A Quantified Industrial Performance Measurement System Based on a Choquet Fuzzy Integral

This study deals with the aggregation of performance expressions in a manufacturing context, Le. the mechanism which allows the computation of a global performance knowing the elementary ones. In this kind of aggregation the elementary performances to be combined are, on the one hand, information, often of a heterogeneous nature (cost, quality, delay ...), on the other hand, they are associated to diversified and numerous objectives which interact in different ways. In this context, the conventional approaches based on the Weighted Arithmetic Mean and the Analytic Hierarchy Process show their limitations. Thus, we propose an approach based on the fuzzy Choquet integral and on a MACBETH inspired method. This approach satisfies measurement theory requirements thanks to performance expressions defined according interval scales. The proposed procedure for quantifying performance measurement is illustrated on a case study submitted by a company that manufactures bathrooms and kitchens.

[1]  Leonard L Fortuin,et al.  Performance Indicators — Why, Where and How? , 1988 .

[2]  Maurice Bitton.  Ecograi : méthode de conception et d'implantation de systèmes de mesure de performances pour organisations industrielles , 1990 .

[3]  Yves Ducq,et al.  Coherence analysis methods for production systems by performance aggregation , 2001 .

[4]  Christophe Labreuche,et al.  The Choquet integral for the aggregation of interval scales in multicriteria decision making , 2003, Fuzzy Sets Syst..

[5]  G. Mauris,et al.  Quantitative expression and aggregation of performance measurements based on the MACBETH multi-criteria method , 2007 .

[6]  Bernard Grabot.  Objective satisfaction assessment using neural nets for balancing multiple objectives , 1998 .

[7]  M. Grabisch.  The application of fuzzy integrals in multicriteria decision making , 1996 .

[8]  Lamia Berrah,et al.  Global vision and performance indicators for an industrial improvement approach , 2000 .

[9]  Shlomo Globerson,et al.  Issues in developing a performance criteria system for an organization , 1985 .

[10]  Thomas J. Crowe,et al.  An integrated dynamic performance measurement system for improving manufacturing competitiveness , 1997 .

[11]  Carlos A. Bana e Costa,et al.  Applications of the MACBETH Approach in the Framework of an Additive Aggregation Model , 1997 .

[12]  L. Berrah,et al.  Information aggregation in industrial performance measurement: rationales, issues and definitions , 2004 .

[13]  V. Clivillé,et al.  Approche systémique et méthode multicritère pour la définition d'un système d'indicateurs de performance , 2004 .

[14]  John Bradford,et al.  A non-linear redesign methodology for manufacturing systems in SMEs , 2002, Comput. Ind..

[15]  Andrea Rangone,et al.  An analytical hierarchy process framework for comparing the overall performance of manufacturing departments , 1996 .

[16]  Carlos A. Bana e Costa,et al.  A critical analysis of the eigenvalue method used to derive priorities in AHP , 2008, Eur. J. Oper. Res..

[17]  R. Kaplan,et al.  The balanced scorecard--measures that drive performance. , 2015, Harvard business review.

[18]  Stan Schenkerman.  Avoiding rank reversal in AHP decision-support models , 1994 .

[19]  U. Bititci.  Modelling of performance measurement systems in manufacturing enterprises , 1995 .