Diagnosis and improvement indexes for a multi-criteria industrial performance synthesized by a Choquet integral aggregation

The design and use of performance measurement systems (PMSs) have received considerable attention in recent years. Indeed, industrial performances are now defined in terms of numerous criteria to be synthesized for overall improvement purposes. The analysis of the literature leads to the conclusion that most of the proposed approaches deal with a qualitative approach of this multi-criteria issue. But only a few quantitative models for PMSs have been proposed in order to better monitor the continuous improvement cycle. Among them, the one proposed by the authors, based on a Choquet integral aggregation operator, allows to express an overall performance according to subordination and transverse interactions between the criteria involved. But, as this model is non linear, it is useful to define pieces of information aimed at aiding the manager to improve the performance situation. Thus, this article is a contribution to the managers' requirements for optimizing the improvement of the overall performance versus the allocated resources. In this view, indexes of efficiency and predictive improvement are proposed. The approach is applied to a case study submitted by a company manufacturing kitchen and bathroom furniture which wants to upgrade the monitoring of its “environment and quality improvement plan”.

[1]  Jean-Luc Marichal,et al.  An axiomatic approach of the discrete Choquet integral as a tool to aggregate interacting criteria , 2000, IEEE Trans. Fuzzy Syst..

[2]  M. Grabisch Fuzzy integral in multicriteria decision making , 1995 .

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

[4]  Umit Bititci,et al.  Quantitative models for performance measurement system , 2000 .

[5]  Jacky Montmain,et al.  A project decision support system based on an elucidative fusion system , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[6]  Lamia Berrah,et al.  Information fusion in industrial performance: a 2-additive Choquet-integral based approach , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[7]  Z. Babic,et al.  Ranking of enterprises based on multicriterial analysis , 1998 .

[8]  P Kueng,et al.  Building a Process Performance Measurement System: Some Early Experiences , 1999 .

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

[10]  Mooyoung Jung,et al.  Satisfaction assessment of multi-objective schedules using neural fuzzy methodology , 2003 .

[11]  Gyutai Kim,et al.  Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance measurement , 1997 .

[12]  A. Neely The performance measurement revolution: why now and what next? , 1999 .

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

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

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

[16]  Michel Grabisch,et al.  Fuzzy Measures and Integrals , 1995 .

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

[18]  Heeseok Lee,et al.  DEVELOPING A BUSINESS PERFORMANCE EVALUATION SYSTEM: AN ANALYTIC HIERARCHICAL MODEL , 1995 .

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

[20]  B. Mareschal,et al.  BANKADVISER: An industrial evaluation system , 1991 .

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

[22]  Christophe Labreuche,et al.  How to improve ACTS: an alternative representation of the importance of criteria in MCDM , 2001 .

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

[24]  Lamia Berrah,et al.  The Aggregation of Industrial Performance Information by the Choquet Fuzzy Integral , 2003 .

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

[26]  George Mavrotas,et al.  A multicriteria approach for evaluating the performance of industrial firms , 1992 .

[27]  Michel Grabisch,et al.  K-order Additive Discrete Fuzzy Measures and Their Representation , 1997, Fuzzy Sets Syst..

[28]  Afef Denguir,et al.  Contrôle de la dynamique d'un processus décisionnel par la phase d'information : Application la gestion d'un appel d'offres , 2004 .

[29]  Philip M. Marcus,et al.  The Visible Hand: The Managerial Revolution in American Business , 1979 .

[30]  Joseph Sarkis,et al.  Quantitative models for performance measurement systems—alternate considerations , 2003 .

[31]  Kai Mertins,et al.  Performance management , 1999, APMS.

[32]  Michel Lebas,et al.  Performance measurement and performance management , 1995 .

[33]  W. Deming Quality, productivity, and competitive position , 1982 .

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

[35]  Valerie Belton,et al.  Adding value to performance measurement by using system dynamics and multicriteria analysis , 2002 .