A fuzzy expert system to increase accuracy and precision in measurement system analysis

In this paper, we have presented the first proposal to apply measurement system analysis (MSA) in fuzzy environment. Nowadays, because the quality control techniques are applied a lot in manufacturing, research and development environments, many decisions are made in processes and equipment evaluation, control, and improvement. Besides, the philosophy of measurement system analysis (MSA) depends on measurement error which hides true process capability; therefore, it must be implemented prior to any process improvement activities to minimize the measurement errors. Since the capability of each quality system is related to the accuracy of its measurement system, this research develops a novel methodology to increase precision and accuracy of MSA. To do so analyzing measurement systems under fuzziness of indices are investigated to make the environment more realistic. In this article, not only fuzzy measurement system analysis with gauge repeatability and reproducibility (GR&R) index as a triangular fuzzy number is proposed, but a fuzzy measurement system analysis a fuzzy expert system is presented to make more reliable and appropriate decisions. At the end, the applicability of the proposed methodology has been demonstrated within a case study in automotive parts industry to show impact of uncertainty in the reality.