A class of process capability indices for asymmetric tolerances

2016 ◽  
Vol 28 (4) ◽  
pp. 441-454 ◽  
Author(s):  
Z. Abbasi Ganji ◽  
B. Sadeghpour Gildeh
2020 ◽  
Vol 38 (6A) ◽  
pp. 910-916
Author(s):  
Sohaib Khlil ◽  
Huthaifa Al-Khazraji ◽  
Zina Alabacy

Process capability indices are a powerful tool used by quality control engineering to measure the degree to which the process is or is not meeting the requirements. This paper studies the application of process capability indices in the evaluation of a process with asymmetric tolerances. The analyzed collected data of the cleaning liquid “Zahi”, was used to investigate the ability of the filling process to meet the requested specifications. Matlab software was used to plot control charts, normal probability, and histogram of the data gathered from the production line and further performed statistical calculations. It was observed from the control charts that the filling process is under control. In addition, it was revealed by the process capability indices that the process of filling the cleaning liquid bottle is not fitted with the target value but it is adequate.


2015 ◽  
Vol 33 (1) ◽  
pp. 42-61 ◽  
Author(s):  
Jeh-Nan Pan ◽  
Chung-I Li ◽  
Wei-Chen Shih

Purpose – In the past few years, several capability indices have been developed for evaluating the performance of multivariate manufacturing processes under the normality assumption. However, this assumption may not be true in most practical situations. Thus, the purpose of this paper is to develop new capability indices for evaluating the performance of multivariate processes subject to non-normal distributions. Design/methodology/approach – In this paper, the authors propose three non-normal multivariate process capability indices (MPCIs) RNMC p , RNMC pm and RNMC pu by relieving the normality assumption. Using the two normal MPCIs proposed by Pan and Lee, a weighted standard deviation method (WSD) is used to modify the NMC p and NMC pm indices for the-nominal-the-best case. Then the WSD method is applied to modify the multivariate ND index established by Niverthi and Dey for the-smaller-the-better case. Findings – A simulation study compares the performance of the various multivariate indices. Simulation results show that the actual non-conforming rates can be correctly reflected by the proposed capability indices. The numerical example further demonstrates that the actual quality performance of a non-normal multivariate process can properly reflected by the proposed capability indices. Practical implications – Process capability index is an important SPC tool for measuring the process performance. If the non-normal process data are mistreated as a normal one, it will result in an improper decision and thereby lead to an unnecessary quality loss. The new indices can provide practicing managers and engineers with a better decision-making tool for correctly measuring the performance for any multivariate process or environmental system. Originality/value – Once the existing multivariate quality/environmental problems and their Key Performance Indicators are identified, one may apply the new capability indices to evaluate the performance of various multivariate processes subject to non-normal distributions.


2002 ◽  
Vol 27 (1) ◽  
pp. 55-68
Author(s):  
Satish Y Deodhar ◽  
Devanath Tirupati

Indian Food Specialties Limited (IFS) introduced tools of food quality management in May 2000 in response to changing market conditions and poor profitability. Spoilage in the production process was very high and the company had incurred losses for three successive years starting from 1996-97. The company addressed quality concerns by introducing management tools such as quality control charts and process capability indices, and was considering implementation of a food safety system called Hazard Analysis and Critical Control Points (HACCP). The case describes the changing market conditions and the company's response to improving quality, and provides a learning exercise on quality control charts, process capability indices, and HACCP.


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