Dynamic schedule execution in an agent based holonic manufacturing system

Jana, Tarun Kanti; Bairagi, Bipradas; Paul, Soumen; Sarkar, Bijan; Saha, J.

doi:10.1016/j.jmsy.2013.07.004

Cited by 44 publications

(21 citation statements)

References 46 publications

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“…It offers a simple and general mechanism for solving coordination of manufacturing entities, and thus it was included in manufacturing planning, scheduling, reconfiguration and control schemes [22][23][24][25]. However, CNP in its original form can conduct to several drawbacks with respect to the optimality and completeness of provided results and thus different extensions of CNP were proposed; some of these improvements are reviewed in [25].…”

Section: Related Work; Proposed Research Goalsmentioning

confidence: 99%

Holonic coordination obtained by joining the contract net protocol with constraint satisfaction

Pănescu

Pascal

2016

Computers in Industry

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Section: Related Work; Proposed Research Goalsmentioning

confidence: 99%

Holonic coordination obtained by joining the contract net protocol with constraint satisfaction

Pănescu

Pascal

2016

Computers in Industry

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“…Resources also transform from hitherto competitive attitude to a cooperative attitude to solve the problem collectively. The communication among the system entities is envisaged to be established by client-server model using J2EE technology (Jana et al 2013).…”

Section: System Supervisormentioning

confidence: 99%

“…Agents exhibit two contradictory properties: under normal situation, they are highly competitive and vie with each other for lucrative jobs to augment their earnings and credentials, but when disturbances try to cripple the system, agents resort to cooperation (Jana et al 2013). Under an abnormal situation, agents metamorphose (Wang et al, 1998;Balasubramanian et al 2001) into the new environments so as to retain their sangfroid by providing solution and to get rid of the crisis.…”

Section: Introductionmentioning

confidence: 99%

Handling machine breakdown for dynamic scheduling by a colony of cognitive agents in a holonic manufacturing framework

Jana¹,

Naskar²,

Paul³

et al. 2015

10.5267/j.dsl

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There is an ever increasing need of providing quick, yet improved solution to dynamic scheduling by better responsiveness following simple coordination mechanism to better adapt to the changing environments. In this endeavor, a cognitive agent based approach is proposed to deal with machine failure. A Multi Agent based Holonic Adaptive Scheduling (MAHoAS) architecture is developed to frame the schedule by explicit communication between the product holons and the resource holons in association with the integrated process planning and scheduling (IPPS) holon under normal situation. In the event of breakdown of a resource, the cooperation is sought by implicit communication. Inspired by the cognitive behavior of human being, a cognitive decision making scheme is proposed that reallocates the incomplete task to another resource in the most optimized manner and tries to expedite the processing in view of machine failure. A metamorphic algorithm is developed and implemented in Oracle 9i to identify the best candidate resource for task re-allocation. Integrated approach to process planning and scheduling realized under Multi Agent System (MAS) framework facilitates dynamic scheduling with improved performance under such situations.

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“…When the studies in literature are investigated, MCDM techniques are grouped under 15 topics: Energyenvironment-sustainability, supply chain management, material, quality management, Geographic Information Systems (GIS), construction and project management, safety and risk management, manufacturing systems, technology management, operation research and soft computing, strategic management, knowledge management, production management, tourism management and the other fields [2]. For MCDM techniques, there are a lot of studies in the area of material science [3][4][5][6][7][8], production technologies [9], mass production [10], infrastructures [11], manufacturing systems [12], global production [13] and production strategies [14]. There is a large volume of published studies in MCDM for manufacturing and material science.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations

Sofuoğlu

Orak

2017

ijisae

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Abstract:Multi criteria decision making models (MCDM) are extensively used in material and process selection in engineering. In this study, a novel hybrid decision making model is developed. Best-Worst method (BWM) is hybridized with TOPSIS, Grey Relational Analysis (GRA) and Weighted Sum Approach (WSA). Developed hybrid models produce similar results in different weight value of decision makers so they are combined. The model is tested in a turning operation and an optimization study is conducted by using Taguchi experimental design. The developed model can be used by engineers and operators in manufacturing environment.

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Dynamic schedule execution in an agent based holonic manufacturing system

Cited by 44 publications

References 46 publications

Holonic coordination obtained by joining the contract net protocol with constraint satisfaction

Holonic coordination obtained by joining the contract net protocol with constraint satisfaction

Handling machine breakdown for dynamic scheduling by a colony of cognitive agents in a holonic manufacturing framework

A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations

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