Application of Fuzzy Risk Analysis for Selecting Critical Processes in Implementation of SPC with a Case Study

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.

[1]  Thong Ngee Goh,et al.  Prioritizing processes in initial implementation of statistical process control , 1998 .

[2]  Jun Ye,et al.  Multicriteria Group Decision-Making Method Using Vector Similarity Measures For Trapezoidal Intuitionistic Fuzzy Numbers , 2010, Group Decision and Negotiation.

[3]  Wen-Ran Zhang Knowledge representation using linguistic fuzzy relations , 1986 .

[4]  Ying-Ming Wang,et al.  Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment , 2006, Expert Syst. Appl..

[5]  C. B. Roes,et al.  Implementation of Statistical Process Control in service processes , 1997 .

[6]  Douglas C. Montgomery,et al.  Introduction to Statistical Quality Control , 1986 .

[7]  Alvin M. Strauss,et al.  Statistical process control application to weld process , 1997 .

[8]  H. Haleh,et al.  A new approach for fuzzy risk analysis based on similarity by using decision making approach , 2010, 2010 IEEE International Conference on Management of Innovation & Technology.

[9]  Juraj Vaculík,et al.  Risk Analysis in Managerial Process and Fuzzy Approach , 2013 .

[10]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on measures of similarity between interval-valued fuzzy numbers , 2008, Comput. Math. Appl..

[11]  Jing Zhang,et al.  Research on the health status monitoring model and monitoring system of destruction equipment for high-risk goods based on the fuzzy combination mode , 2012, Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing).

[12]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads , 2009, Expert Syst. Appl..

[13]  N. Ravi Shankar,et al.  Fuzzy risk analysis based on the novel fuzzy ranking with new arithmetic operations of linguistic fuzzy numbers , 2014, J. Intell. Fuzzy Syst..

[14]  Tony Roberts,et al.  Using statistical process control (SPC) chart techniques to support data quality and Information proficiency: the underpinning structure of high-quality health care , 2005 .

[15]  Shyi-Ming Chen,et al.  A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers , 2009, Expert Syst. Appl..

[16]  T. P. Nugent Improved roll texturing through implementation of statistical process control , 1994 .

[17]  Deng Yong,et al.  A TOPSIS-BASED CENTROID–INDEX RANKING METHOD OF FUZZY NUMBERS AND ITS APPLICATION IN DECISION-MAKING , 2005 .

[18]  A. R. Crathorne,et al.  Economic Control of Quality of Manufactured Product. , 1933 .

[19]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers , 2007, Applied Intelligence.

[20]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers , 2003, IEEE Trans. Fuzzy Syst..

[21]  Rui Cai,et al.  Research and Application of Intelligent Quality Control System Based on FMEA Repository , 2009, 2009 International Conference on Information Technology and Computer Science.

[22]  Xiuxu Zhao A Process Oriented Quality Control Approach Based on Dynamic SPC and FMEA , 2011 .

[23]  Kurt J. Schmucker,et al.  Fuzzy Sets, Natural Language Computations, and Risk Analysis , 1983 .

[24]  G. Goch,et al.  A Process Oriented Approach to Automated Quality Control , 2001 .

[25]  Shyamal Kumar Mondal,et al.  Fuzzy risk analysis using area and height based similarity measure on generalized trapezoidal fuzzy numbers and its application , 2015, Appl. Soft Comput..

[26]  Jiju Antony,et al.  Key ingredients for the effective implementation of statistical process control , 2000 .

[27]  Hadi Akbarzadeh Khorshidi,et al.  Implementation of SPC with FMEA in less-developed industries with a case study in car battery manufactory , 2013 .

[28]  Rjmm Ronald Does,et al.  A framework for implementation of statistical process control , 1997 .

[29]  Reza Tavakkoli-Moghaddam,et al.  A Fuzzy Stochastic Multi-Attribute Group Decision-Making Approach for Selection Problems , 2011, Group Decision and Negotiation.

[30]  S. M. Hosseini,et al.  An improved fuzzy risk analysis based on a new similarity measures of generalized fuzzy numbers , 2011, Expert Syst. Appl..