The environment, resources, and population are three critical issues that human society currently faces. Among them, environmental problems have been worsening and now pose a serious threat to the survival and development of humanity. The manufacturing industry is a key sector that generates wealth for society, but it also consumes significant amounts of limited natural resources and contributes heavily to pollution. Therefore, it is essential for the manufacturing industry to adopt a sustainable development strategy. Green manufacturing is a modern approach that considers both environmental impact and resource efficiency throughout the entire product lifecycle—from design and production to packaging, transportation, usage, and disposal. It aims to minimize environmental harm, reduce resource consumption, and optimize economic and social benefits.
Machining is a fundamental process in manufacturing technology, and with technological advancements, it has evolved into a stage characterized by high-speed cutting, new processing methods, and comprehensive technologies. High-speed cutting, for example, has become the mainstream in cutting processes, and its development and application—covering improvements in machine tools and cutting tools—can enhance overall manufacturing performance, efficiency, and environmental friendliness. In modern machining, the cutting tool plays a crucial role in ensuring machining quality, improving productivity, and influencing energy consumption, the use of cutting fluids, and safety. These factors collectively determine the greenness of the machining process.
Recent developments in eco-friendly, high-performance tool materials, including coated surfaces, advanced manufacturing techniques, and safe usage practices, have significantly improved cutting performance. This has enabled green cutting methods such as high-speed and dry cutting. These innovations have enhanced machining quality, efficiency, cost-effectiveness, energy use, and fluid consumption, supporting the goals of green manufacturing. When planning for green manufacturing, selecting the right tool directly affects the environmental performance of the cutting process.
From five perspectives—processing time, quality, cost, resource consumption, and environmental impact—the influence of cutting tools on machining was analyzed, leading to the establishment of a multi-objective evaluation system for tool selection and a decision-making framework for green manufacturing. The model combines quantitative analysis using fuzzy clustering with qualitative reasoning from expert systems. Since the 1980s, researchers have studied resource and energy issues in manufacturing systems related to green manufacturing, proposing a set of decision variables including time (T), quality (Q), cost (C), environmental impact (E), and resource consumption (R). These variables form the basis for decision-making in green manufacturing.
Tool selection in green manufacturing is a complex, multi-objective problem involving both qualitative and quantitative factors. Traditionally, optimization focused on productivity, cost, and profitability. However, with the growing emphasis on sustainability, the tool industry is shifting toward a multi-objective model that balances economic, social, and environmental benefits. Factors influencing tool development now include function, quality, cost, time, environment, and resources. The tool selection target system for green manufacturing includes T, Q, C, R, and E as key factors, with corresponding objective functions: T(X), Q(X), C(X), R(X), and E(X).
The optimal decision involves finding the best solution among multiple alternatives, represented as an n-dimensional vector X = [x1, x2, ..., xn]^T, where xi indicates whether the ith plan is used or not. Constraints, both inequality and equality, define the feasible region. The goal is to find X* that minimizes time, maximizes quality, reduces cost, lowers resource consumption, and minimizes environmental impact.
In practice, cutting speed and feed rates are subject to various constraints, such as tool durability, surface roughness, workpiece rigidity, and clamping reliability. The model operates under given environmental conditions, including resource limitations, quality objectives, cost targets, and process requirements. Solving this multi-objective problem requires combining quantitative analysis, such as fuzzy clustering, with qualitative reasoning from experts. The process involves establishing an evaluation index set, performing fuzzy clustering, calculating similarity matrices, assigning weights, and normalizing results to achieve a comprehensive evaluation.
A case study compared conventional high-speed steel tools with TiN-coated domestic and imported high-speed steel tools in a CNC machining process. Results showed that TiN-coated tools improved machining quality, reduced energy consumption, lowered noise levels, and minimized cutting fluid use. Although the initial cost of imported tools was higher, their longer tool life and improved efficiency led to lower overall costs. This demonstrated the feasibility of green manufacturing strategies in real-world applications.
In conclusion, the choice of cutting tools significantly impacts the environmental performance of machining. A multi-objective decision-making framework for green manufacturing, incorporating time, quality, cost, resource use, and environmental impact, provides a structured approach to tool selection. By integrating quantitative and qualitative methods, this model offers a practical solution for achieving sustainable manufacturing.
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