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Aggregation for quality management

The problem relevant for quality management such as aggregation of many features into one representative is analyzed. Actually, in quality management practice, standard approaches to aggregation are often trivial and as a consequence - inadequate. In this paper, aggregation is treated as a logical and/or pseudo-logical operation that is important from many points of view such as adequacy and interpretations. | Yugoslav Journal of Operations Research 16 (2006), Number 2, 177-188 AGGREGATION FOR QUALITY MANAGEMENT Marko MIRKOVIĆ AD Rudnici boksita, Nikshich Montenegro marko-nk@cg.yu Janko HODOLIČ Faculty of Technical Sciences – Novi Sad, Novi Sad, Serbia hodolic@uns.ns.ac.yu Dragan RADOJEVIĆ Mihajlo Pupin Institute, Belgrade, Serbia Dragan.Radojevic@imp-automatika.co.yu Received: June 2005 / Accepted: August 2006 Abstract: The problem relevant for quality management such as aggregation of many features into one representative is analyzed. Actually, in quality management practice, standard approaches to aggregation are often trivial and as a consequence - inadequate. In this paper, aggregation is treated as a logical and/or pseudo-logical operation that is important from many points of view such as adequacy and interpretations. Keywords: Aggregation, quality, features of quality, Boolean polynomial, Choquet integral, OWA, logical aggregation. 1. INTRODUCTION A very important problem in quality control is the aggregation (fusion) of many partial aspects of quality – quality attributes into one global quality representative aspect. In the existing practice of quality control the weighting sum of partial aspects is used most often as an aggregation tool. This approach is additive and for all effects of interest which are not additive in their nature it is not adequate. For example: one, using a weighting sum as an aggregation tool even in the case of only two attributes (a, b), can’t 178 M. Mirković, J. Hodolič, D. Radojević / Aggregation for Quality Management realize a simple and natural demand such as a and b is important. In multi-attribute decision making community this problem was recognized [2, 10] and as a solution they use theory of capacity [10] known in fuzzy community as fuzzy measure and fuzzy integrals . In this approach additivity is relaxed by monotonicity, for which additivity is only a special case. As a consequence, the possible domain of application