PCB assembly scheduling through kit concept

This paper presents the design and test of a new scheduling environment dedicated to the off-line scheduling of PCB assembly shops. The main idea introduced is the employment of the 'kit concept' as a scheduling tool, as opposed to the traditional batch scheduling. In the kit approach, the basic PCB aggregations are kits composed of different PCBs matching finished products requirements, instead of homogeneous batches of identical boards. By introducing the kit approach, PCB assembly schedule is intended to be focused more towards the assembly of final products than towards the internal PCB assembly shop constraints and requirements. A simulation model and data from a real assembly system are used to compare the kit approach with traditional batch processing. Experimental results show that the proposed kit approach jointly achieves remarkable improvements in the effectiveness and efficiency performances of the assembly system, as compared to the batch approach. However, it is determined also that these advantages can only be achieved if a sufficiently advanced scheduling system is used.     

Fuzzy multi-attribute decision-making for evaluating manufacturing flexibility

Evaluation of manufacturing flexibility in operations management is important to determine the competitiveness of manufacturing system, and is being increasing discussed in the literature on manufacturing system. The objective of this research is to develop a multi-attribute decision-making model based on fuzzy set theory to improving the manufacturing flexibility evaluation process. Since most information available in this stage is not numerical, fuzzy linguistic assessment is used to represent the performance rating of all flexibility metrics under flexibility dimensions and importance grade of all flexibility dimensions. This paper proposes a modified LOWA operator, which uses the maximum entropy weights, and uses it to direct computation on linguistic terms. The developed model evaluates the degree of manufacturing flexibility that can assist decision-makers, when making capital investment decisions and measuring performance, in finding the need for improving manufacturing flexibility, and in determining the dimensions of flexibility as the best directions to improvement. Examples using a case study of leading Taiwan firm in the bicycle industry are used to illustrate the concept developed. In addition, sensitivity analysis can be performed to examine the solution reasonability.     

Multi-objective machine-component grouping in cellular manufacturing: A genetic algorithm

The cellular manufacturing system (CMS) is an important group technology (GT) application. The first step of CMS design is cell formation, generally known as machinecell formation (MCF) or machine-component (MCG). A genetic algorithm (GA) is a robust adaptive optimization method based on principles of natural evolution and is appropriate for the MCG problem, which is an NP complete complex problem. In this study, we propose a GA-based procedure to solve the MCG problem. More specifically, this study aims to minimize (1) total cost, which includes intercell and intracell part transportation costs and machines investment cots; (2) intracell machine loading imbalance; and (3) intercell machine loading imbalance under many realistic considerations. An illustrative example and comparisons demonstrate the effectiveness of this procedure. The proposed procedure is extremely adaptive, flexible, efficient and can be used to solve real MCG problems in factories by providing robust manufacturing cell formation in a short execution time.     

确定多属性群决策协调权的模型和方法

在权重信息不完全的多属性群决策过程中,当决策者给出了各自的关于方案的偏好序关系之后,需要检验是否存在一组能支持所有决策者意见的权重(即协调权).在定义偏好关系"重要度"的基础上,构造了一个{0,1}混合整数线性规划模型,该模型不仅能够判断协调权是否存在,而且可以识别出导致协调权不存在的"最不重要"的偏好序关系.此外还证明当决策者修改这些序关系后,群决策问题一定存在协调权.最后用一个例子说明了该模型的有效性和实用性.     

Line balance analyses for system assembly lines in an electronic plant

This research analysed and optimised the assembly line balance of notebook computer system production lines in a major computer plant. The research developed a mathematical model for balancing assembly lines of a specific notebook computer system. Precedence relationship charts were created to enforce the required sequences and ILOG CPLEX software was used to obtain the optimal solution of the task assignments to the workstations. The new task assignments were simulated to verify the improvement recommendations and predict the potential benefits.The estimated improvements include: (1) 5.9% increase in average daily production; (2) 29% decrease in average daily WIP; (3) 67.9% reduction in cycle time; (4) 16.7% reduction in operator headcount over the whole system assembly area. The contributions of this research include: (1) Establishing line balancing mathematical model suitable for notebook computer factories; (2) Optimising the system assembly lines for the subject company; (3) Transferring the line balance modelling and optimisation techniques for company use.     

Development of an algorithm for the application of Group Technology in the design of Manufacturing Systems

The Group Technology theory identifies and groups similar parts into families and machines into cells, advantages being in the similarity of the parts made in each cell, and designing and manufacturing. The benefits are: simple material flow, cost reduction in material handling, reduction in work in progress, reduction in the cycle time and set-up time, increased manufacturing flexibility, increased quality, and increased job satisfaction. The objective of the work presented in this paper was to develop a Group Technology (GT) algorithm by means of cell analysis for the design of the productive system to batch production, e.g. water heater manufacturing, system manufacturing, lathes manufacturing, etc. The TGIP algorithm allows the definition of technical and economical parameters for the application of Group Technology, also taking into account the demand for the performance of the algoof heating gasrithm. The benefits of the algorithm developed are the focus on solving the case of multiple machines and the assignment of the parts to the groups related to the load of the machines; also it allows the definition of technical and economical parameters to differentiate the machines that do the same operation or even the consideration of the demand for a certain period of time.     

An approach to consensus measurement of linguistic preference relations in multi-attribute group decision making and application

This paper studies the group decision making problem with linguistic preference relations. We first study the consensus measure between the individual preference relations and the collective (group) preference relation by defining the concept of degree of similarity between two linguistic values and two linguistic preference relations. Then we propose a concept of the acceptance consensus threshold value for group decision making with linguistic preference information. We show that the consensus between individual preference relations and the collective (group) preference relation is greater than the weighted similarity degree of a given individual preference relation with respect to other individual preference relations in group decision making with linguistic preference relations. The results will help in the analysis of crucial issues of conflict and agreement among preferences of decision-makers, which affect the consensus of group decision making with linguistic preference relations. Theoretical foundations are then established for the proposed method. Finally, the proposed method is applied to evaluate the degree of consensus of individual overall preference values with respect to the collective overall preference values for multi-attribute group decision making with linguistic information. The main contribution of this paper is twofold. One is to present a new way to measure the consensus between the individual preference relations and the collective (group) preference relation in group decision making with linguistic preference information. Another is to provide an effective approach to evaluating individual overall preference values with respect to the collective overall preference values in multi-attribute group decision making with linguistic information.     

An extension of the Electre I method for group decision-making under a fuzzy environment

Many real-world decision problems involve conflicting systems of criteria, uncertainty and imprecise information. Some also involve a group of decision makers (DMs) where a reduction of different individual preferences on a given set to a single collective preference is required. Multi-criteria decision analysis (MCDA) is a widely used decision methodology that can improve the quality of group multiple criteria decisions by making the process more explicit, rational and efficient. One family of MCDA models uses what is known as “outranking relations” to rank a set of actions. The Electre method and its derivatives are prominent outranking methods in MCDA. In this study, we propose an alternative fuzzy outranking method by extending the Electre I method to take into account the uncertain, imprecise and linguistic assessments provided by a group of DMs. The contribution of this paper is fivefold: (1) we address the gap in the Electre literature for problems involving conflicting systems of criteria, uncertainty and imprecise information; (2) we extend the Electre I method to take into account the uncertain, imprecise and linguistic assessments; (3) we define outranking relations by pairwise comparisons and use decision graphs to determine which action is preferable, incomparable or indifferent in the fuzzy environment; (4) we show that contrary to the TOPSIS rankings, the Electre approach reveals more useful information including the incomparability among the actions; and (5) we provide a numerical example to elucidate the details of the proposed method.     

Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

Hamacher算子在模糊评价中的应用方法

模糊合成算子是模糊评价中数据处理的核心技术。目前模糊合成算子在模糊评价中应用时比较混乱,没有一般方法。原因之一是Zadeh的模糊集理论存在缺陷,另一方面是对算子性质研究挖掘不够。需要研究不同的模糊算子在模糊评价中的使用方法。Hamacher算子是参数算子,含参γ在[1,+∞)时有对参数变量和数据变量的多重单调性,它的清晰域不随参数变化而改变,并且清晰域最小。模糊评价中的数据起到至关重要作用,分析模糊与算子的清晰域,确定数据点与清晰域的从属关系,提出基于清晰域与数据分布的Hamacher算子的应用方法,通过实例验证其合理、有效性。     

高校知识工作者的激励模型及模糊综合评价

知识经济下,高校作为知识传授和创新的桥头堡,如何极大地激励高校知识工作者的创新潜能和科教热情,成为中国高校的一大难题。本文在几种激励理论的基础之上,提出高校知识工作者的激励模型,并对其建立了模糊综合评价模型,为制定高校知识工作者的激励政策提供有用的依据。     

基于熵权的乏燃料公路运输选线模型

由于核电站的特殊性,乏燃料的运输在核电供应体系中占据重要地位.核电站乏燃料具有辐射性,运输过程中对工作人员、沿途公众和环境等可能会产生危害,又属于公路超限货包运输,所以对公路运输线路要求非常高.本文在利用层次分析法构造乏燃料公路运输线路优选系统的综合评价指标体系的基础上,结合熵权和模糊数学理论,构造基于熵权的乏燃料公路运输选线模糊层次分析模型,为确保核电供应链中乏燃料物流的安全、降低其对环境的影响提供决策依据,以达到安全、可靠和经济合理地完成核电站乏燃料运输的目的.     

Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage

Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel‐induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step‐by‐step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN‐based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel‐induced pipeline damage model is proposed to reveal the cause‐effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment.     

经营者模糊需求在激励设计中的精确化研究

经营者报酬设计是一个非常复杂的系统性问题,复杂性表现为:委托人和经营者的需求是多方面的,各种需求与社会制度、文化环境、法律法规、政策、市场、价值观、道德、人格等因素之间存在非线性关系,而且有很多需求,尤其是心理情感方面的需求,是模糊不清的,任何一方要获得完全信息的成本非常高.因此,在现实生活中,委托人和经营者无一不是在人力资本价值无法估计、需求模糊、信息不对称的前提下,根据他们所掌握的有限信息进行协商或讨价还价的.本文从委托人、经营者都有模糊需求出发,利用模糊数刻画他们所有可能的需求,确定各自模糊需求的顺序,根据经营者、委托人模糊集的交集和需求顺序的比较,最终回答模糊环境下经营者激励设计中的解模糊思路和措施.     

Application of the Fuzzy Weighted Average in Strategic Portfolio Management*

We propose a systematic approach that incorporates fuzzy set theory in conjunction with portfolio matrices to assist managers in reaching a better understanding of the overall competitiveness of their business portfolios. Integer linear programming is also accommodated in the proposed integrated approach to help select strategic plans by using the results derived from the previous portfolio analysis and other financial data. The proposed integrated approach is designed from a strategy‐oriented perspective for portfolio management at the corporate level. It has the advantage of dealing with the uncertainty problem of decision makers in doing evaluation, providing a technique that presents the diversity of confidence and optimism levels of decision makers. Furthermore, integer linear programming is used because it offers an effective quantitative method for managers to allocate constrained resources optimally among proposed strategies. An illustration from a real‐world situation demonstrates the integrated approach. Although a particular portfolio matrix model has been adopted in our research, the procedure proposed here can be modified to incorporate other portfolio matrices.     

Optimizing the number of stations in assembly lines under learning for limited production

This paper considers finding the optimal number of stations for an assembly line producing a limited quantity of a new product under learning conditions. This type of production characterizes heavy products (such as airplanes and communication systems) and science-based industries (e.g. laser cutting devices and special equipment for hospitals). These products are manufactured in assembly line fashion in small batches of a few hundred. Since the products are assumed to be totally new to the workers, the learning phenomenon is significant (i.e. task times decrease from cycle to cycle as experience is gained). Therefore, standard balancing methods are no longer applicable. Determining the number of stations has a large effect on the production rate while the actual assignment of tasks to stations helps to fine tune the cycle time. Thus, the number of stations can be regarded as a strategic decision variable . This paper discusses two ways for determining the optimal number of stations, namely as a cost minimization problem and as a profit maximization problem.     

并行工程产品开发过程定量化建模与计划制订

由于现有的一些并行工程定量化模型中修改设计微循环的细节特征描述得还不够充分 ,本文提出了一种新的基于产品 -工艺设计活动对网络的定量化模型来描述并行工程产品开发过程 ,并且给出了产品 -工艺设计活动对平均持续时间与产品或工艺设计活动资源占用率的计算方法 .在此基础上 ,将并行工程产品开发过程的计划制订问题建模成一个有资源约束的项目调度问题 .与其它此类问题不同的是 ,在本文中 ,分配给产品开发项目的各类资源的数量不是事先给定的 ,而是与最优产品开发计划一起获得的 ,所以这是一个资源分配与计划制订的集成优化问题 .本文提出了一种新的基于分枝定界的算法来解决此问题并引入一个启发式规则来提高算法的搜索效率     

日本制造企业新产品开发过程中模糊前端创新的效果分析

本文对日本制造企业新产品开发(NPD)过程中模糊前端(FFE)创新成功的关键因素进行了大样本分析,开发并构建了FFE创新要素与NPD项目绩效之间的因果关系模型.根据513家日本制造企业NPD项目的调查数据,运用AMOS验证因果关系模型,我们得出两个重要结论:在FFE阶段,技术和市场的不确定性减少越多,NPD项目的效率越高;开发前项目初始规划强度越大,开发过程中市场和技术的不确定性就越少.而且相对服务企业而言,制造企业的管理层更容易做出对降低市场不确定性有重大影响的初始规划.