Multi-agent System for Cloud Manufacturing Process Planning

Sarkar, Arkopaul; Šormaz, Dušan

doi:10.1016/j.promfg.2018.10.067

Cited by 13 publications

(7 citation statements)

References 5 publications

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“…High computational capability can be utilised in cloud based platforms for employing reinforcement learning approach, that could aid in making highly effective distributed intelligence based decisions in manufacturing environment [21]. Further applications to this approach involve process planning [22] and dynamic task scheduling [15].…”

Section: Methodsmentioning

confidence: 99%

“…discovering and orchestrating services on demand [41] and running agent technology in the network or edge if needed [20]. The integration, of agents is also supported by standards.…”

Section: R Lu Et Al [27] : Multi-agent Deep Deterministic Policy Gradient (Maddpg) Algorithmmentioning

confidence: 99%

“…Some examples are XML language that formalizes knowledge base methods for queries and data storage [42] or RFID tags that provide opportunities for precise data acquisition [23]. Finally, semantic communication and in general ontologies and semantic web provide methods for data understanding, knowledge and automatic discovering of information [41].…”

Section: R Lu Et Al [27] : Multi-agent Deep Deterministic Policy Gradient (Maddpg) Algorithmmentioning

confidence: 99%

“…Here we are presenting some of the most relevant works in each application. Sarkar et al [41] proposed an agent framework for developing a generic planning agent based on Belief, Desire and Intention mechanism (BDI). The proposed model can be used for planning at any level of aggregation dimension.…”

Section: Applications Of Mas In Manufacturing [Rq3]mentioning

confidence: 99%

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Multi-agent based manufacturing: current trends and challenges

Pulikottil

Estrada-Jimenez

Rehman

et al. 2021

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )

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The advent of Industry 4.0 and the development of future industrial applications can be achieved using Cyber-Physical Systems (CPS). This technological development invokes high levels of communication and computation in the form of an interconnected network of industrial resources. Multi-agent systems precisely can empower such technological evolution by introducing properties like decentralisation, autonomy, flexibility, social ability and modularity to the industrial context. In this regard, the current work surveys recent multi-agent based manufacturing approaches and provides a general vision of current trends focusing on frameworks/architectures, complementary technologies and common applications. This article, ends with an integrated discussion of emerging agent-based industrial challenges, a general conclusion and final remarks.

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Section: Methodsmentioning

confidence: 99%

“…discovering and orchestrating services on demand [41] and running agent technology in the network or edge if needed [20]. The integration, of agents is also supported by standards.…”

Section: R Lu Et Al [27] : Multi-agent Deep Deterministic Policy Gradient (Maddpg) Algorithmmentioning

confidence: 99%

Section: R Lu Et Al [27] : Multi-agent Deep Deterministic Policy Gradient (Maddpg) Algorithmmentioning

confidence: 99%

Section: Applications Of Mas In Manufacturing [Rq3]mentioning

confidence: 99%

See 2 more Smart Citations

Multi-agent based manufacturing: current trends and challenges

Pulikottil

Estrada-Jimenez

Rehman

et al. 2021

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )

View full text Add to dashboard Cite

show abstract

“…An information delivery process, large-scale data analysis, and a cloud infrastructure services network underpin the entire system [14]. A system for cloud-based process planning using agents has been proposed [15]. Data collection units can collect data from machines and data collection units that provide detailed information about the machine.…”

Section: A Review Of Iot In Manufacturingmentioning

confidence: 99%

Internet of Things Based Cutting Tool Status Monitoring in a Computer Numerical Control Milling Machine

Natarajan¹,

Gokulachandran²

2021

Int. J. Adv. Sci. Eng. Inf. Technol.

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The Internet of Things (IoT) in the manufacturing industry shares machine data in real time. The majority of industrial data can be gathered and processed from machines and other remote IoT devices in a production system through data streaming. As sensors become smaller and more affordable, the Internet of things will attract more attention. It is possible to employ a wide range of sensors for monitoring, and with efficient open-source software, the status of the operation can be evaluated effectively. Our work aims at providing instructions for sending data (cutting tool status time) from Particle Photon devices connected to CNC milling machines to open-source software called ThingSpeak. This task is accomplished by integrating the Particle Photon device with the infrared sensor to the CNC milling machine. Three axis CNC vertical milling machine is used to manufacture the sample component. The status of the cutting tool, in this case the cutting time for each machining feature is monitored. Using infrared technology, the sensor detects whether the cutting tool is present. Particle photons measure machining time and communicate it to ThingSpeak. The ThingSpeak library will interpret the cloud information and displays it. With ThingSpeak software, we define the fields for various cutting tools and track every tool in real time. The time recorded using ThingSpeak software is found to be near to the time, which is monitored manually by the user. A major step in computer assisted process planning in manufacturing is monitoring the machining time for each cutting tool and it is successfully implemented in this research work.

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