设计流水线的建模、平衡及调度研究
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摘要
随着全球环境和技术的快速发展，产品研发能力越来越成为企业发展的关键。目前，我国产品研发面临效率低下和成本过高的问题，无法满足产销能力、产品需求和国际技术水平高速发展的迫切需要。设计流水线正是为解决这一问题而提出的制造业产品研发管理方法。
设计流水线借鉴了生产流水线的管理模式，充分发挥流水线标准化、通用化、高效率的优势，同时结合了产品研发过程复杂性（包括设计任务复杂性及其关系的复杂性）、不确定性（可变性和不精确性）、以及模糊性（信息不充分和唯一性）的特点，通过稳定“节拍”的设计任务以及均衡的任务流，有效、快速的进行产品设计。围绕着流水线设计的两个关键科学问题：技术设计和组织设计，以典型汽车产品设计为研究对象，结合复杂网络、模糊理论、智能算法等理论方法来实现设计流水线的建模、分析、平衡和优化调度，并建立了设计流水线的原型系统。全文从以下几个方面展开研究：
（1）类比分析了企业当前设计环境与生产流水线的产生环境，总结了流水线相关技术方法的研究进展，归纳了设计流水线的主要特点及其科学问题，阐述了本文的主要内容和创新点。
（2）在分析与制造过程异同点的基础上，提出了设计流水线的概念模型和定义。对于设计流水线中的关键对象，提出了基于网络（语义网络和复杂网络）的流水线建模方法，通过语义网络建立流水线中的关键对象信息模型和语义关系模型，通过单值和双模式网络模型以及双模式-单模式映射网络建立关系对象的数值信息模型。结合设计过程的特征，提出了设计流水线的构建过程和理论方法。
（3）通过组合或分解设计任务、识别设计过程要素来实现流水线的技术设计。提出了设计任务的层次模型及基于知识单元的分解/组合方法，作为设计过程要素识别的基础，解决了设计过程唯一性与流水线批量使用冲突的问题，保证了设计流水线的通用性。构造设计过程的网络模型，应用复杂网络模体方法进行设计过程要素交互模式识别；基于复杂网络拓扑特性，定义了设计过程要素模式评价指标对任务分解的性能进行评估；并基于评价指标提出设计过程要素的优化方法。
（4）对于流水线的组织设计，提出了基于模糊理论与改进遗传算法的设计流水线平衡问题求解算法。提出了模糊设计结构矩阵的方法来解决设计的不确定性、迭代性的问题，其中采用模糊数表达设计活动的持续时间估计；建立了基于模糊数的长周期设计流水线平衡问题数学模型，并提出了基于改进交叉算子的高效遗传算法进行求解。
（5）对于流水线的实际应用，提出了基于多技能等级、多模式的设计资源优化调度方法。针对设计流水线的关键对象——人具有多技能与主动性等特点，提出了基于双模式网络及社会网络的资源能力计算方法，通过双模式向单模式网络的映射获取人员多能力等级，社会网络则考虑了人员从他人获取自己未知知识的能力。最后，基于资源冲突、多项目并行等约束，建立了流水线使用中的资源优化调度模型，并通过二维粒子群算法实现问题求解。
最后，基于以上所提出的理论方法，围绕某汽车公司研发需求，开发了一个基于B/S与C/S模式结合的原型系统，实现设计流水线的管理理念，并在该公司车身研发项目中得到了实施和应用，进而检验了所提出的设计流水线理论方法的可行性和实用性。
With the rapidly change of global environment and technology development, thecapabilities of R&D (research and development) will be the key factor whether it willsurvive. However, Product development of Chinese industrial company has low efficiencyand high cost, whcih can not meet the rapid development of the production and marketingcapacity, product demand and new technology. Design stream line is born to solve theseproblems.
With the advantage of standardization, generalization, and high efficiency ofstreamlining production, design stream line combined with the complexity, ambiguity anduncertainty of the product development process. Design stream line has the design taskswith Takt time and balancing tasks flow which support effective and rapid product design.Surrounded with the two scientific problem (technology design and organizational design),model, analysis, line balancing and scheduling of design stream line is presented by usingcomplex networks, fuzzy theory and intelligent algorithms. And a prototype system ofdesign stream line for automotile design is built. The paper is mainly focus on thefollowing aspects:
1) The same points of the environment for the production lines which the designprocesses have are analysed. And summarizes the main characteristics and scientific issuesof design stream line are summarized, and main content and innovation of technologyresearch are then described. Furthermore, the related methods of design stream line arereviewed and summarized.
2) With difference of the design processes and manufacturing processes, the keytechnologies and framework of design stream line are presented. The concept modelofdesign stream line and the key objects are defined. Stream line is modeled based onsemantic networks and complex networks. Information models and semantic relationmodels are built based on semantic network models, and bipartite networks and theirprojected networks are modeled for numerical information.
3) Combination and partition of design tasks and recognization of the design-process-element is presented for technical design of stream line. The structure model of designtasks with the combination and decomposition based on knowledge units is the basic ofrecognization of the design-process-element. Network motif is used to recognize the interactive pattern of the design-process-element. Measure indices of the interactivepattern are presented based on the topology of complex networks which is the basic ofdesign-process-element optimization. The design-process-element solves the conflictbetween unique of design tasks and common of stream line.
4) To the organizational design, line balancing based on fuzzy theory is presented fordesign stream line and improved GA is described to solve the problem. Considered theuncertainty, interation and long cycle time of product design, the duration estimationmethod of design tasks is presented integrated with fuzzy numbers and DSM. Amathematical model of line balancing is proposed, and a Genetic Algorithm (GA) isutilized to find the optimum solution.
5) Considered of the high level of design imprecision and employees with multipleskills and different skill levels, a product development projects scheduling problem withmulti-skilled employees and multiple modes is presented. A calculation methodology ofdesigners’ Capacity based on bipartite networks and social networks is presented, whichcombines the designers’ capabilities of know-how and know-who knowledged. Amathematical model of multi projects scheduling problem subject to the precedence andresource constraints is presented, and an extended partical swarm Algorithm is presentedto find the optimum solution.
At last, a prototype system of design stream line for automobile design is built basedon B/S and C/S modes. A case of an automobile design is used to illustrate the problemand proposed method. The results verify the feasibility and effectiveness of this algorithm.
设计流水线借鉴了生产流水线的管理模式，充分发挥流水线标准化、通用化、高效率的优势，同时结合了产品研发过程复杂性（包括设计任务复杂性及其关系的复杂性）、不确定性（可变性和不精确性）、以及模糊性（信息不充分和唯一性）的特点，通过稳定“节拍”的设计任务以及均衡的任务流，有效、快速的进行产品设计。围绕着流水线设计的两个关键科学问题：技术设计和组织设计，以典型汽车产品设计为研究对象，结合复杂网络、模糊理论、智能算法等理论方法来实现设计流水线的建模、分析、平衡和优化调度，并建立了设计流水线的原型系统。全文从以下几个方面展开研究：
（1）类比分析了企业当前设计环境与生产流水线的产生环境，总结了流水线相关技术方法的研究进展，归纳了设计流水线的主要特点及其科学问题，阐述了本文的主要内容和创新点。
（2）在分析与制造过程异同点的基础上，提出了设计流水线的概念模型和定义。对于设计流水线中的关键对象，提出了基于网络（语义网络和复杂网络）的流水线建模方法，通过语义网络建立流水线中的关键对象信息模型和语义关系模型，通过单值和双模式网络模型以及双模式-单模式映射网络建立关系对象的数值信息模型。结合设计过程的特征，提出了设计流水线的构建过程和理论方法。
（3）通过组合或分解设计任务、识别设计过程要素来实现流水线的技术设计。提出了设计任务的层次模型及基于知识单元的分解/组合方法，作为设计过程要素识别的基础，解决了设计过程唯一性与流水线批量使用冲突的问题，保证了设计流水线的通用性。构造设计过程的网络模型，应用复杂网络模体方法进行设计过程要素交互模式识别；基于复杂网络拓扑特性，定义了设计过程要素模式评价指标对任务分解的性能进行评估；并基于评价指标提出设计过程要素的优化方法。
（4）对于流水线的组织设计，提出了基于模糊理论与改进遗传算法的设计流水线平衡问题求解算法。提出了模糊设计结构矩阵的方法来解决设计的不确定性、迭代性的问题，其中采用模糊数表达设计活动的持续时间估计；建立了基于模糊数的长周期设计流水线平衡问题数学模型，并提出了基于改进交叉算子的高效遗传算法进行求解。
（5）对于流水线的实际应用，提出了基于多技能等级、多模式的设计资源优化调度方法。针对设计流水线的关键对象——人具有多技能与主动性等特点，提出了基于双模式网络及社会网络的资源能力计算方法，通过双模式向单模式网络的映射获取人员多能力等级，社会网络则考虑了人员从他人获取自己未知知识的能力。最后，基于资源冲突、多项目并行等约束，建立了流水线使用中的资源优化调度模型，并通过二维粒子群算法实现问题求解。
最后，基于以上所提出的理论方法，围绕某汽车公司研发需求，开发了一个基于B/S与C/S模式结合的原型系统，实现设计流水线的管理理念，并在该公司车身研发项目中得到了实施和应用，进而检验了所提出的设计流水线理论方法的可行性和实用性。
With the rapidly change of global environment and technology development, thecapabilities of R&D (research and development) will be the key factor whether it willsurvive. However, Product development of Chinese industrial company has low efficiencyand high cost, whcih can not meet the rapid development of the production and marketingcapacity, product demand and new technology. Design stream line is born to solve theseproblems.
With the advantage of standardization, generalization, and high efficiency ofstreamlining production, design stream line combined with the complexity, ambiguity anduncertainty of the product development process. Design stream line has the design taskswith Takt time and balancing tasks flow which support effective and rapid product design.Surrounded with the two scientific problem (technology design and organizational design),model, analysis, line balancing and scheduling of design stream line is presented by usingcomplex networks, fuzzy theory and intelligent algorithms. And a prototype system ofdesign stream line for automotile design is built. The paper is mainly focus on thefollowing aspects:
1) The same points of the environment for the production lines which the designprocesses have are analysed. And summarizes the main characteristics and scientific issuesof design stream line are summarized, and main content and innovation of technologyresearch are then described. Furthermore, the related methods of design stream line arereviewed and summarized.
2) With difference of the design processes and manufacturing processes, the keytechnologies and framework of design stream line are presented. The concept modelofdesign stream line and the key objects are defined. Stream line is modeled based onsemantic networks and complex networks. Information models and semantic relationmodels are built based on semantic network models, and bipartite networks and theirprojected networks are modeled for numerical information.
3) Combination and partition of design tasks and recognization of the design-process-element is presented for technical design of stream line. The structure model of designtasks with the combination and decomposition based on knowledge units is the basic ofrecognization of the design-process-element. Network motif is used to recognize the interactive pattern of the design-process-element. Measure indices of the interactivepattern are presented based on the topology of complex networks which is the basic ofdesign-process-element optimization. The design-process-element solves the conflictbetween unique of design tasks and common of stream line.
4) To the organizational design, line balancing based on fuzzy theory is presented fordesign stream line and improved GA is described to solve the problem. Considered theuncertainty, interation and long cycle time of product design, the duration estimationmethod of design tasks is presented integrated with fuzzy numbers and DSM. Amathematical model of line balancing is proposed, and a Genetic Algorithm (GA) isutilized to find the optimum solution.
5) Considered of the high level of design imprecision and employees with multipleskills and different skill levels, a product development projects scheduling problem withmulti-skilled employees and multiple modes is presented. A calculation methodology ofdesigners’ Capacity based on bipartite networks and social networks is presented, whichcombines the designers’ capabilities of know-how and know-who knowledged. Amathematical model of multi projects scheduling problem subject to the precedence andresource constraints is presented, and an extended partical swarm Algorithm is presentedto find the optimum solution.
At last, a prototype system of design stream line for automobile design is built basedon B/S and C/S modes. A case of an automobile design is used to illustrate the problemand proposed method. The results verify the feasibility and effectiveness of this algorithm.
引文
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