An application of fuzzy sets to process performance evaluation

The successfulness of total quality management is dependent on the initiative of employees to apply their problem solving techniques continuously. However, the performance evaluation is quite subjective since it relies on the individual judgements of supervisors who have different perceptions of the process performance. This paper presents a performance measurement system to determine the priority in execution of quality improvement according to the performances of processes. Using a model containing a set of strategy‐related performance measures, misdirection of implementation of improvement projects due to subjective evaluation of process performance can be reduced. A fuzzy set of quality measures is introduced to calculate numerical quality rating for processes. The model is simulated and experimented on with a conventional improvement implementation practice. It is expected that the proposed model is superior in the major competitive capabilities including quality, cost flexibility, delivery reliability and speed.

[1]  Serafín Moral,et al.  Classification of fuzzy measures , 1989 .

[2]  B. Dale.  The Use of the Quality Improvement Framework in Trafford Park , 1994 .

[3]  John G. Wacker,et al.  A Theoretical Model of Manufacturing Lead Times and Their Relationship to a Manufacturing Goal Hierarchy , 1996 .

[4]  Gregory P. White.  A survey and taxonomy of strategy‐related performance measures for manufacturing , 1996 .

[5]  Andy Neely,et al.  Performance measurement system design , 1995 .

[6]  Andy Neely,et al.  Realizing Strategy through Measurement , 1994 .

[7]  Amy J. C. Trappey,et al.  A computerized quality function deployment approach for retail services , 1996 .

[8]  J. Rockart.  Chief executives define their own data needs. , 1979, Harvard business review.

[9]  W. H. Ip,et al.  The implementation of a model for integration of MRP II and TQM , 1999 .

[10]  Robert H. Chenhall,et al.  Reliance on manufacturing performance measures, total quality management and organizational performance , 1997 .

[11]  Chris Caplice,et al.  A Review and Evaluation of Logistics Performance Measurement Systems , 1995 .

[12]  R. C. Daniels.  Performance measurement at the sharp end driving continuous improvement on the shop floor , 1995 .

[13]  Kl Yung,et al.  A mechanism for the integration of TQM and MRPII , 1998 .

[14]  Stefano Tonchia,et al.  Lean organization, management by process and performance measurement , 1996 .

[15]  James S. Noble,et al.  The changing basis of performance measurement , 1996 .

[16]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[17]  Houn-Gee Chen,et al.  The information requirements of total quality management , 1998 .