A quantitative analysis: Assessment of data-driven decisions in CNC machining
Department of Mechanical Engineering Technology, Faculty of Engineering Technology, Rufus Giwa Polytechnic, Owo, Nigeria.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 355–359.
Article DOI: 10.30574/wjaets.2024.13.2.0582
Publication history:
Received on 18 October 2024; revised on 25 November 2024; accepted on 27 November 2024
Abstract:
A rapidly evolving field of manufacturing is real and data-driven decision-making has become a pivotal element in optimizing Computer Numerical Control (CNC) machining processes. This paper evaluates the effectiveness of employing a Likert scale to assess the impact of data-driven decisions in CNC machining environments. The key performance indicators (KPIs) such as precision, efficiency, user satisfaction and cost-effectiveness were focal points. The research aims to evaluate the impact of data analysis on decision-making processes in CNC machining, exploring factors such as accuracy, efficiency, and productivity. The results indicate a significant positive correlation between data-driven decisions and improved CNC machining outcomes. This paper investigated how subjective assessments from industry professionals can provide actionable insights. This study combines quantitative data with qualitative feedback to offer a comprehensive view of the effectiveness of data-driven strategies in CNC machining. However, the results suggested that data-driven decisions in CNC machining are perceived positively by industry professionals, with significant improvements in key performance areas.
Keywords:
Computer Numerical Control; Data-driven decision making; Precision; Efficiency
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