Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration

Year : 2025 | Volume : 15 | Issue : 02 | Page : 25 30
    By

    Prashant Roy,

  1. Student, Department of Mechanical Engineering, Banaras Hindu University, Varanasi, Uttar Pradesh, India

Abstract

Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic techniques. The paper further underscores the integration of smart manufacturing technologies, such as Internet of Things (IoT)-enabled CNC systems and digital twins, in enhancing real-time process control and sustainable production outcomes. Insights into multi-objective optimization for balancing throughput, surface quality, energy efficiency, and tool longevity position this paper as a practical reference for production managers, researchers, and CNC engineers. CNC machining has evolved into a vital strategic asset within production systems, driving improvements in efficiency, product quality, and sustainability. This paper provides a managerially focused review of optimization methodologies in CNC processes from 2015 to 2025, emphasizing their relevance to production strategy, resource planning, and operational decision-making. Techniques span traditional mathematical models to AI-driven and hybrid metaheuristic systems. Integration with Industry 4.0 technologies—such as IoT, digital twins, and real-time adaptive control—positions CNC systems as key enablers of smart and sustainable production. This review synthesizes how strategic optimization impacts throughput, quality, energy consumption, and tool longevity, offering actionable insights for operations managers, manufacturing strategists, and decision-makers. The article concludes by identifying key research gaps and suggesting future directions, such as the integration of sustainable machining practices, deployment of real-time closed-loop systems, and exploration of bio-inspired and quantum optimization algorithms. By presenting a comprehensive synthesis of existing literature and emerging technologies, this review aims to serve as a valuable reference for researchers, engineers, and practitioners working in the field of CNC machining and production optimization.

Keywords: CNC machining, production systems, optimization strategies, operations management, smart factory, sustainable manufacturing, strategic decision-making

[This article belongs to Journal of Production Research & Management ]

How to cite this article:
Prashant Roy. Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration. Journal of Production Research & Management. 2025; 15(02):25-30.
How to cite this URL:
Prashant Roy. Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration. Journal of Production Research & Management. 2025; 15(02):25-30. Available from: https://journals.stmjournals.com/joprm/article=2025/view=224394


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Regular Issue Subscription Review Article
Volume 15
Issue 02
Received 09/07/2025
Accepted 31/07/2025
Published 08/08/2025
Publication Time 30 Days
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