生产效率、缩短制造周期具有重要的意义。模具制造工序之间大量存在的各种约束关系,可归纳为先后顺次序约束和组合约束。本文给出了基于关系数据库的工序约束的描述方法。一套模具的不同工件、一个工件的不同工序的制造都可能在扩展企业内的不同企业间进行,此时的调度必须考虑企业间的工件运输时间。本文建立了模具扩展企业间的运输时间参数数据库,并以此为依据,在染色体解码时计算相应工序的作业时间参数。
遗传算法是一种通用的进化算法,论文将结合模具制造的特点,将遗传算法与启发式算法相结合,对模具工序调度进行优化计算。对基于工序的编码和基于工件的编码设计了相应的种群初始化、选择、交叉、变异等遗传算子,同时对算子中的相关参数进行了研究。
采用基于工序编码的遗传算法进行调度计算时,在种群初始化、交叉和变异操作的过程中,不可避免地要生成无效编码。因此,在解码之前,需要对中间过程生成的编码的工序约束进行相应的预调整,算例的计算结果验证了所提出的预调整算法的正确性。制定调度计划需要得到有关制造资源的可利用时间参数,为了便于研究,调度计划的数学计算模型需要对一些参数进行理想化处理。传统的调度计算模型通常假设时间缓冲区是连续的并且长度为无限长。然而,过于理想的计算模型使调度算法的结果并不符合模具的生产实际。本文针对模具制造的非连续时间作业问题给出了相应的解码算法,该算法的调度结果更符合模具制造的实际情况。设计了典型的模具制造验证案例,通过验证,本系统能够得出满意的、符合生产实际的调度方案。
建立了基于SOA的模具c-MES的原型系统,实现了模具工序调度服务模块及相关数据库的功能。本系统具有粗粒度、松耦合、跨平台、基于Web等特性,符合模具协同制造的要求。
Mold industry is an important part of national economics, and the development level of mold manufacturing represents the level of national manufacturing at some degree. As an advanced manufacturing mode, Collaborative Manufacturing (CM) can combine the various mold ralative enterprises and units to a mold Extended Enterprise (EE or E2), and furthermore improve the competitive power of the mold enterprise. The injection mold is the research object in this dissertation. The characteristics of mold manufacturing are studied. The necessity of the importing CM mode to mold manufacturing is analyzed. The mold collaborative manufacturing execution system (c-MES) model based on SOA (Service-Oriented Architecture) is built. The operation scheduling ralatived problem of the mold manufacturing is studied.
Mold EE has the following characteristics: distributed in locality, tight cooperation and frequent information exchange. It needs a Web based, collaborative, high efficient, intelligent and reliable manufacturing management system. The solution is the mold c-MES based on SOA. As a distributed integrated architecture, the SOA has many advantages, such as loose coupling, reusable, coarse-grained, platform-independent, and so on. SOA can meet the needing of information integration for mold EE. The feature of Web Service platform is analyzed. The necessity and feasibility of importing Web Service to mold c-MES are discussed. Every service module’s function of the mold c-MES is described in detail, including the functions it supplies and the mechanism of information interaction among them. The feasibility of mold c-MES model is validated by a real mold manufacturing case. The impletation of this solution can bring more performance increasing to mold EE.
It is important to perform an optimized scheduling on mold operations reasonably when manufacturing them to improve the manufacturing efficiency and shorten the manufacturing period. There are many various constraints among the mold manufacturing operations. They can be classified to two kinds: sequence constraint and combination constraint. The expression method based on relational database is designed. The different workpieces in one mold and the different operations in one workpiece can be made in different places among mold EE. So, the workpiece’s transportation time must be considered. The transportation time database is designed. It can be queried when decoding the chromosome for despatching the job time parameter.
GA is a universal evolutionary algorithm. With the chrasteristics of mold manufacturing considered, the hybrid algorithm of GA and heuristic algorithm is adopted to optimize the mold operation scheduling. The genetic arithmetic operators for operation based representation and workpiece based representation are designed, including the population initialization, reproduction, crossover and mutation. The relative parameters in the arithmetic operators are studied.
When the operation-based chromosome representation is adoped in GA for mold operation scheduling, the invalid chromosome will be generated unavoidably during the computing period of population initialization, reproduction, crossover and mutation of chromosome. So, an adjustment algorithm is proposed to ensure the validity of chromosome before decoding. The feasibility of the algorithm is validated by computing cases. We should get the available time parameters of the machine resource before making the scheduling plan. In order to compute conveniently, the GA mathematics model should be idealized in some extent. Traditional scheduling model supposed that the available time buffer is continuous and has no length limitation. However, this over idealized supposition brings the result out of accord with mold production practice. The decoding algorithm is proposed for various job time properties, and it can bring the computing result in accord with mold production practice much more. The solution is validated by a typical mold manufacturing case, and it can carry out the satisfied scheduling plan which meets the mold production practice.
The mold c-MES prototype system based on SOA is built, and the mold operation scheduling service module and the relative database are implemented. Mold c-MES is coarse-grained, loose coupling, platform-independent, Web based, and it can support the mold CM perfectly.
引文
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