INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING

Published

December 10, 2015

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

Pub Type

Conferences

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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 January 24, 2025)