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A System and Architecture for Reusable Abstractions of Manufacturing Processes

Published

Author(s)

Alexander Brodsky, Mohan Krishnamoorthy, William Z. Bernstein, M. Omar Nachawati

Abstract

In this paper we report on the development of a system for managing a repository and conducting analysis and optimization on manufacturing performance models. The repository is designed to contain (1) unit manufacturing process performance models, (2) composite performance models representing production cells, lines, and facilities, (3) domain specific analytical views, and (4) ontologies and taxonomies. Initial implementation includes performance models for milling and drilling as well as a composite performance model for machining. These performance models formally capture (1) the metrics of energy consumption, CO2 emissions, tool wear and tear, and cost as a function of process controls and parameters, and (2) the process feasibility constraints. The initial scope of the system includes (1) an Integrated Development Environment and its interface, and (2) simulation and deterministic optimization of performance models through the use of Unity Decision Guidance Management System.
Proceedings Title
2016 IEEE International Conference on Big Data (Big Data 2016)
Conference Dates
December 5-8, 2016
Conference Location
Washington, DC, US

Keywords

Knowledge Base, Unit Manufacturing Processes, Repository, Optimization, Reusable Manufacturing Models

Citation

Brodsky, A. , Krishnamoorthy, M. , Bernstein, W. and Nachawati, M. (2017), A System and Architecture for Reusable Abstractions of Manufacturing Processes, 2016 IEEE International Conference on Big Data (Big Data 2016), Washington, DC, US, [online], https://doi.org/10.1109/BigData.2016.7840823 (Accessed March 1, 2024)
Created June 1, 2017, Updated October 12, 2021