Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Smart Machining Systems: Issues and Research Trends

Published

Author(s)

Laurent Deshayes, Lawrence A. Welsch, Alkan Donmez, Robert W. Ivester, David E. Gilsinn, Richard L. Rhorer, Eric P. Whitenton, Florian Potra

Abstract

Smart Machining Systems (SMS) should be an important part of Life Cycle Engineering (LCE) since its capabilities are: producing the first and every product correct; improving the response of the production system to changes in demand (just in time); realizing rapid manufacturing; and, providing data on an as needed basis. Thereby, SMS have to improve the performance of production systems and reduce production costs. In addition, an SMS not only has to improve a particular machining process, but it also has to determine the best optimized solution to produce the part faster, better, at lower cost, and with a minimum impact on the environment. In addition, new software tools are required to facilitate the improvement of a machining system, characterized by a high level of expertise or heuristic methods. A global approach requires integrating knowledge/information about the product design, production equipment and machining process. This paper first discusses the main characteristics and components which are envisioned to be part of SMS. Then, uncertainties associated with models and data and the optimization tasks in SMS are discussed. Robust Optimization is an approach for coping with such uncertainties in SMS. Current use of machining models by production engineers and associated problems are discussed. Finally, the paper discusses interoperability needs for integrating SMS into the product life cycle as well as the need for knowledge-based systems. The paper ends with a description of future research trends and work plans.
Proceedings Title
Proceedings of the 12th CIRP Seminar on Life Cycle Engineering
Conference Location
Grenoble, 1, FR

Keywords

Knowledge bases, Life Cycle Engineering, Ontologies, Robust Optimization, Smart Machining Systems

Citation

Deshayes, L. , Welsch, L. , Donmez, A. , Ivester, R. , Gilsinn, D. , Rhorer, R. , Whitenton, E. and Potra, F. (2005), Smart Machining Systems: Issues and Research Trends, Proceedings of the 12th CIRP Seminar on Life Cycle Engineering, Grenoble, 1, FR, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822255 (Accessed April 25, 2024)
Created December 31, 2004, Updated October 12, 2021