Application of fuzzy risk analysis for selecting critical processes in implementation of SPC with a case study

Hadi Akbarzadeh Khorshidi; Indra Gunawan; Sanaz Nikfalazar

doi:10.1007/s10726-015-9439-5

Application of fuzzy risk analysis for selecting critical processes in implementation of SPC with a case study

Hadi Akbarzadeh Khorshidi, Indra Gunawan, Sanaz Nikfalazar

School of Mathematics

Research output: Contribution to journal › Article › Research › peer-review

13 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	203-220
Number of pages	18
Journal	Group Decision and Negotiation
Volume	25
Issue number	1
DOIs	https://doi.org/10.1007/s10726-015-9439-5
Publication status	Published - 2016

Keywords

Fuzzy risk analysis
Group decision making
Manufacturing line
Statistical process control (SPC)
TOPSIS approach
Uncertainty

Access to Document

10.1007/s10726-015-9439-5

Cite this

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title = "Application of fuzzy risk analysis for selecting critical processes in implementation of SPC with a case study",

abstract = "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.",

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AB - 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.

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KW - Statistical process control (SPC)

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