Smart manufacturing, manufacturing intelligence and demand-dynamic performance

By Jim Davis, Thomas F. Edgar, James Porter, J. Bernaden, Michael Sarli. Computers and Chemical Engineering, 2012

718 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/fab482240b9062e9313ad34cc532df836cdde7db

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In Control and Systems Engineering

In Industrial and Manufacturing Engineering

Citations in the corpus

Managerial challenges of Industry 4.0: an empirically backed research agenda for a nascent field (2018, background): “…and platform models, which enable firms to reduce development and deployment costs for software, share IT resources and access dedicated manufacturing software applications that facilitate (joint product and process) innovations (Davis et al. 2012; Holtewert et al. 2013; Papazoglou et al. 2015).”
Health-aware hierarchical control for smart manufacturing using reinforcement learning (2017, background): “and maintenance and replacement decisions than is seen in traditional environments [13].”
A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0 (2016, background): “Most of the new factory concepts share attributes of smart networking (Dolgui and Proth 2010; Ivanov, Sokolov, and Pavlov 2013; Chick, Huchzermeier, and Netessine 2014; Davis et al. 2012; Villa, O ’ Brien, and Burlat 2012).”
A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs- A review and empirical investigation (2020, methodology): “…ability to execute real-time job scheduling (Saif et al., 2019; Fan et al., 2019; Framinan et al., 2019) real-time design and engineering changes (Davis et al., 2012), real-time monitoring of customer orders (Qu et al., 2019; Petrillo et al., 2019), and real-time supply status of products (Longo…”
Design Principles for Industrie 4.0 Scenarios (2016, background): “Further similar ideas can be found under the terms “Integrated Industry” [19], “Smart Industry”, or “Smart Manufacturing” [20] [21] [22].”
Literature review on the ‘Smart Factory’ concept using bibliometric tools (2017, methodology): “The second component is developing around the paper of Davis et al. (2012), i.e. node 2, describing the Smart Manufacturing landscape from the political and economic point of view, along with the efforts to accelerate the process of adoption of the Smart Factory in the US.”
A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, background): “Precisely, the authors propose a modular Smart Manufacturing approach [108], where autonomous modules execute high-level tasks without human control, deciding among a set of alternative actions, and responding to failures or unexpected events without affecting the work of other modules (thus…”
New IT Driven Service-Oriented Smart Manufacturing: Framework and Characteristics (2019, background): “dite new and greater development of manufacturing [8].”