International Journal of Flexible Manufacturing Systems (INT J FLEX MANUF SYS )

Publisher: Springer Verlag


Flexible manufacturing systems (FMS) represent a class of highly automated systems. The increased importance of these highly automated manufacturing systems to the survival of modern industries has resulted in increasing research efforts that address the many issues inherent in flexible manufacturing. However not one periodic publication has been established to serve the research needs of the growing audience of industrial academic and governmental persons becoming involved with flexible machining and flexible assembly systems. The aim of the journal is to provide a consolidated forum for the publication of original high-quality articles on all topics related to flexible manufacturing that heretofore have been dispersed throughout a wide body of literature. The scope of the journal includes analysis to support the design or control of FMSs in which a variety of part types are simultaneously produced using versatile resources. These can be reallocated to produce different part types or a different mix of part types without major delays or investment. A balanced discussion of both theoretical and applied issues may be found in this journal including such matters as decision models performance models managerial issues and industrial needs and applications. Finally the journal cuts across the fields of engineering and management to include operations management manufacturing engineering industrial engineering operations research and management science as they relate to FMS.

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  • Website
    International Journal of Flexible Manufacturing Systems website
  • Other titles
    International journal of flexible manufacturing systems (Online), International journal of flexible manufacturing systems
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  • Material type
    Document, Periodical, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

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Springer Verlag

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    • Author can archive a post-print version
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    • On funders designated website/repository after 12 months at the funders request or as a result of legal obligation
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    • Articles in some journals can be made Open Access on payment of additional charge
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    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Deadlock-free scheduling of parts is vital for increasing the utilization of an Automated Manufacturing System (AMS). An existing literature survey has identified the role of an effective modeling methodology for AMS in ensuring the appropriate scheduling of the parts on the available resources. In this paper, a new modeling methodology termed as Extended Color Time Net of Set of Simple Sequential Process with Resources (ECTS3PR) has been presented that efficiently handles dynamic behavior of the manufacturing system. The model is subsequently utilized to obtain a deadlock-free schedule with minimized makespan using a new Evolutionary Endosymbiotic Learning Automata (EELA) algorithm. The ECTS3PR model, which can easily handle various relations and structural interactions, proves to be very helpful in measuring and managing system performances. The novel algorithm EELA has the merits of both endosymbiotic systems and learning automata. The proposed algorithm performs better than various benchmark strategies available in the literature. Extensive experiments have been performed to examine the effectiveness of the proposed methodology, and the results obtained over different data sets of varying dimensions authenticate the performance claim. Superiority of the proposed approach has been validated by defining a new performance index termed as the ‘makespan index’ (MI), whereas the ANOVA analysis reveals the robustness of the algorithm.
    International Journal of Flexible Manufacturing Systems 11/2007; 19(4):486-515.
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    ABSTRACT: Reactive scheduling is a procedure followed in production systems to react to unforeseen events that disturb the normal operation of the system. In this paper, a novel operations insertion heuristic is proposed to solve the deadlock-free reactive scheduling problem in flexible job shops, upon the arrival of new jobs. The heuristic utilizes rank matrices (Latin rectangles) to insert new jobs in schedules, while preventing the occurrence of deadlocks or resolving them using the available buffer space (if any). Jobs with alternative processing routes through the system are also considered. The heuristic can be employed to execute two reactive scheduling approaches in a timely efficient manner; to insert the new jobs in the already existing schedule (job insertion) or to reschedule all the jobs in the system (total rescheduling). Using experimental design and analysis of variance (ANOVA), the relative performance of the two approaches is studied and analyzed to provide some measures and guidelines for selecting the appropriate reactive scheduling approach for different problem settings. Three measures of performance are considered in the analysis; efficiency of the revised schedules in terms of the mean flow time, resulting system nervousness, and the required solution time. The results show that, on average, job insertion obtains revised schedules featuring significantly lower system nervousness and slightly higher mean flow time than total rescheduling. However, depending on the system size, number and processing times of the new jobs, and the available flexibility in the system, a trade-off between the two approaches should sometimes be considered.
    International Journal of Flexible Manufacturing Systems 08/2007; 19(3):264-285.
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    ABSTRACT: As the field of mass customization (MC) attains the status of a mature discipline, two significant research deficits stand out. First, a through metareview of the entire body of MC research that looks at the application value and rigorousness of research is overdue. Second, manufacturing issues, especially those pertaining to quality and the supply chain have been largely ignored. This issue is dedicated to both of these important areas of research. The conclusion with regards to the status of the MC field is that it is currently vibrant, with growing research volume and applications. The manufacturing issues dealt with in this issue are strategically important, dealing with quality and customization issues. The work on quality is the first of its kind: it seeks to generate a defect-tracking matrix consistent with product configurations, enabling agile identification of defects in a mass customization environment. The use of discrete event simulation to deal with the dynamically evolving customized demand so as to minimize cost and schedule disruption is innovative, timely, and profound.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(4):625-629.
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    ABSTRACT: The vision of mass customization has driven a movement toward low volume, high variety mass customization production (MCP) at low price. However, defect identification and defect tracking in such systems are extremely difficult because of the frequent reconfiguration needed by the number of different part types and the interruption of the information flow about quality with each reconfiguration of the system. It is important to quickly rebuild quality information flow with MCP system’s reconfiguration synchronously. This paper introduces a defect tracking method based on Quality Function Deployment for every MCP system module. A defects tracking matrix (DTM) based on the House of Quality directly connects manufacturing technologies with quality defects inside a MCP module. Each MCP reconfiguration requires the DTMs’ rearrangement and DTM-chain is proposed. A dynamic reconstructing algorithm synchronizes the DTM-chain with each MCP reconfiguration. A case study demonstrates the usefulness of the DTM and DTM-chain.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(4):666-684.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Business and operations strategists have long sought to formulate strategies that would serve profitably for a market of one. Two decades after its conception, there is growing evidence that mass customization strategy is transforming into a mass personalization strategy, making the market of one a reality, at least in select industries. The degree of transformation of a company depends on the extent to which its product is soft, i.e., can be produced electronically. Thus, at the lower end of the personalization spectrum are manufacturing companies engaged in producing hard, configurable products, while on the high end of the spectrum are service companies whose product can be totally configured and delivered electronically. The underlying factors that are enabling this transformation, in our view, are: (1) development of information technologies such as peer to peer (P2P), business to consumer (B2C), and Web 2.0, (2) near-universal availability of the Internet, (3) customer willingness and preparedness to be integrated into the process of product co-design and co-creation, (4) modern manufacturing systems, such as flexible manufacturing and, of course, (5) mass customization tools such as modularity and delayed differentiation, which help reduce manufacturing cost and cycle times and (6) deployment of customer-satisfaction-specific software called customer relationship management (CRM) to engender customer retention. Due to the importance and strategic success of affordable personalization, this issue is dedicated to that theme. The articles included in this issue would, I believe, serve as significant decision support mechanisms for companies pursuing a mass customization and personalization strategy. In addition to providing a brief perspective on articles included in this issue, we also summarize the state of the art of mass customization research.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(4):533-547.
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    ABSTRACT: In production environments, such as Flexible Manufacturing Systems (FMSs), the schedule can be disturbed by the occurrence of unplanned events. Machines stop for major failures, maintenance, tool changes due to wear, or tool reassignments. The rescheduling process, however, can be costly. In this study, a dynamic measure of flexibility which helps to determine an appropriate time for rescheduling an FMS has been defined and investigated. Flexibility is defined as a function of Capability and Capacity. Accordingly, two metrics have been developed to monitor the capability and capacity efficiency of each machine in the system for responding to the dynamic system status. The value of each metric falls between 0 and 1at all times. Higher values in the capability metric mean better machine selection and part distribution strategies among the machines. Higher values for the capacity metric mean higher machine utilization in the production plan. Based on the interaction between the metrics and their respective behavior in the system, four states have been identified and characterized. Simulations of various scenarios can be used to demonstrate the use of these metrics for monitoring FMS operations and determining appropriate times for rescheduling and tool reassignment.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(3):195-216.
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    ABSTRACT: This article employs a mass customization strategy to design travel packages that minimize the operation and processing costs for the service provider on one hand, while aligning the components of the packages to maximize customer satisfaction on the other. Data mining is used to identify rules of association to develop this model. Hidden relations in the massive travel agencies’ databases are revealed by using the association rules technique to customize travel packages according to customers’ requirements. This approach leads to fewer, but more manageable and popular travel package promotions. The overall package selection problem is modeled as an integer program that minimizes costs of operation and processing. Two different solution approaches were used: a mathematical modeling language approach and a heuristic algorithm approach. An illustrative numerical example based on a synthetic data set is also presented.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(4):612-624.
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    ABSTRACT: The selection of Reconfigurable Manufacturing Systems (RMS) configurations that include arrangement of machines, equipment selection, and assignment of operations, has a significant impact on their performance. This paper reviews the relevant literature and highlights the gaps that exist in this area of research. A novel “RMS Configuration Selection Approach” is introduced. It consists of two phases; the first deals with the selection of the near-optimal alternative configurations for each possible demand scenario over the considered configuration periods. It uses a constraint satisfaction procedure and powerful meta-heuristics, real-coded Genetic Algorithms (GAs) and Tabu Search (TS), for the continuous optimization of capital cost and system availability. The second phase utilizes integer-coded GAs and TS to determine the alternatives, from those produced in the first phase, that would optimize the degree of transition smoothness over the planning horizon. It uses a stochastic model of the level of reconfiguration smoothness (RS) across all the configuration periods in the planning horizon according to the anticipated demand scenarios. This model is based on a RS metric and a reconfiguration planning procedure that guide the development of execution plans for reconfiguration. The developed approach is demonstrated and validated using a case study. It was shown that it is possible to provide the manufacturing capacity and functionality needed when needed while minimizing the reconfiguration effort. The proposed approach can provide decision support for management in selecting RMS configurations at the beginning of each configuration period.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(2):67-106.
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    ABSTRACT: Dynamic variability in low-volume and highly customized products of a large assembly manufacturing system with an integrated supply chain has been very challenging to capture. Design and product configurations most likely impact outcomes of such broad variability. This article presents a framework to encompass this completely integrated system for using discrete event simulation as a modeling method. The system modeling framework addresses factors including customized configuration attributes and individual customer-preferred considerations for customized configurations. The framework is intended to aid decision-making concerning cost and schedule impacts associated with customization options chosen throughout the supply chain. A real-world example drawn from aerospace is included to demonstrate and validate the operational capability of the proposed framework.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(4):685-712.
  • International Journal of Flexible Manufacturing Systems 01/2007; 19(4):331-333.
  • International Journal of Flexible Manufacturing Systems 01/2007; 19(3):125-127.
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    ABSTRACT: This paper presents an optimal solution, based on Markov decision theory, for the problem of optimal capacity-related reconfiguration of manufacturing systems, under stochastic market demand. Both capacity expansion and reduction are considered. The solution quantitatively takes into account the effect of the ramp-up phenomenon, following each reconfiguration, on the optimal policy. A closed-form solution is presented for when product demand is independently and generally distributed over time. A real case concerning a flexible manufacturing line in the automotive sector is shown, to prove that ignoring the ramp-up effect in the decision process can lead to significant increases in overall costs.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(3):173-194.
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    ABSTRACT: Agility can be viewed as a need to encourage the enterprise-wide integration of flexible and core competent resources so as to offer value-added product and services in a volatile competitive environment. Since flexibility is considered a property that provides change capabilities of different enterprise-wide resources and processes in time and cost dimensions, supply chain flexibility can be considered a composite state to enterprise-wide resources to meet agility needs. Enterprise modeling frameworks depicting these composite flexibility states are difficult to model because of the complex and tacit interrelationship among system parameters and also because agility thrives on many business objectives. In view of this, the modeling framework presented in this paper is based on analytical network process (ANP) since this methodology can accommodate the complex and tacit interrelationship among factors affecting enterprise agility. The modeling framework forms a three-level network with the goal of attaining agility from the perspective of market, product, and customer as the actors. The goal depends on substrategies that address the characteristics of the three actors. Each of these substrategies further depends on manufacturing, logistic, sourcing, and information technology (IT) flexibility elements of the enterprise supply chain (SC). The research highlights that, under different environmental conditions, enterprises require synergy among appropriate supply chain flexibilities for practising agility. In the present research, the ANP modeling software tool Super Decisions™ has been used for relative prioritization of the supply chain flexibilities. We demonstrate through sensitivity analysis that dynamic conditions do require adjustments in the enterprise-wide flexibility spectrum.
    International Journal of Flexible Manufacturing Systems 01/2007; 19(4):410-442.