Chapter

Design of Advanced Manufacturing Systems

pp 37-71

A DSS for Strategic Planning

  • M. BruccoleriAffiliated withDipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale (DTMPIG), Università degli Studi di Palermo
  • , G. Lo NigroAffiliated withDipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale (DTMPIG), Università degli Studi di Palermo
  • , S. La Noto DiegaAffiliated withDipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale (DTMPIG), Università degli Studi di Palermo
  • , P. RennaAffiliated withDipartimento di Fisica Ambientale, Università degli Studi della Basilicata
  • , G. PerroneAffiliated withDipartimento di Fisica Ambientale, Università degli Studi della Basilicata

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Abstract

This chapter presents an innovative approach for assisting entrepreneurs in making long term capacity decisions in Advanced Manufacturing Systems (AMSs). AMSs require high investment costs in manufacturing equipment, human resources and technology knowledge. Such high investments together with the wideness and the variability of the competition scenario contribute to increase the perception of the risk for industrial entrepreneurs especially in SMEs. This problem could be approached by providing the entrepreneur with a Decision Support System (DSS) able to assist her/him in making long term capacity decision in AMS. The DSS proposed in this chapter allows the entrepreneur to plan its production strategy starting from company business strategy, market strategy, competition scenario and outsourcing scenario. Starting from such information, a Fuzzy Expert Systems allows defining the kind of strategic flexibility the company needs and how the company should compose its production mix between internal production and outsourced one. This strategic information represents the input of a Long Term Capacity Planning Model based on economy of scope models that constitutes the economic and financial hearth of the DSS.

Keywords

Advanced Manufacturing Systems long-term capacity planning fuzzy systems economy of scope