Process analytics formalism for decision guidance in sustainable manufacturing

Alexander Brodsky, Guodong Shao () and Frank Riddick
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Alexander Brodsky: George Mason University
Guodong Shao: Engineering Laboratory, National Institute of Standards and Technology
Frank Riddick: Engineering Laboratory, National Institute of Standards and Technology

Journal of Intelligent Manufacturing, 2016, vol. 27, issue 3, No 6, 580 pages

Abstract: Abstract This paper introduces National Institute of Standards and Technology (NIST)’s Sustainable Process Analytics Formalism (SPAF) to facilitate the use of simulation and optimization technologies for decision support in sustainable manufacturing. SPAF allows formal modeling of modular, extensible, and reusable process components and enables sustainability performance prediction, what-if analysis, and decision optimization based on mathematical programming. SPAF models describe (1) process structure and resource flow, (2) process data, (3) control variables, and (4) computation of sustainability metrics, constraints, and objectives. This paper presents the SPAF syntax and formal semantics, provides a sound and complete algorithm to translate SPAF models into formal mathematical programming models, and illustrates the use of SPAF through a manufacturing process example.

Keywords: Process analytics; Decision guidance; Sustainable manufacturing; Optimization; What-if analysis (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10845-014-0892-9

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