Modelling and Complexity Assessment of Assembly Supply Chain Systems

Abstract This paper focuses on the modeling of assembly supply chain (ASC) systems in order to establish a framework generating topological classes of ASCs. Subsequently, structural parameters of the networks levels are explored with the aim to generate all possible non–repeated ASC structures. In this paper, we also define several structural complexity metrics indicators, such as the index of vertex degree that is adopted from the Shannon«s entropy theory as well as other pertinent complexity indicators. After the application of these indicators to ASC structures, we benchmark complexity indicators based on predefined criteria. Research results are especially applicable at the early configuration design stage to make a decision about a suitable networked manufacturing structure that will satisfy the production functional requirements and will make managerial tasks simpler and more cost effective.

[1]  P. Földesi,et al.  Efficient Control of Logistic Processes Using Multi-criteria Performance Measurement , 2009 .

[2]  Robert Bucki,et al.  COMPUTATIONAL MODELLING OF THE PARALLEL LOGISTIC SYSTEM , 2012 .

[3]  Vladimir Modrak,et al.  Complexity Metrics for Assembly Supply Chains: A Comparative Study , 2012 .

[4]  T. Blecker,et al.  Development of an Approach for Analyzing Supply Chain Complexity , 2005 .

[5]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[6]  Yoram Koren,et al.  Product variety and manufacturing complexity in assembly systems and supply chains , 2008 .

[7]  Moshe M. Barash,et al.  Complexity in manufacturing systems, Part 1: Analysis of static complexity , 1998 .

[8]  Alessandro Vespignani,et al.  Dynamical Processes on Complex Networks , 2008 .

[9]  Gregory J. Chaitin,et al.  On the Length of Programs for Computing Finite Binary Sequences , 1966, JACM.

[10]  Bronislav Chramcov,et al.  Control of the serial production system , 2011 .

[11]  N. Trinajstic,et al.  Information theory, distance matrix, and molecular branching , 1977 .

[12]  B. Vos,et al.  Virtuous and vicious cycles on the road towards international supply chain management , 1999 .

[13]  A. Kolmogorov Three approaches to the quantitative definition of information , 1968 .

[14]  D. Bonchev,et al.  Complexity in chemistry, biology, and ecology , 2005 .

[15]  Bang‐Yen Chen WHAT CAN WE DO WITH NASH'S EMBEDDING THEOREM ? , 2004 .

[16]  Gerhard Friedrich,et al.  Mass Customization: Concepts-Tools-Realization , 2005 .

[17]  Danail Bonchev,et al.  Quantitative Measures of Network Complexity , 2005 .

[18]  O. Deiser,et al.  On the Development of the Notion of a Cardinal Number , 2010 .

[19]  V. Modrak On the conceptual development of virtual corporations and logistics , 2007, 2007 International Symposium on Logistics and Industrial Informatics.

[20]  Richard Wilding,et al.  Chaos Theory: Implications for Supply Chain Management , 1998 .

[21]  Irene A. Stegun,et al.  Handbook of Mathematical Functions. , 1966 .

[22]  Taghi M. Khoshgoftaar,et al.  Applications of a relative complexity metric for software project management , 1990, J. Syst. Softw..

[23]  Michael Milgate,et al.  Supply chain complexity and delivery performance: an international exploratory study , 2001 .

[24]  Janet Efstathiou,et al.  Advances on measuring the operational complexity of supplier-customer systems , 2006, Eur. J. Oper. Res..

[25]  W. Ashby,et al.  An Introduction to Cybernetics , 1957 .