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PERFORMANCE MEASUREMENT OF TQM USING INTEGRATED FUZZY-AHP
RAKESH KUMAR & R.S. MISHRA
Delhi Technological University, Delhi-110042
ABSTRACT
Performance measurement is regarded as one of the most important and critical tasks in the course of any organization.
Measuring performance is the assessment of the possible impact that a proposed plan or project may have on the
organizational system, together consisting of the financial, non-financial and operational aspects. The aim of this paper is
to propose a performance measurement methodology based on an integrated Fuzzy-AHP approach in the context of total
quality management (TQM). In the proposed methodology the criteria weights are generated by a fuzzy-AHP procedure.
The fuzzy set theory is a perfect means for modeling uncertainty or imprecision arising from human mental phenomena.
The usage of fuzzy sets in describing uncertainties and vagueness in different critical success factors of TQM simplifies
the complex structure of performance assessment.
KEYWORDS: Performance Measurement, TQM, Multicriteria, Fuzzy, AHP
Received: Jun 08, 2020; Accepted: Jun 28, 2020; Published: Sep 01, 2020; Paper Id.: IJMPERDJUN20201008
INTRODUCTION
Performance measurement often has to deal with latent variables which were difficult to identify and define also
components that may involve both quantitative and qualitative factors. Performance measurement is a complex task
not only because of its wide scope but also because of the wide range of attributes that bear on its assessment,
Kumar, R. et al. (2019).In terms of scope, an assessment may cover subjective and vague decisions that may affect
various interest groups or stakeholders each with their own demands and needs. In view of these difficulties,
methods based on fuzzy logic may be quite useful in undertaking difficult assessment procedures. The fuzzy set
theory was introduced by Zadeh (1965) to express the linguistic terms in decision-making process in order to
resolve the vagueness, ambiguity and subjectivity of human judgment. A fuzzy method stands very helpful to tackle
precisely with complex and ill-defined performance measurement decision making problems. Very few
organizations categorized themselves as having fairly TQM-driven performance management system, they were
quite positive – if not yet revealing conclusive evidence – of understanding the influence of system factors on
individual performance in a quality-driven context, Soltani,E. et al. (2005).G. G. Dess et al. (1984) addressed in his
research that research which incorporates organizational performance (OP) must address two basic issues: (1)
selection of a conceptual framework from which to define OP and (2) identification of accurate, available measures
that operationalize OP. In addition, collecting data and information to coordinate and support the procedure of
taking action and making decisions throughout the organization is the reason for performance measurement (Van
Schalkwyk, 1998).
The subsystems like Just-in-Time (JIT), Total Productivity System (TPS), Total Productive Maintenance
(TPM), Supply Chain Management (SCM), Lean Manufacturing (LM) System and many more were incorporated to
the organizational system as per their fit to achieve the benchmarked performance or the targeted level of
Original Article
International Journal of Mechanical and Production
Engineering Research and Development (IJMPERD)
ISSN(P): 2249–6890; ISSN(E): 2249–8001
Vol. 10, Issue 3, Jun 2020, 10543–10562
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