An autonomous manufacturing system based on swarm of cognitive agents

Park, Hae‐Sim; Tran, Ngoc-Hien

doi:10.1016/j.jmsy.2012.05.002

Cited by 50 publications

(13 citation statements)

References 50 publications

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“…Agent, knowledge-based methods and autonomous discrete event simulation can be applied to realise production autonomy. Park and Tran (2012) presented an autonomous manufacturing system where work pieces, machines, robots and other resources are controlled by the corresponding cognitive agents. The system reacts to disturbances autonomously based on the reaction of each agent or on their cooperation.…”

Section: Cps/cpps and Autonomous Manufacturingmentioning

confidence: 99%

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Ding

Chan

Zhang

et al. 2019

International Journal of Production Research

328

106

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Smart manufacturing is the core idea of the fourth industrial evolution. For a smart manufacturing shop floor, real-time monitoring, simulation and prediction of manufacturing operations are vital to improve the production efficiency and flexibility. In this paper, the Cyber-Physical System (CPS) and Digital Twin technologies are introduced to build the interconnection and interoperability of a physical shop floor and corresponding cybershop floor. A Digital Twin-based Cyber-Physical Production System (DT-CPPS) is further established, and the configuring mechanism, operating mechanism and real-time data-driven operations control of DT-CPPS are discussed in detail. It is expected that DT-CPPS will provide the basis for shop floors to march towards smart manufacturing.

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Section: Cps/cpps and Autonomous Manufacturingmentioning

confidence: 99%

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Ding

Chan

Zhang

et al. 2019

International Journal of Production Research

328

106

View full text Add to dashboard Cite

show abstract

“…Finally, AI systems have been developed in such a way as to contain self-decision-making, self-adaption, and self-learning systems. The manufacturing literature, in particular, emphasizes these features of decision-making technology (e.g., Park & Tran, 2012;Zhou, 2013). However, non-human algorithms are affecting the outcomes, content, and order of issues in the search engines, portals, and social media all over the Web.…”

Section: Decision-making In Technologymentioning

confidence: 99%

Is coopetitive decision-making a black box? Technology and digitisation as decision-makers and drivers of coopetition

Rusko

2019

Technology Analysis & Strategic Management

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Coopetition-simultaneous cooperation-and competition are increasingly becoming popular approaches in business studies. However, coopetition discussions dominate the content of decision-making about coopetition activities. The decision-maker can be a black box, firm, or organization, which optimizes its decisions in the prevailing business environment. The role of technology in decision-making has also passed. Because of developing decision-support systems, it is crucial to understand who makes decisions about coopetition and how, and what is the relationship between human and non-human decision-makers. This study offers a typology, which describes the different degrees of technology in coopetition decisions.

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“…Delen & Pratt (2006) developed an intelligent decision support system for manufacturing systems (IDSS-MS), capable of providing structuring, analysis-tool selection, autonomic model generation and execution for a set of problem-symptoms. Finally, Park & Tran (2012) propose an autonomous manufacturing system based on a swarm of cognitive agents (AMS-SCA) in order to adapt to the disturbances autonomously based on the reaction of each agent or the Journal of Decision Systems 15 cooperation among them. While these approaches successfully produce an autonomic model for a complex manufacturing floor, they are limited by the fact that queries can only be posed against the entire model.…”

Section: Related Workmentioning

confidence: 99%

Autonomic smart manufacturing

Menascé

Krishnamoorthy

Brodsky

2015

Journal of Decision Systems

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Smart manufacturing (SM) systems have to optimise manufacturing activities at the machine, unit or entire manufacturing facility level as well as adapting the manufacturing process on the fly as required by a variety of conditions (e.g. machine breakdowns and/or slowdowns) and unexpected variations in demands. This paper provides a framework for autonomic smart manufacturing (ASM) that relies on a variety of models for its support: (1) a process model to represent machines, parst inventories and the flow of parts through machines in a discrete manufacturing floor;(2) a predictive queueing network model to support the analysis and planning phases of ASM; and (3) optimisation models to support the planning phase of ASM. In essence, ASM is an integrated decision support system for smart manufacturing that combines models of different nature in a seamless manner. As shown here, these models can be used to predict manufacturing time and the energy consumed by the manufacturing process, as well as for finding the machine settings that minimise the energy consumed or the manufacturing time subject to a variety of constraints using non-linear optimisation models. The diversity of models used affords different levels of integration and granularity in the decision-making process. An example of a car manufacturing process is used throughout the paper to explain the concepts and models introduced here.

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An autonomous manufacturing system based on swarm of cognitive agents

Cited by 50 publications

References 50 publications

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors

Is coopetitive decision-making a black box? Technology and digitisation as decision-makers and drivers of coopetition

Autonomic smart manufacturing

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