On the fuzzy evaluation of measurement system analysis in a manufacturing and process industry environment: A comparative study

Abstract

Variation exists in all processes. There is not even a single process that is completely true. Measuring the trueness of the process is itself a process which can also imitate the process variation. Therefore, measurement system should be strong enough to wager on the trueness of the process. This paper is an attempt to indicate the true method and substantiate the use of measurement system analysis (MSA) by using it in two different environments i.e. in manufacturing as well as process industry. Also, a comparison among various analyzing techniques has been drawn for authenticating the candid method followed by an evaluation using fuzzy TOPSIS for authenticating the results of comparison. The organization's type, also, strongly influences the performance of MSA as revealed in the conclusion of the article. The results calculated by various methods and in both environments were discussed and as a result ANOVA comes out to be the best method. The application of correct MSA is highly required which ultimately results in increased organizations' performance. The study is one of its type and will motivate the researchers and industrialists to use and explore the new and efficient ways of MSA.

Uncertainty-Based Trimmed Coefficient of Variation with Application

“…e authors of [12][13][14][15] discussed the applications of trimmed average using fuzzy logic. More applications can be seen in [16,17].…”

The evaluation of supply chain performance in the Oil Products Distribution Company, using information technology indicators and fuzzy TOPSIS technique

“…Supply Chain Management (SCM) as an integrated approach for the appropriate management of materials and goods, information and finance owns the ability to face such conditions (Gazanfari et al, 2000). Also, a comparison among various analyzing techniques has been drawn for authenticating the candid method followed by an evaluation using fuzzy TOPSIS (Hwang & Yoon, 1981;Chakraborty et al, 2018) for authenticating the results of comparison (Mittal et al, 2018). Supply chain management, based on two principles of coordination and collaboration coordinates the organizations of a chain through information sharing and invites them to gain competitive advantage.…”