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INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING

Published

Author(s)

Deogratias Kibira, Qais Y. Hatim, Guodong Shao, Soundar R. Kumara

Abstract

Modern manufacturing systems are installed with smart systems such as sensors that monitor performance and collect data in order to manage uncertainties in their operations. However, multiple parameters and variables affect system performance making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of data collected is beyond simulation analysis alone to guide decision making. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs. System optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also discusses candidate standards and gaps in existing standards for data collection, simulation, and systems interfaces.
Proceedings Title
Proceedings of the 2015 Winter Simulation Conference
Conference Dates
December 6-9, 2015
Conference Location
Huntington Beach, CA
Conference Title
2015 Winter Simulation Conference

Keywords

Data collection, data analytics, system parameters, system performance, simulation optimization, interface standards

Citation

Kibira, D. , Hatim, Q. , Shao, G. and Kumara, S. (2015), INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING, Proceedings of the 2015 Winter Simulation Conference, Huntington Beach, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=918497 (Accessed April 14, 2024)
Created December 10, 2015, Updated February 19, 2017