Environmentally Friendly Machining

Zhao, F and Sharma, Abhay (2014) Environmentally Friendly Machining. In: Handbook of Manufacturing Engineering and Technology. Springer, London, pp. 1-25. ISBN 978-1-4471-4976-7

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Abstract

Machining is a controlled material removal process and finds its application in a variety of industrial sectors such as automobile, aerospace, and defense. Similar to many other manufacturing processes, machining bears significant environmental impacts in terms of energy/resource consumption, airborne emissions, wastewater discharge, and solid wastes along with occupational health risks. Most of these issues are due to the use of cutting fluids, which are traditionally formulated with petroleum-derived compounds with high ecotoxicity and low biodegradability. Exposure to these chemicals, along with growth of microorganisms and biocides used for microbial control, could lead to respiratory irritation, asthma, pneumonia, dermatitis, and even cancer. To address these concerns, extensive effort has been put forth to (1) extend the cutting fluid life span by removing particulates, free oils, and other contaminants via separation and filtration, (2) reformulate traditional petroleum-based fluids with vegetable oils and bio-based ingredients for lower toxicity and higher biodegradability, and (3) reduce or even eliminate the reliance on cutting fluids during machining through dry machining and minimum quantity lubrication (MQL) techniques. Apart from these technology developments, machining process parameters can be optimized for reduced environmental impacts, especially energy consumption and carbon footprint. Process optimization approaches require the development of models and equations to correlate process parameters with process inputs and outputs. Given the current status in the field, opportunities exist in designing new bio-based, microfiltration-compatible formulations using industrial by-products, optimizing minimum MQL system configuration, advancing cutting tool insert materials and lubricants for MQL, and developing high-energy efficiency machine tools.

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