Customer's behaviour modelling for manufacturing planning

This paper deals with a customer-driven manufacturing planning approach. Manufacturers have adopted modern communication technologies for the information flow related to customers' orders. However, there is still high uncertainty in the information provided. This work introduces a model for estimating the probability that, once a customer has received a potential delivery date for a product, whether they will actually place the order. In this instance the manufacturing resources should be committed to this order. The Bayesian networks method is adopted and an automotive industrial case study is discussed.

[1]  H. Wiendahl,et al.  Production in Networks , 2002 .

[2]  Pawel Pawlewski,et al.  Modeling of Customer Behavior in a Mass-Customized Market , 2008, DCAI.

[3]  Sotiris Makris,et al.  On the information modeling for the electronic operation of supply chains: A maritime case study , 2008 .

[4]  Vivek B. Ajmani Modern Engineering Statistics , 1997, Technometrics.

[5]  M. Rouse,et al.  The Customer Centric Enterprise : Advances in Mass Customization and Personalization , 2003 .

[6]  George Chryssolouris,et al.  Manufacturing Systems: Theory and Practice , 1992 .

[7]  Sotiris Makris,et al.  Supply chain modeling and control for producing highly customized products , 2008 .

[8]  László Monostori,et al.  AI and machine learning techniques for managing complexity, changes and uncertainties in manufacturing , 2003 .

[9]  Géza Schay Introduction to probability with statistical applications , 2007 .

[10]  Tullio Tolio,et al.  A Rolling Horizon Approach to Plan Outsourcing in Manufacturing-to-Order Environments Affected by Uncertainty , 2007 .

[11]  László Monostori AI and machine learning techniques for managing complexity, changes and uncertainties in manufacturing , 2002 .

[12]  John Goodier,et al.  The Cambridge Dictionary of Statistics (3rd edition) , 2007 .

[13]  Quirico Semeraro,et al.  A new method to cope with decision makers' uncertainty in the equipment selection process , 2004 .

[14]  Soung Hie Kim,et al.  Mining the change of customer behavior in an internet shopping mall , 2001, Expert Syst. Appl..

[15]  D. Goodin The cambridge dictionary of statistics , 1999 .

[16]  J. Movellan Tutorial on Hidden Markov Models , 2006 .

[17]  Botond Kádár,et al.  Approaches to Managing Changes and Uncertainties in Manufacturing , 1998 .

[18]  Catherine Bounsaythip,et al.  Overview of Data Mining for Customer Behavior Modeling , 2001 .

[19]  Joseph Fong,et al.  An e-customer behavior model with online analytical mining for internet marketing planning , 2005, Decis. Support Syst..

[21]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[22]  Sotiris Makris,et al.  Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach , 2010 .