Implementation of fuzzy rule-based algorithms in p control chart to improve the performance of statistical process control

Rabbi, Md. F.; Chakrabarty, N.; Shefa, J.

doi:10.22105/riej.2018.150727.1062

Document Type : Research Paper

Authors

Department of Industrial Engineering and Management, Faculty of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, Bangladesh.

https://doi.org/10.22105/riej.2018.150727.1062

Abstract

In the statistical process control when the process is very sensitive and control limit shifts are the prime concerns, there fuzzy control charts can be a better solution. In decision making, extra “rather in control” and “rather out of control” decisions facilitate to find out the slight changes in the control chart. The automation of fuzzy control chart in the Excel VBA makes the data input and decisions making process faster. The vagueness of the data is removed as the charts deal with the triangular or trapezoidal area rather than some points in the control limits. Alongside the fuzzy control charts, Marcucci approach has been followed to find out the goodness-of-fit of the samples and to find out the effectiveness of fuzzy control charts.

Keywords

Main Subjects

Total quality management and quality engineering

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International Journal of Research in Industrial Engineering

Implementation of fuzzy rule-based algorithms in p control chart to improve the performance of statistical process control

References

References

Volume 7, Issue 4
December 2018
Pages 441-459

Implementation of fuzzy rule-based algorithms in p control chart to improve the performance of statistical process control

References

References

Volume 7, Issue 4December 2018Pages 441-459

Volume 7, Issue 4
December 2018
Pages 441-459