Operation allocation and part type selection in E-manufacturing: An auction based heuristic supported by agent technology

Tiwari, Manoj Kumar; Jha, Sujit Kumar; Anand, Raj Bardhan

doi:10.1016/j.rcim.2009.11.009

Cited by 15 publications

(4 citation statements)

References 43 publications

(37 reference statements)

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“…Basically, E-manufacturing integrates customers, e-commerce systems, and suppliers with manufacturing process to provide an Internet-based strategic framework for the factory [35][36][37][38][39][40].…”

Section: Inteligent E-manufacturing Control Systemmentioning

confidence: 99%

Implementation of Web based Technique into the Intelligent Manufacturing System

Mostafaeipour¹,

Roy²

2011

IJCA

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Intelligent Manufacturing System (IMS) shall be considered as a system integrated with different intelligent subsystems, which completes the distributed solution procedure on the basis of exchanging large quantities of materials, energy and information. Any intelligent manufacturing process selfregulates and self-controls itself in manufacturing the products within the design specifications. It incorporates introduction of human-like decision-making capabilities into the manufacturing system that brings the intelligence. The system however requires complete information of the requirements and processing of production system to generate appropriate decisions. This paper provides a comprehensive review of research on web-enabled e-Manufacturing technology which bridges certain aspects of manufacturing system like Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and Supply Chain Management (SCM). Web-based systems have been implemented to provide remote service and manufacturing for rapid prototyping, enhance the availability of facilities and improve the capability of rapid product development for various enterprises. Web-based technique is utilized to derive the availability of information anytime, anywhere and by the persons who are authorized to deal with it. The eManufacturing production system can substantially reduce product cost and delivery cycle for manufacturing systems.

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Section: Inteligent E-manufacturing Control Systemmentioning

confidence: 99%

Implementation of Web based Technique into the Intelligent Manufacturing System

Mostafaeipour¹,

Roy²

2011

IJCA

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“…In recent years multi-agent systems (MAS) have gained tremendous popularity in providing solution to the distributed decision making problems in different domains of industrial life. Some of the examples are multi-plant production scheduling (Alvarez, 2007); real-time distributed manufacturing and control (Leitao, 2009;Jason et al, 2011); e-manufacturing (Tiwari et al, 2010); dynamic supply chain (Wang et al, 2009); bus maintenance scheduling (Zhou et al, 2004), etc. The term agent in MAS refers to a software entity which is autonomous, proactive, social (Sandholm, 2001;Wooldridge, 2009) and having its own execution environment and decision powers.…”

Section: Introductionmentioning

confidence: 99%

A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach

Adhau¹,

Mittal²,

Mittal³

2012

Engineering Applications of Artificial Intelligence

115

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“…Several dedicated sites targeting ordinary individuals have already been emerged and this population is growing at a rapid rate. Auction protocols that have been used in supply chain management, distributed multi project scheduling, e-manufacturing, and allocation of loads in transportation logistics [1][2][3][4] are becoming more popular among ordinary individuals.…”

Section: Introductionmentioning

confidence: 99%

A method for detecting agents that will not cause emergent behavior in agent based systems - A case study in agent based auction systems -

Fard

Far

2012

2012 IEEE 13th International Conference on Information Reuse &Amp; Integration (IRI)

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Modeling and implementing auction systems using agent technology is a common practice because agents can assume various roles and their behavior will be determined as a result of negotiation. However, emergent behavior is a hurdle. Mechanisms must be in place to make sure that agents participating in the auction systems won't behave in an unintended way. Detecting emergent behaviors in the design phase rather than the deployment is more cost and effort efficient. Patterns of interaction, called scenarios, are the basic modeling constructs for design and behavioral modeling of agents. However, working with several agents in an online auction system needs large number of scenarios. Therefore transforming scenarios to finite state machines (FSM) and parallel execution of the FSMs in the behavioral synthesis phase may lead to computational overload. So far all the research has been around the ways of detecting emergent behavior and scalability of behavioral modeling has been an issue. In this paper a method to identify those agents that will not cause emergent behavior is introduced. Then by eliminating them from the behavioral modeling phase, the number of FSMs and their states will be reduced. The method is explained along with a case study of a realistic online auction system that has led to 33% reduction of synthesized FSMs.

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Operation allocation and part type selection in E-manufacturing: An auction based heuristic supported by agent technology

Cited by 15 publications

References 43 publications

Implementation of Web based Technique into the Intelligent Manufacturing System

Implementation of Web based Technique into the Intelligent Manufacturing System

A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach

A method for detecting agents that will not cause emergent behavior in agent based systems - A case study in agent based auction systems -

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