Type of the Paper Article

Azerbaijan State Oil and Industrial University

Article

Application of Innovative Methods in Uncertainty Measurement System Analysis.
Mahammad Imanov, Department of Instrumentation Engineering, ASOIU

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Teacher: Arzu Ibrahimova, PhD in Technology Sciences and dean of the Sabah groups, ASOIU

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Abstract: The project's goal is to use innovative methods in Measurement System Analysis. As a result of this application, there will be a process of selecting measuring systems and associated measuring instruments for use in all industries, limiting probable errors in product safety and quality assessments, and dramatically boosting measurement accuracy.

Keywords: Measurement System Analysis; uncertainty; methods in uncertainity; measurement accuracy, measurement errors; measuring instrument; metrological support; metrology; quality.
1. Introduction
As previously said, we can use the uncertainty in the Measurement System Analysis with the method we studied, and as a result of this application, we can accomplish a complicated method of decreasing measurement errors and a rapid improvement in measurement accuracy in evaluating product safety and quality. Measurement Systems Analysis (MSA) is a series of experiments and analyses used to more properly assess a measured system's process capability, performance, and level of uncertainty. We must examine the measurement data obtained at the start of the process, as well as the methods and equipment utilized to collect and record the data. Our purpose is to assess the accuracy of a measuring system, examine data changes, and pinpoint a possible source. Its purpose is to evaluate the acquired data's quality in terms of bias, stability, and linearity.

The level of measurement uncertainty for each measuring device or measuring instrument indicated in the process Control Plans must be evaluated when using the uncertainty approach we learned in the analysis of a measurement system. Each instrument must have the appropriate level of discrimination and resolution in order to get more accurate results.

All production facilities can aim to set the required target with Six Sigma, IMAIC (Identification, Measurement, Analysis, Improvement, and Control) or Product Quality Planning stages and select the correct and accurate measurement tools for more accurate process management using the method we explored. To do so, it must first identify the process's input and output factors, as well as gather data that will help it solve quantitative or qualitative challenges in order to accomplish the desired outcome.

In Six Sigma applications and Product Quality Planning, data measurement and analysis to detect input and output variability will be critical. As a result, according to the IMAIC concept, we can apply the PICT (Plan, Implement, Check, Take Measure) system approach in the measurement and analysis stages, as well as in Product Quality Planning.