An integrated modelling framework to support manufacturing system diagnosis for continuous improvement

  • Authors:

  • J. C. Hernandez-Matias;A. Vizan;J. Perez-Garcia;J. Rios

  • Affiliations:

  • Mechanical and Manufacturing Engineering Department, E.T.S. Ingenieros Industriales,, Polytechnic University of Madrid (UPM), Jose Gutierrez Abascal 2, 28006 Madrid, Spain;Mechanical and Manufacturing Engineering Department, E.T.S. Ingenieros Industriales,, Polytechnic University of Madrid (UPM), Jose Gutierrez Abascal 2, 28006 Madrid, Spain;Mechanical and Manufacturing Engineering Department, E.T.S. Ingenieros Industriales,, Polytechnic University of Madrid (UPM), Jose Gutierrez Abascal 2, 28006 Madrid, Spain;Mechanical and Manufacturing Engineering Department, E.T.S. Ingenieros Industriales,, Polytechnic University of Madrid (UPM), Jose Gutierrez Abascal 2, 28006 Madrid, Spain

  • Venue:
  • Robotics and Computer-Integrated Manufacturing
  • Year:
  • 2008

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Abstract

This paper proposes an integrated modelling framework for the analysis of manufacturing systems that can increase the capacity of modelling tools for rapidly creating a structured database with multiple detail levels and thus obtain key performance indicators (KPIs) that highlight possible areas for improvement. The method combines five important concepts: hierarchical structure, quantitative/qualitative analysis, data modelling, manufacturing database and performance indicators. It enables methods to build a full information model of the manufacturing system, from the shopfloor functional structure to the basic production activities (operations, transport, inspection, etc.). The proposed method is based on a modified IDEF model that stores all kind of quantitative and qualitative information. A computer-based support tool has been developed to connect with the IDEF model, creating automatically a relational database through a set of algorithms. This manufacturing datawarehouse is oriented towards obtaining a rapid global vision of the system through multiple indicators. The developed tool has been provided with different scorecard panels to make use of KPIs to decide the best actions for continuous improvement. To demonstrate and validate both the proposed method and the developed tools, a case study has been carried out for a complex manufacturing system.