Hybrid Discrete Event Simulation with Model Predictive Control for Semiconductor Supply-chain Manufacturing

Sarjoughian, Hessam S.; Huang, Dongping; Godding, Gary W.; Wang, Wenlin; Rivera, Daniel E.; Kempf, Karl G.; Mittelmann, Hans D.

doi:10.1109/wsc.2005.1574259

Cited by 16 publications

(21 citation statements)

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“…Since 1995, several papers on hybrid modeling have been published, most of them used in new directions, such as optimization [10] and system behavior analysis, like supplychain management [11]. Recent hybrid modeling approaches exist for network processor design [12] and to combine software design evaluation with network specific architecture in [13], where analytical and simulation solution procedures are applied one after the other iteratively.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Analytical-Simulation Model Used to Evaluate and Improve System Performance

Chise¹,

Jurca

2011

2011 10th International Symposium on Parallel and Distributed Computing

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Performance prediction has been intensively studied in the last decade, alongside the accelerated development of distributed systems. This paper focuses on a hybrid approach regarding model solving, combining two popular prediction techniques applied separately so far, analytical and simulation modeling, in order to benefit from the strengths of both. The input UML model with MARTE (Modeling and Analysis of Real-time and Embedded systems) annotations is transformed into a hierarchically decomposed performance model, and performance results for simulated submodels are used by an analytical solver. The validation of the proposed method is to be performed with a tool called PHYMSS (Performance Hybrid Model Solver and Simulator) developed by the authors that implements both the hybrid solver and a multithreaded simulator.

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Section: Related Workmentioning

confidence: 99%

Hybrid Analytical-Simulation Model Used to Evaluate and Improve System Performance

Chise¹,

Jurca

2011

2011 10th International Symposium on Parallel and Distributed Computing

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“…To model the interactions between models that are described in disparate modeling formalisms, the Knowledge Interchange Broker (KIB) approach has been introduced [6]- [8]. As a multiformalism model composability framework, input/output mappings, synchronization, concurrency, and timing properties for models can be described at the level of modeling formalisms [9].…”

Section: Simulation Of Semiconductor Manufacturingmentioning

confidence: 99%

“…To have a composable simulation testbed for semiconductor supply-chain systems, a hybrid DEVS/MPC with KIB has been developed [8], [10]. This testbed supports composing Discrete EVent System specification (DEVS) [11] and model predictive control (MPC) [12] models.…”

Section: Simulation Of Semiconductor Manufacturingmentioning

confidence: 99%

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Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB

Huang

Sarjoughian

Wang

et al. 2009

IEEE Trans. Semicond. Manufact.

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The dynamics of high-volume discrete-part semiconductor manufacturing supply-chain systems can be described using a combination of Discrete EVent System Specification (DEVS) and model predictive control (MPC) modeling approaches. To formulate the interactions between the discrete process model and its controller, another model called Knowledge Interchange Broker (KIB) is used. A robust and scalable testbed supporting DEVS-based manufacturing process modeling, MPC-based controller design, and the KIB DEVS MPC interaction model is developed. A suite of experiments have been devised and simulated using this testbed. The flexibility of this approach for modeling, simulating, and evaluating stochastic discrete process models under alternative control schemes is detailed. The testbed illustrates the benefits and challenges associated with developing and using realistic manufacturing process models and process control policies. The simulation environment demonstrates the importance of explicitly defining and exposing the interactions between the manufacturing and control subsystems of complex semiconductor supply-chain systems.Index Terms-Discrete-event system specification, hybrid simulation testbed, Knowledge Interchange Broker (KIB), model composability, model predictive control, optimization, semiconductor manufacturing, supply-chain management.

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“…Simulation research has been found in a Wang, Ingham: A Discrete-Event Modelling Approach for Supply Chain Simulation wide range of application areas such as a manufacturing supply chain [27], construction supply chain [28] and semiconductor supply chain [29] etc. If the future were predictable then managing a supply chain would be straightforward.…”

Section: Simulationmentioning

confidence: 99%

A discrete event modelling approach for supply chain simulation

Wang¹,

Ingham²

2008

Int. j. simul. model.

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In today's competitive environment, companies face increasingly diverse challenges. To survive in the next millennium, they need to improve their profit margins by cutting capital costs and creating more responsive and adaptable supply chains to meet the ever changing market demand. This paper aims to investigate how dynamic simulation tools can be used to improve and optimise supply chain performance. The general overview of the supply chain is first introduced, the importance of order release mechanisms is examined and its use as a performance measure to monitor the supply chain is proposed. Simulations were developed to investigate the customer/manufacturer relationship of the supply chain. After the running of the trials a diagnostic evaluation was formed. With the simulation results analysed, significant improvements in lowering inventory costs, increasing output and fulfilling orders on time were achieved.

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Hybrid Discrete Event Simulation with Model Predictive Control for Semiconductor Supply-chain Manufacturing

Cited by 16 publications

References 0 publications

Hybrid Analytical-Simulation Model Used to Evaluate and Improve System Performance

Hybrid Analytical-Simulation Model Used to Evaluate and Improve System Performance

Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB

A discrete event modelling approach for supply chain simulation

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