PROMETHEE based sustainable concept selection

Manufacturing organisations started recognising the importance of sustainability concepts: This is due to increasing government regulations and the consciousness of the sustainable products among the customers. In general, the sustainability concepts are classified into economic, environment and social perspectives. The classification of sustainable concept concerning to manufacturing firms can be material oriented, product design oriented and manufacturing process oriented. Sustainable concept selection is a vital problem for the contemporary manufacturing organisations. The selection process includes multiple criteria, therefore a Multi-Criteria Decision Making (MCDM) method namely, PROMETHEE (Preference Ranking Organisational Method for Enrichment Evaluation) is used in the study to select the best sustainable concept considering the criteria from social, economical and natural perspectives. The study revealed that the change of material as the best orientation and it implies that the material should be done at the first stage to achieve sustainability in the case organisation.     

Manufacturing technology policy and deployment of processing innovations

This is a report of a study on the evolution of manufacturing technology policy during the deployment of domestic advanced manufacturing systems in thirty-four plants and two panels of data collection separated by one year. Changing firm environment was significantly correlated with pioneering product introduction business strategy (p<0.05). More importantly, it was found that manufacturing technology policy is significantly (p<0.05) associated with pioneering business strategy. Further, findings indicate that fine-tuning or modest adjustment in this policy (versus doing nothing or drastic change) was significantly (p<0.05) associated with the maximum levels of reported utilization of these new systems in a subsample of second panel, complete data cases (n=21). This curvilinear relationship between the absolute value of changes in technology policy and performance measure did not hold for the percentage of target cycle time achieved nor uptime, although results concerning performance are considered preliminary at the time of this writing. Advertising this processing technology tends to be inversely related to the radicalness of the technology incorporated into the system (p=0.076) during the deployment period tracked thus far. That is, firms installing more radical systems tend to become very cautious about sharing information about the project once installation begins.     

Measurement of loading and operations flexibility in flexible manufacturing systems: An information-theoretic approach

An information-theoretic approach is applied for measuring the flexibility in flexible manufacturing systems (FMSs). The general relation between flexibility and entropy is discussed. The entropy for a Markovian process is obtained and then applied to closed queueing network models of FMSs to discuss loading flexibility which arises from the power to regulate the frequency of the visit of a part to different work stations. The concept of operations entropy as a measure of operations flexibility, which arises from the power to choose the work station and the corresponding operations, is introduced. The operations entropy has been decomposed into entropies within and between operations and entropies within and between groups of operations. This measure has been used to determine the next operation to be performed on a part by using the principle of least reduction of flexibility.The present paper is an improved version of the paper On measurement of flexibility in flexible manufacturing systems: An information-theoretic approach, presented at the II ORSA/TIMS Special Conference on Flexible Manufacturing Systems, held at Ann Arbor in August 1986.     

云制造环境下企业制造资源共享的演化博弈分析

云制造服务平台为在不同时空上获取制造资源提供了一个良好的工作环境,它实现了产品全生命周期的协同制造、管理和创新。在明确云制造环境下企业制造资源共享模式的基础上,构建了考虑两方行为的制造资源共享的演化博弈模型,分别在博弈群体处于均匀混合和非均匀混合两种状态下,找出了模型的均衡点并对其稳定性进行分析。引入系统动力学的方法,建立制造资源共享的演化博弈SD仿真模型,对比分析不同参数变化对演化结果的影响。研究结果表明,企业群体初始共享比例、升级设备成本、信息化改善收益和技术流失风险对博弈双方的策略演化结果具有显著的影响,促进企业联盟中的信息互通与资源共享,须从上述方面着手管理并持续改进。     

On modeling failure and repair times in stochastic models of manufacturing systems using generalized exponential distributions

Failures of machines have a significant effect on the behavior of manufacturing systems. As a result it is important to model this phenomenon. Many queueing models of manufacturing systems do incorporate the unreliability of the machines. Most models assume that the times to failure and the times to repair of each machine are exponentially distributed (or geometrically distributed in the case of discrete-time models). However, exponential distributions do not always accurately represent actual distributions encountered in real manufacturing systems. In this paper, we propose to model failure and repair time distributions bygeneralized exponential (GE) distributions (orgeneralized geometric distributions in the case of a discretetime model). The GE distribution can be used to approximate distributions with any coefficient of variation greater than one. The main contribution of the paper is to show that queueing models in which failure and repair times are represented by GE distributions can be analyzed with the same complexity as if these distributions were exponential. Indeed, we show that failures and repair times represented by GE distributions can (under certain assumptions) be equivalently represented by exponential distributions.This work was performed while the author was visiting the Laboratory for Manufacturing and Productivity, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.     

A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment

The purpose of this paper is to design a new extension of the ELECTRE, known as the elimination and choice translating reality method, for multi-criteria group decision-making problems based on intuitionistic fuzzy sets. This method is widely utilized when a set of alternatives should be identified and evaluated with respect to a set of conflicting criteria by reflecting decision makers’ (DMs’) preferences. However, handling the exact data and numerical measure is difficult to be precisely focused because the DMs’ judgments are often vague in real-life decision problems and applications. A more realistic and practical approach can be to use linguistic variables expressed in intuitionistic fuzzy numbers instead of numerical data to model DMs’ judgments and to describe the inputs in the ELECTRE method. The proposed intuitionsitic fuzzy ELECTRE utilizes the truth-membership function and non-truth-membership function to indicate the degrees of satisfiability and non-satisfiability of each alternative with respect to each criterion and the relative importance of each criterion, respectively. Then, a new discordance intuitionistic index is introduced, which is extended from the concept of the fuzzy distance measure. Outranking relations are defined by pairwise comparisons and a decision graph is depicted to determine which alternative is preferable, incomparable or indifferent in the intuitionistic fuzzy environment. Finally, a comprehensive sensitivity analysis is employed to further study regarding the impact of threshold values on the final evaluation, and a comparative analysis is demonstrated with an application example in flexible manufacturing systems between the proposed ELECTRE method and the existing intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method.     

Competitive diffusion process of repurchased products in knowledgeable manufacturing

This paper presents a diffusion model to explain the competitive diffusion of the repurchased products in knowledgeable manufacturing. The acute market competition accelerates the products’ improvement, which requires that the manufacturing enterprises be highly capable of rapid reaction by means of knowledgeable manufacturing. To forecast the diffusion behavior effectively enables the realization of knowledgeable manufacturing system (KMS) which targets T (time), Q (quality), C (cost), S (service), and E (environment). Various diffusion models have emerged since Bass model was firstly proposed in 1969. A nonlinear model of the repurchased competitive products is proposed on the basis of the product diffusion analysis. By taking the frequently purchased products as example, the stability of the model is examined in light of the qualitative theory of differential equations and proved by the approximate linearization method. As the qualitative analysis reveals, between the two frequently purchased products competing in the same market, one undoubtedly occupies a fixed market share while the other may finally be eliminated from the market. A special case of the problem is that both products are one-time-purchased. With the corresponding model given, the qualitative analysis shows that either of the products occupies a market share, the size of which is determined by the product’s competitive strength and the new product’s time-to-market. A system dynamics model is then established and simulated by vensim. The result is consistent with that of the qualitative analysis.     

Optimal yield improvement in multi-stage manufacturing systems

Multi-stage manufacturing systems producing some non-conforming items still present economic operational problems. A decomposition approach is presented to model multi-stage manufacturing systems with inspection stations. The concept of process improvement as developed is expressed in terms of a step-wise yield improvement path, along which the most profitable improvement stages are identified. It is shown that the model selects an ever increasing set of stations to improve, once the profitability of the best station-candidates reaches a level similar to that of some other station-candidates. The approach also extends the concept of an event (naturally connected to a time frame) by relating it to a dynamic profitability frame. From an operational perspective the findings suggest that a quality improvement project, initially undertaken by a cross-functional team at a multi-stage level, may be continued through concurrent projects, focusing on improving the quality of specific manufacturing stages. The research results may be directly extended to include integrated economic improvement-inspection decisions.     

A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system

This paper develops a mixed-integer programming model to design the cellular manufacturing systems (CMSs) under dynamic environment. In dynamic environment, the product mix and part demand change under a multi-period planning horizon. Thus, the best designed cells for one period may not be efficient for subsequent periods and reconfiguration of cells is required. Reconfiguration may involve adding, removing or relocating machines; it may also involve a change in processing rout of part types from a period to another. The advantages of the proposed model are as follows: considering the batch inter/intra-cell material handling by assuming the sequence of operations, considering alternative process plans for part types, and considering machine replication. The main constraints are maximal cell size and machine time-capacity. The objective is to minimize the sum of the machine constant and variable costs, inter- and intra-cell material handling, and reconfiguration costs. An efficient hybrid meta-heuristic based on mean field annealing (MFA) and simulated annealing (SA) so-called MFA–SA is used to solve the proposed model. In this case, MFA technique is applied to generate a good initial solution for SA. The obtained results show that the quality of the solutions obtained by MFA–SA is better than classical SA, especially for large-sized problems.     

Modeling and nonlinear control of a flexible-link manipulator

The problem of modeling and controlling the tip position of a one-link flexible manipulator is considered. The proposed model has been used to investigate the effect of the open-loop control torque profile, and the payload. The control strategy is based on the nonlinear State Dependent Riccati Equation (SDRE) design method in the context of application to robotics and manufacturing systems. In this paper, an experimental test-bed was developed to demonstrate the concept of end-point position feedback on a single-link elastic manipulator, and the control strategy for a single-link flexible manipulator. The controller is designed based on the nonlinear SDRE developed by the authors and applied to a flexible manipulator. The experimental results are compared with conventional PD controller strategy. The results reveal that the nonlinear SDRE controller is near optimal and robustly; and its performance is improved comparing to the PD control scheme.     

基于体系工程与物流均衡的C2M服务制造物流体系结构模型

C2M服务制造是基于以顾客为中心的C2M(Customer to Manufacture)商业模式,是在服务型制造及生产性服务业为基础上而形成的一种新型产业模式。C2M服务制造要求构建合理的物流体系,而构建物流体系结构已经成为该研究的关键基础。本文基于体系工程和物流均衡理论,通过建立物流体系以解决C(客户)端与M(制造)端的短链式互联问题,在分析C2M服务制造物流体系特征和资源要素的基础上,给出了C2M服务制造物流体系的概念模型和结构模型,并运用价值函数分析体系状态是否优化,从而达到C端与M端快速互联的目标,进而解决了物流体系结构模型在C2M服务制造物流体系构建中的应用问题。     

A Petri Net based algorithm for minimizing total tardiness in flexible manufacturing systems

Petri Nets have been extensively used for modeling and simulating of the dynamics of flexible manufacturing systems. Petri Nets can capture features such as parallel machines, alternative routings, batch sizes, multiplicity of resources, to name but a few. However, Petri Nets have not been very popular for scheduling in manufacturing due to the Petri Net “state explosion” combined with the NP-hard nature of many of such problems. A promising approach for scheduling consists of generating only portions of the Petri Net state space with heuristic search methods. Thus far, most of this scheduling work with Petri Nets has been oriented to minimize makespan. The problem of minimizing total tardiness and other due date-related criteria has received little attention. In this paper, we extend the Beam A^* Search algorithm presented in a previous work with capability to handle the total tardiness criterion. Computational tests were conducted on Petri Net models of both flexible job shop and flexible manufacturing systems. The results suggest that the Petri Net approach is also valid to minimize due date related criteria in flexible systems.     

Evaluation of Plant Focus Strategies: A Continuous Approximation Framework

The concept of plant focus emphasizes a firm's ability to increase productivity and lower cost by limiting the number and variety of operations at its production lines. In this paper, we present a quantitative modeling framework to analyze the choice between product focus and market focus strategies. We also study the effect of flexible manufacturing technology on plant focus. Our methodology is based on a facility design model that uses continuous functions in representing the spatial distribution of demand and cost parameters. One of the advantages of this approach is its ability to generate closed-form solutions with relatively little data. Furthermore, it enables us derive several managerial insights into plant focus decisions as well as the impact of technology alternatives on these decisions. Finally, continuous approximation approach has potential to complement more detailed mixed integer models. This research was partially funded by the Natural Sciences and Engineering Council of Canada (OGP 183631) and the Canada Research Chair in Distribution Management at HEC Montreal. Both authors are affiliated with the Center for Research on Transportation, which provided an excellent environment for collaboration. Three anynomuous referees and Gilbert Laporte, the guest co-editor, provided very helpful comments on an earlier draft of the paper.     

Hierarchical controls in stochastic manufacturing systems with convex costs

This paper presents an extension of earlier research on heirarchical control of stochastic manufacturing systems with linear production costs. A new method is introduced to construct asymptotically optimal open-loop and feedback controls for manufacturing systems in which the rates of machine breakdown and repair are much larger than the rate of fluctuation in demand and rate of discounting of cost. This new approach allows us to carry out an asymptotic analysis on manufacturing systems with convex inventory/backlog and production costs as well as obtain error bound estimates for constructed open loop controls. Under appropriate conditions, an asymptotically optimal Lipschitz feedback control law is obtained.This work was partly supported by the NSERC Grant A4619, URIF, General Motors of Canada, and Manufacturing Research Corporation of Ontario.     

多级制造系统的最优化模型及其应用

多级制造系统是现代制造业的主要加工方式，系统的每一级的加工速度和加工周期是系统设计的主要决策变量，正确确定这两个变量是系统得到优化的主要目标。本文导出了系统优化的基本模型，它包括系统各级的生产时间、等待时间、生产速度、生产成本以及系统的循环时间、总成本、产品利润和利润率等，并给出了一个应用实例。     

基于模糊证据推理的汽车制造产业网络环境复杂性测度

环境复杂性是汽车制造产业网络复杂性的主要诱因。利用指标波动程度测度复杂性的思想,建立表征汽车制造产业网络外部环境的指标体系,构建指标变动程度的模糊信度结构模型,运用模糊证据推理算法结合熵值理论对多指标进行信息融合,并利用灰色关联分析方法评估复杂性测度结果。通过2002~2012年汽车行业数据的实证研究,结果表明:经济环境与国际环境的波动是导致汽车制造产业网络复杂性的最主要因素,技术环境和市场环境次之;近10年来我国汽车制造产业网络外部环境经历了两次较大波动,总体复杂性呈现增长趋势。本研究可为汽车产业环境复杂性测度及应对提供思路参考。     

A genetic algorithm for cellular manufacturing design and layout

Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our proposed algorithm include a hierarchical chromosome structure to encode two important cell design decisions, a new selection scheme to dynamically consider two correlated fitness functions, and a group mutation operator to increase the probability of mutation. From the computational analyses, these proposed structure and operators are found to be effective in improving solution quality as well as accelerating convergence.     

Operational Decisions in AGV-Served Flowshop Loops: Fleet Sizing and Decomposition

This paper considers design and operational issues that arise in repetitive manufacturing systems served by automated guided vehicles (AGVs) in loop layouts with unidirectional material flow. Such systems are in widespread industrial use, and play an important role in modern manufacturing environments. The objective considered is the minimization of AGV fleet size, given the minimum steady state cycle time required to produce a minimal job set (or equivalently, given the maximum throughput rate). We also study whether the decomposition of a large AGV-served flowshop loop into several smaller loops improves productivity. The original loop and the decomposed design are compared with respect to the minimum cycle time needed for the repetitive manufacture of a minimal job set. When there are three or more machines in the loop, finding the optimal cycle time is an intractable problem. We therefore use the genetic algorithm developed in the companion paper [17], to identify whether the original or the decomposed design is more efficient. Our study suggests that many systems perform more productively as a result of decomposition. Finally, we discuss a joint sequencing issue that arises in decomposed systems with limited buffers between the loops, and analyze the tractability of all the relevant joint sequencing problems.     

A two-level hedging point policy for controlling a manufacturing system with time-delay,demand uncertainty and extra capacity

This paper focuses on the production control of a manufacturing system with time-delay, demand uncertainty and extra capacity. Time-delay is a typical feature of networked manufacturing systems (NMS), because an NMS is composed of many manufacturing systems with transportation channels among them and the transportation of materials needs time. Besides this, for a manufacturing system in an NMS, the uncertainty of the demand from its downstream manufacturing system is considered; and it is assumed that there exist two-levels of demand rates, i.e., the normal one and the higher one, and that the time between the switching of demand rates are exponentially distributed. To avoid the backlog of demands, it is also assumed that extra production capacity can be used when the work-in-process (WIP) cannot buffer the high-level demands rate. For such a manufacturing system with time-delay, demand uncertainty and extra capacity, the mathematical model for its production control problem is established, with the objective of minimizing the mean costs for WIP inventory and occupation of extra production capacity. To solve the problem, a two-level hedging point policy is proposed. By analyzing the probability distribution of system states, optimal values of the two hedging levels are obtained. Finally, numerical experiments are done to verify the effectiveness of the control policy and the optimality of the hedging levels.