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.

Process Monitoring of Turning and Model Adaptation for Smart Machining Systems

Published

Author(s)

Jarred C. Heigel, Robert W. Ivester

Abstract

Smart Machining Systems improve manufacturing efficiency using optimization based on process models. Cutting force models developed from a narrow set of empirical data provide insight into the physical properties of cutting, but the extreme physical phenomena of metal cutting and practical limits on control of environment and material homogeneity, hinder predictability. In order to improve the practicality of model based decision making in an industrial machining environment, this paper introduces a method to adapt parameters of a traditional empirical model in response to on-line measures of process performance to cope with these practical limitations on process predictability. This method enables Smart Machines to self monitor production performance and adapts models and process parameters in response to uncontrollable disturbances, reducing the need for expensive empirical tests.
Citation
Journal of Manufacturing Systems
Volume
36
Issue
5

Keywords

Adaptation, In-Process Monitoring, Modeling, Smart Machining Systems, Uncertainty

Citation

Heigel, J. and Ivester, R. (2007), Process Monitoring of Turning and Model Adaptation for Smart Machining Systems, Journal of Manufacturing Systems, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=824635 (Accessed April 23, 2024)
Created September 3, 2007, Updated February 19, 2017