Application of Fuzzy Risk Analysis for Selecting Critical Processes in Implementation of SPC with a Case Study
| Autor: | Indra Gunawan, Hadi Akbarzadeh Khorshidi, Sanaz Nikfalazar |
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| Rok vydání: | 2015 |
| Předmět: |
Adaptive neuro fuzzy inference system
021103 operations research Computer science Strategy and Management 0211 other engineering and technologies General Social Sciences General Decision Sciences 02 engineering and technology computer.software_genre Statistical process control Group decision-making Arts and Humanities (miscellaneous) Ranking Management of Technology and Innovation 0202 electrical engineering electronic engineering information engineering Fuzzy set operations Factory (object-oriented programming) Fuzzy number 020201 artificial intelligence & image processing Data mining Risk assessment computer |
| Zdroj: | Group Decision and Negotiation. 25:203-220 |
| ISSN: | 1572-9907 0926-2644 |
| DOI: | 10.1007/s10726-015-9439-5 |
| Popis: | Fuzzy risk analysis is widely used in risk assessment of components by linguistic terms. Fuzzy numbers are used to quantify the associated uncertainty. This study employs fuzzy risk analysis to evaluate processes for implementing statistical process control (SPC) in a specified manufacturing system. To reach this goal, fuzzy risk analysis has been applied based on both ranking and similarity of generalized trapezoidal fuzzy numbers in a stepwise procedure. Therefore, a new approach has been introduced for fuzzy risk analysis of processes to overcome the shortcomings of previous fuzzy risk analysis approaches. As a result, fuzzy risk analysis is used as a decision making technique to select critical processes under uncertainty. Also, the application of the proposed SPC implementation algorithm is illustrated in the manufacturing line of a car battery factory. |
| Databáze: | OpenAIRE |
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