An Ontology for Production Control of Semiconductor Manufacturing Processes

Mönch, Lars; Stehli, Marcel

doi:10.1007/978-3-540-39869-1_14

Cited by 15 publications

(11 citation statements)

References 9 publications

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“…Based on a data model of the semiconductor manufacturing domain, we derive the important concepts activity, resource, order, product, event, plan, and schedule (cf. [5] for a detailed description).…”

Section: Fabmas Ontologymentioning

confidence: 99%

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An Ontology to Support Adaptive Agents for Complex Manufacturing Systems

Mönch

Zimmermann

2008

2008 32nd Annual IEEE International Computer Software and Applications Conference

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In this paper, we extend the FABMAS ontology towards its usage in adaptive production control systems for complex manufacturing systems. FABMAS is a hierarchically organized multi-agent-system for production control in the semiconductor manufacturing domain. It consists of decision-making and staff agents. Staff agents support the decision-making agents. We introduce adaptive staff agents. Adaptive staff agents make sure that the parameters of production control algorithms are properly adjusted in a situation-dependent manner. We derive necessary extensions of the FABMAS ontology based on the architecture of adaptive staff agents and their interaction with other agents of the manufacturing control system. We present an example for using the ontology within FABMAS.

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Section: Fabmas Ontologymentioning

confidence: 99%

“…FABMAS is a hierarchically organized multi-agent-system that is designed to allowing for production control of wafer fabs [2], [3]. The FABMAS ontology [5] was suggested to allow for a meaningful communication among the agents.…”

Section: Introductionmentioning

confidence: 99%

An Ontology to Support Adaptive Agents for Complex Manufacturing Systems

Mönch

Zimmermann

2008

2008 32nd Annual IEEE International Computer Software and Applications Conference

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“…In the approach, the top layer is an aggregated model obtained on-line; the intermediate layer consists of production optimisation and inventory control; the bottom layer consists of a distributed control policy. Mo¨nch and Stehli (2003) suggested an ontology that is an appropriate hierarchical control approach to coordinate the autonomous entities of the hierarchy. Hwang and Chang (2003) describe the design of a two-level hierarchical production scheduling engine which consists of a mid-term scheduler and a short-term scheduler, and are aimed at achieving coordination between the fab-wide objectives and local shop-floor operations.…”

Section: Literature Reviewmentioning

confidence: 99%

A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line

Yan

Wang

2012

International Journal of Production Research

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This study focuses on the dynamic scheduling problem of a re-entrant production line, in which all of the parts are assumed to have the same processing routes and be processed on every machine. A two-layer dynamic scheduling method is proposed for the dynamic scheduling of the re-entrant line with the objective of minimising total earliness and tardiness. This method consists of two layers. The top layer is to select the appropriate scheduling policy, and the bottom layer is to generate the scheduling by using the policy selected in the top layer. In the top layer, three different rules are constructed for selecting scheduling policies, namely the lateness comparison rule, the lateness variation comparison rule, and the equal interval switching rule. In the bottom layer, three different scheduling policies are proposed to generate the real-time scheduling for manufacturing, namely the FCFS (first come first service) scheduling policy, the PI (proportional-integral) scheduling policy, and the fuzzy PI scheduling policy. Considering that the real-time status of manufacturing changes constantly, it is necessary to switch among different scheduling policies to adapt to this change. Numerical experiments are performed in the situations with and without urgent jobs. The results show that the proposed two-layer dynamic scheduling method outperforms any single scheduling policy (e.g., the FCFS policy, the PI policy and the fuzzy PI policy) for the dynamic scheduling of a re-entrant production line.

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“…A specific ontology (Mo¨nch and Stehli 2003) and content language (Mo¨nch and Stehli 2004) for production control in the semiconductor manufacturing domain are developed. The ontology contains more than 100 domain concepts and takes into account the hierarchical production control approach.…”

Section: Case Study: Fabmasmentioning

confidence: 99%

ManufAg: a multi-agent-system framework for production control of complex manufacturing systems

Mönch

Stehli

2005

ISeB

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In this paper, we present a framework for the implementation of multi-agent-systems for production control of complex manufacturing systems. We present the results of a requirement analysis for production control systems for complex manufacturing systems; then we describe the framework design criteria. Our framework supports the inclusion of distributed hierarchical decision-making schemes into the production control. Furthermore, in order to increase the coordination abilities of multi-agent-systems, we follow the decision-making and staff agent architecture suggested in the PROSA reference architecture. We indicate the usage of the framework for designing and implementing an agent-based production control system for semiconductor manufacturing processes in a case study.

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An Ontology for Production Control of Semiconductor Manufacturing Processes

Cited by 15 publications

References 9 publications

An Ontology to Support Adaptive Agents for Complex Manufacturing Systems

An Ontology to Support Adaptive Agents for Complex Manufacturing Systems

A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line

ManufAg: a multi-agent-system framework for production control of complex manufacturing systems

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