International Journal of Flexible Manufacturing Systems Impact Factor & Information

Publisher: Springer Verlag

Journal description

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.

Current impact factor: 0.90

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2009 Impact Factor 0.903
2008 Impact Factor 1.044
2007 Impact Factor 0.452
2006 Impact Factor 0.448
2005 Impact Factor 0.231
2004 Impact Factor 0.6
2003 Impact Factor 0.735
2002 Impact Factor 0.694
2001 Impact Factor 0.222
2000 Impact Factor 0.382
1999 Impact Factor 0.419
1998 Impact Factor 0.258
1997 Impact Factor 0.313

Impact factor over time

Impact factor

Additional details

5-year impact 1.37
Cited half-life 9.40
Immediacy index 0.00
Eigenfactor 0.00
Article influence 0.40
Website International Journal of Flexible Manufacturing Systems website
Other titles International journal of flexible manufacturing systems (Online), International journal of flexible manufacturing systems
ISSN 0920-6299
OCLC 37915772
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Springer Verlag

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
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  • Conditions
    • Author's pre-print on pre-print servers such as
    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification

Publications in this journal

  • [Show abstract] [Hide abstract]
    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 12/2007; 19(4):685-712. DOI:10.1007/s10696-008-9041-0
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    ABSTRACT: This study is motivated by a real problem encountered in the manufacturing and distribution process at a local electronic manufacturer of security devices. We investigate the impact of operations redesign (i.e., operations merging) on the cost of safety stock in a supply chain. A simple safety stock method is used to derive a model for estimating safety stock levels. Our result shows that operations redesign can have a significant impact on safety stock investment. We extend and complement the existing literature in the following aspects: (i) we address the issue of safety stock deployment, i.e., we not only investigate the problem of how many operations should be delayed, but also determine which operations need to be delayed, (ii) we provide an efficient heuristic algorithm to determine which operations need to be merged, and (iii) we find the optimal operations redesign strategies under some special cases. Our analysis also reveals some important conditions and insights for better operations redesign, which enable us not only to decide when an operations redesign is appropriate, but also to suggest the scale and the format of the operations redesign.
    International Journal of Flexible Manufacturing Systems 12/2007; 19(4):516-532. DOI:10.1007/s10696-007-9029-1
  • [Show abstract] [Hide abstract]
    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 12/2007; 19(4):410-442. DOI:10.1007/s10696-008-9044-x
  • [Show abstract] [Hide abstract]
    ABSTRACT: In the increasingly competitive global markets, enterprises face challenges in responding to customer orders quickly, as well as producing customized products cost-effectively. This paper proposes a dynamic heuristic-based algorithm for the part input sequencing problem of flexible manufacturing systems (FMSs) in a mass customization (MC) environment. The FMS manufactures a variety of parts, and customer orders arrive dynamically with order size as small as one. Segmental set functions are established in the proposed algorithm to apply the strategy of dynamic workload balancing, and the shortest processing time (SPT) scheduling rule. Theoretical analysis is performed and the effectiveness of the algorithm in dynamic workload balancing under the complex and dynamic environment is proven. The application of the algorithm is illustrated by an example. The potential of its practical applications to the FMSs in make-to-order (MTO) supply chains is also discussed. Further research is provided.
    International Journal of Flexible Manufacturing Systems 12/2007; 19(4):392-409. DOI:10.1007/s10696-008-9045-9
  • [Show abstract] [Hide abstract]
    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 12/2007; 19(4):612-624. DOI:10.1007/s10696-007-9030-8
  • [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 12/2007; 19(4):533-547. DOI:10.1007/s10696-008-9048-6
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    ABSTRACT: The problem of scheduling jobs using wearing tools is studied. Tool wearing is assumed to be stochastic and the jobs are processed in one machining centre provided with a limited capacity tool magazine. The aim is to minimize the expected average completion time of the jobs by choosing their processing order and tool management decisions wisely. All jobs are available at the beginning of the planning period. This kind of situation is met in production planning of CNC-machines. Previous studies concerning this problem have either assumed deterministic wearing for the tools or omitted the wearing completely. In our formulation of the problem, tool wearing is stochastic and the problem becomes very hard to solve analytically. A heuristic based on genetic algorithms is therefore given for the joint problem of job scheduling and tool management. The algorithm searches the most beneficial job sequence when the tool management decisions are made by a removal rule taking into account the future planned usage of the tools. The cost of each job sequence is evaluated by simulating the job processing. Empirical tests with heuristics indicate that by taking the stochastic information into account, one can reduce the average job processing time considerably.
    International Journal of Flexible Manufacturing Systems 12/2007; 19(4). DOI:10.1007/s10696-008-9043-y
  • [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. DOI:10.1007/s10696-008-9046-8
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    ABSTRACT: This paper presents a model for assessing different capacity scalability policies in Reconfigurable Manufacturing System (RMS) for different changing demand scenarios. The novelty of this approach is two fold: (1) it is the first attempt to explore different capacity scalability policies in RMS based on multiple performance measures, mainly scaling rate, Work In Process level, inventory level and backlog level; and (2) the dynamic scalability process in RMS is modeled for the first time using System Dynamics. Different policies for capacity scalability for various demand scenarios were assessed. Numerical simulation results obtained using the developed capacity scalability model showed that the best capacity scalability policy to be adopted for RMS is dependent on the anticipated demand pattern as well as the various manufacturing objectives. The presented assessment results will help the capacity scalability planners better decide the different tradeoffs between the competing strategic and operational objectives of the manufacturing enterprise, before setting the suitable capacity scalability plan parameters.
    International Journal of Flexible Manufacturing Systems 09/2007; 19(3):128-150. DOI:10.1007/s10696-008-9031-2
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    ABSTRACT: Objective-oriented factory planning is a prerequisite for the economic operation of a factory. As intensive discussions in the literature as well as practical findings in factories over the years show, transformability and logistics are among the key objectives of a factory. It is striking, however, that both objectives have not so far been related to each other. Based on these findings, a method for evaluating the actual as well as the target transformability of a factory has been developed. It allows the user to assess whether the factory possesses adequate and economic transformability. In order to make the method more manageable for users in practice, a software tool is presented, and a benchmarking has been derived from the data collected by evaluating factory transformability. In addition, it has been found that transformability can influence logistics. A procedure will be presented that allows major means of adjustment to be found that improve the logistics objectives of a factory by using transformability. Finally, the outlook for future developments is discussed.
    International Journal of Flexible Manufacturing Systems 09/2007; 19(3):286-307. DOI:10.1007/s10696-007-9027-3
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    ABSTRACT: The flexibility of production capacities is a means for coping with the challenges in today’s market environment, especially when dealing with strong fluctuations in customers’ demands. The reliable planning and evaluation of these capacities and their inherent flexibilities are considered an important task for many companies. This paper presents a capacity/cost model that considers the impact of market uncertainties and the corresponding capacity flexibilities. It proposes a demand forecasting method, a modeling approach for capacity-related flexibilities and the analysis of the economical correlation between available and required capacities. Based on this, capacity planning can be optimized using this model. The different steps of applying this modeling approach are illustrated with the aid of an example.
    International Journal of Flexible Manufacturing Systems 09/2007; 19(3):151-172. DOI:10.1007/s10696-007-9024-6