Paper
13 October 2000 Self-assessment procedure using fuzzy sets
Fotini Mimi
Author Affiliations +
Proceedings Volume 4192, Intelligent Systems in Design and Manufacturing III; (2000) https://doi.org/10.1117/12.403676
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States
Abstract
Self-Assessment processes, initiated by a company itself and carried out by its own people, are considered to be the starting point for a regular strategic or operative planning process to ensure a continuous quality improvement. Their importance has increased by the growing relevance and acceptance of international quality awards such as the Malcolm Baldrige National Quality Award, the European Quality Award and the Deming Prize. Especially award winners use the instrument of a systematic and regular Self-Assessment and not only because they have to verify their quality and business results for at least three years. The Total Quality Model of the European Foundation for Quality Management (EFQM), used for the European Quality Award, is the basis for Self-Assessment in Europe. This paper presents a self-assessment supporting method based on a methodology of fuzzy control systems providing an effective means of converting the linguistic approximation into an automatic control strategy. In particular, the elements of the Quality Model mentioned above are interpreted as linguistic variables. The LR-type of a fuzzy interval is used for their representation. The input data has a qualitative character based on empirical investigation and expert knowledge and therefore the base- variables are ordinal scaled. The aggregation process takes place on the basis of a hierarchical structure. Finally, in order to render the use of the method more practical a software system on PC basis is developed and implemented.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fotini Mimi "Self-assessment procedure using fuzzy sets", Proc. SPIE 4192, Intelligent Systems in Design and Manufacturing III, (13 October 2000); https://doi.org/10.1117/12.403676
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Cited by 3 scholarly publications.
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KEYWORDS
Fuzzy logic

Mathematical modeling

Systems modeling

Automatic control

Control systems

Intelligence systems

Design for manufacturability

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