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Toward Smart Manufacturing Using Decision Guidance Analytics

Published

Author(s)

Alexander Brodsky, Mohan Krishnamoorthy, Daniel A. Menasce, Guodong Shao, Sudarsan Rachuri

Abstract

This paper is focused on decision analytics for smart manufacturing. We consider temporal manufacturing processes with stochastic throughput and inventories. We demonstrate the use of the recently proposed concept of the decision guidance analytics language to perform monitoring, analysis, planning, and execution tasks. To support these tasks we define the structure of and develop modular reusable process component models, which represent data, decision/control variables, computation of functions, constraints, and uncertainty. The tasks are then implemented by posing declarative queries of the decision guidance analytics language for data manipulation, what-if prediction analysis, decision optimization, and machine learning.
Proceedings Title
The 2014 IEEE International Congress on Big Data (BigData 2014) conference
Conference Dates
October 27-30, 2014
Conference Location
Washington DC, DC, US

Keywords

smart manufacturing, decision support, decision guidance, optimization, data analytics

Citation

Brodsky, A. , Krishnamoorthy, M. , Menasce, D. , Shao, G. and Rachuri, S. (2014), Toward Smart Manufacturing Using Decision Guidance Analytics, The 2014 IEEE International Congress on Big Data (BigData 2014) conference, Washington DC, DC, US (Accessed February 22, 2024)
Created October 31, 2014, Updated October 12, 2021