Statistical Analyses of Productivity Model Parameters for Process Improvement

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Abstract

Productivity modeling and validation is the assessment of data to establish scientific indications that a process is stable. The aim of this paper is to present a novel approach using statistical analyses for process improvement. This study highlights the process behavior of three different lathe machines unit with the intention to replace one of them. The research methodology has illustrated by producing a steel rod of 3.175 millimeter diameter based on 180 samples collected from each machine. For statistical data value analysis, MS Excel 2016 and Minitab 18 were utilized. The results showed that lathe machine 1 and 2 had an equivalent inconsistency, but significantly different data spreads. Similarly, the throughput for machine 2 was higher with greater variability as compared to machine 1 while machine 3 encountered a low rate of throughput. On the basis of the fallouts of the analysis, the research team has officially suggested to substitute lathe machine 3.

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APA

Hussain, Z. (2019). Statistical Analyses of Productivity Model Parameters for Process Improvement. Advances in Science and Technology Research Journal, 13(2), 157–167. https://doi.org/10.12913/22998624/106240

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