Evaluating and Assessing the Impact of Optimized Testing on Product Quality in Machine Parts Manufacturing

Abstract

This project-based thesis examines the assessment and evaluation of the impact of the optimized testing in machine parts manufacturing, the client company for this work. Process metrics were identified and evaluated by comparing averages and variations to performance specifications or targets. Metrics such as First-Pass Yield and Customer Claim data are used to track, monitor, and assess whether the strategy would yield manageable and sustainable results. These metrics were analyzed before and after the implementation to quantify the impact of the optimized testing. Some process changes were implemented, such as immediate dissemination of information or training, supporting material, monitoring, and control procedures.

This work used a quantitative data collection method, a statistical analysis tool called Minitab, and MS Excel to organize and analyze the data. Data was collected from existing internal process records and a database.

This paper provides an answer to the research question by showcasing the outcomes of the data analysis. It also examines the impact of optimized testing on the quality metric. Furthermore, the report acknowledges the limitations of the research and puts forward suggestions for future studies.