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The Condition of Uniqueness in Manufacturing Process Representation by Performance/Quality Indicators
Author(s) -
Franceschini Fiorenzo,
Galetto Maurizio,
Maisano Domenico,
Viticchiè Luciano
Publication year - 2006
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.762
Subject(s) - uniqueness , computer science , quality (philosophy) , set (abstract data type) , process (computing) , representation (politics) , performance indicator , production (economics) , management science , risk analysis (engineering) , operations research , industrial engineering , mathematics , engineering , marketing , economics , business , mathematical analysis , philosophy , epistemology , politics , political science , law , macroeconomics , programming language , operating system
One of the most critical aspects in operations management is making firm goals representable. This is usually done by translating the organization results and objectives in to ‘performance measures’. The scientific literature shows many applications in different fields such as quality, production, logistics, marketing, etc. Nevertheless, a general theory formalizing the basic and application concepts is still lacking. This paper represents a first attempt to provide a mathematical structure to the concept of an indicator. A set of basic definitions is introduced with the aim of giving a rigorous explanation of the concept of a ‘performance indicator’. Particular attention is dedicated to the condition of ‘uniqueness’. When dealing, for example, with performance evaluations of a given manufacturing plant, a practical way is to define some indicators which make tangible the different aspects of the system at hand. In this case, indicators such as throughput, defectiveness, output variability, efficiency, etc. are commonly employed. However, going on into the problem, many questions arise: ‘How many indicators shall we use?’, ‘Is there an optimal set?’, ‘Is this set unique?’, ‘If not, what is the best one (if it exists)?’, ‘Can all these indicators be aggregated in a unique one?’, ‘Are indicators the same as measurements?’, and so on. The aim of this paper is to give an answer to all these questions. A general theory which specifically faces this topic is presented. All the introduced concepts are explained and discussed by the use of practical examples. Copyright © 2006 John Wiley & Sons, Ltd.