Sustainable machining of P20 mold steel via trochoidal milling: Optimization strategies, cutting forces, and energy efficiency

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Authors: Nuri BOYACI, Gürcan Atakök
Cited by: 1
References: 23

Abstract

Trochoidal tool paths are preferred due to their superior material removal rate (MRR) compared to conventional strategies. Reducing cutting forces directly contributes to lower power consumption, which in turn decreases both machining time and operational costs, thereby enhancing overall productivity. In the context of intensifying global competition, minimizing the cost per unit through optimized cutting conditions—particularly by reducing cutting force and power—is imperative. Given that electricity generation still heavily relies on finite fossil fuel resources, optimizing machining parameters also supports sustainability objectives. Trochoidal milling has emerged as a transformative strategy for the sustainable machining of AISI P20 mold steel, offering significant improvements in cutting force reduction, surface integrity, and energy efficiency. By leveraging an extensive scientific background together with newly generated computational results, this work establishes that well‑calibrated trochoidal machining approaches deliver measurable improvements over traditional milling in terms of operational effectiveness and environmentally responsible manufacturing. Multi-objective optimization frameworks and experimental validations are discussed to provide a comprehensive understanding of how trochoidal milling contributes to green manufacturing. The paper concludes with identified research gaps and future directions for industrial implementation. In 27 experiments, the average force ranged from 1359.3 N to 2546.1 N. The cutting power was between 1042.6 and 1203.5 watt. The innovation in this study is to reduce costs, increase efficiency, and ensure sustainability by machining plastic mold steel with a trochoidial tool path using the latest technology 6 or 7-blade cutting tool.

Fields of Study & Subjects

Advanced machining processes and optimization Advanced Machining and Optimization Techniques Energy Efficiency and Management

Publication details

Journal / source
Journal of Engineering Research
Publisher
Elsevier BV
Volume
14
Issue
3
Pages
3479-3490
Publication date
1 April 2026
Language
EN