Multi‐objective optimization for cost‐efficient and resilient machining under tool wear

Wilson, James P.; Shen, Zongyuan; Awasthi, Utsav; Bollas, George M.; Gupta, Shalabh

doi:10.1002/amp2.10140

Multi‐objective optimization for cost‐efficient and resilient machining under tool wear

Journal Article · Tue Aug 09 00:00:00 EDT 2022 · Journal of Advanced Manufacturing and Processing

DOI:https://doi.org/10.1002/amp2.10140· OSTI ID:1893172

^[1]; Shen, Zongyuan ^[1]; Awasthi, Utsav ^[2]; ^[2]; Gupta, Shalabh ^[1]

Department of Electrical and Computer Engineering University of Connecticut Storrs Connecticut USA
Department of Chemical and Biomedical Engineering University of Connecticut Storrs Connecticut USA

Abstract

With the onset and rapid growth of smart manufacturing, there is a constant increase in the demand for automation technologies to enhance productivity while providing uninterrupted, cost‐efficient, and resilient machining. Traditional manufacturing systems, however, suffer from several losses due to machine faults and degradation. Specifically, tool wear directly impacts the precision and quality of the milled parts, which causes an increase in the scrap production. Hence, more attempts are required to meet the desired quota of successful parts, which in turn results in wasted material, longer delays, further tool degradation, and higher energy, machining, and labor costs. As such, this paper develops a multi‐objective optimization framework to generate the optimal control set points (e.g., feed rate and width of cut) that minimize the total cost of machining operations resulting from multiple contradictory cost functions (e.g., material, energy, tardiness, machining, labor, and tool) in the presence of tool wear. Notably, we estimate the total expected cost in dollars, which provides automatic and intuitive weighting in this multi‐objective formulation. The optimization framework is tested on a high‐fidelity face milling model that has been validated on real data from industry. Results show significant dollar savings of up to as compared to the default control scheme.

View Accepted Manuscript (Publisher)

Sponsoring Organization:: USDOE

Grant/Contract Number:: EE0007613

OSTI ID:: 1893172

Journal Information:: Journal of Advanced Manufacturing and Processing, Journal Name: Journal of Advanced Manufacturing and Processing Journal Issue: 4 Vol. 4; ISSN 2637-403X

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: United States

Language:: English

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