Optimizing Machine Selection and Cost of Quality: A Comprehensive Approach for Enhanced Industrial Efficiency and Economic Growth

Abstract

Abstract: In today's modern industrial economy, selecting suitable machinery and efficiently managing quality costs are critical for achieving sustainable growth and competitiveness. This research paper presents a comprehensive approach to optimizing machine selection and cost of quality (COQ) within industrial operations. The study commences by delineating the criteria for machine selection and determining their respective weights using the Analytic Hierarchy Process (AHP). Subsequently, the VIKOR method is applied to select the most suitable machine based on the established criteria and weights. Moreover, the paper explores the concept of COQ, underscoring its importance as a performance measurement tool for organizations. The research investigates various strategies for minimizing quality-related expenses and maximizing benefits, including defect prevention, quality assurance, and continuous improvement initiatives. A case study analysis, focusing on the selection between mechanical cutting CNC machines and laser cutting CNC machines, provides practical insights into the implementation of the proposed methodologies. Real data analysis of cost and quality metrics, coupled with formula-based calculations, offers valuable insights into the decision-making process. The research underscores the significance of market analysis and leveraging modern technology trends to inform machine selection decisions. Overall, the findings contribute to enhancing industrial efficiency and promoting economic growth by facilitating informed decision-making in machine selection and COQ management