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

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

doi:10.1109/tsm.2008.2011680

Cited by 22 publications

(12 citation statements)

References 20 publications

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“…The use of efficient management techniques will allow the reduction of production cost, inventory, supplying and service costs in each process (Eshlaghy & Razavi, 2011). In some companies, the incorporation of management techniques represented cost savings of 5-6 % (Huang et al, 2009).…”

Section: Mpc Application In Supply Chainsmentioning

confidence: 99%

“…Within semiconductors manufacturing supply chains, Huang et al (2009) presented a testbed that integrates DEVS (Discrete EVent System Specification), MPC and KIB (Knowledge Interchange Broker) in a scalable and robust manner. The testbed was evaluated with different experiments, showing the benefits and challenges related to using and developing of manufacturing processes realistic models and processes control policies.…”

Section: Forest-based Supply Chainmentioning

confidence: 99%

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Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

et al. 2015

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Aim of study: This work aims to provide an overview of Model Predictive Controllers (MPC) applications in supply chains, to describe the forest-based supply chain and to analyse the potential use and benefits of MPC in a case study concerning a biomass supply chain.Area of study: The proposed methods are being applied to a company located in Finland.Material and methods: Supply chains are complex systems where actions and partners’ coordination influence the whole system performance. The increase of competitiveness and need of quick responses to the costumers implies the use of efficient management techniques. The control theory, particularly MPC, has been successfully used as a supply chain management tool. MPC is able to deal with dynamic interactions between the partners and to globally optimize the supply chain performance in the presence of disturbances. However, as far as is authors’ knowledge, there are no applications of this methodology in the forest-based supply chains. This work proposes a control architecture to improve the performance of the forest supply chain. The controller is based on prediction models which are able to simulate the system and deal with disturbances.Main results: The preliminary results enable to evaluate the impacts of disturbances in the supply chain. Thus, it is possible to react beforehand, controlling the schedules and tasks’ allocation, or alert the planning level in order to generate a new plan.Research highlights: Overview of MPC applications in supply chains; forest-based supply chain description; case study presentation: wood biomass supply chain for energy production; MPC architecture proposal to decrease the operation times.Keywords: biomass; forest; Model Predictive Control; planning; supply chain.

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Section: Mpc Application In Supply Chainsmentioning

confidence: 99%

Section: Forest-based Supply Chainmentioning

confidence: 99%

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

et al. 2015

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“…To achieve model composability, the main goal centers on having appropriate concepts and methods to compose different model types such that both the disparate models and their interactions can be described using model abstractions with proper syntax and semantics. The composed models must be specified correctly-i.e., (i) correctness is ensured according to the domain-neutral modeling formalism of each subsystem model and (ii) validation is ensured according to the domain-specific model descriptions (Mayer et al 2006;Huang et al 2009;Godding et al 2007). Once the subsystems are formally defined, an interaction model can be developed to explicitly model the interaction.…”

Section: Polyformalism Model Compositionmentioning

confidence: 99%

“…Engineering researchers have been developing useful and practical concepts, techniques, and tools to support hybrid modeling for embedded devices (e.g., Karsai et al 2004) and manufacturing and planning enterprises (e.g., Huang et al 2009). In natural sciences, research in hybrid modeling (e.g., social-ecological systems) is relatively new.…”

mentioning

confidence: 99%

Managing Hybrid Model Composition Complexity: Human–Environment Simulation Models

Sarjoughian

Mayer

Ullah

et al. 2015

Concepts and Methodologies for Modeling and Simulation

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It is becoming commonplace to use multiple types of models together for simulating multifaceted systems across many scientific disciplines. Indeed, in recent years, some approaches (referred to as multimodeling or multiformalism modeling) have been developed for representing a complex system as a set of subsystem models. Among these, there has been an interest in developing hybrid methods where structures and behaviors of models are explicitly accounted for. Furthermore, theories and approaches are proposed to define the interactions among heterogeneous model types. However, modeling a system this way brings about composition complexity that must also be managed. The complexities of hybrid modeling resulting from the interactions of the composed models can be reduced using interaction models, an approach referred to as polyformalism modeling (Sarjoughian 2006). Independently developing and utilizing such interaction models provides additional flexibility in system model design, modification, and execution for both the subsystem models and the resultant hybrid system model.

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“…Therefore, some researchers propose treating a supply chain as a complex adaptive system (CAS) in order to understand how the supply chain adapts to and co-evolves with the dynamic environment in which it exists [5]. All relevant aspects involved in a specific problem are considered and integrated into a systematic model, and suitable methodologies and tools from the systems engineering discipline are applied to deal with the complexity directly, such as systems architecture analysis [6], system dynamics [7], [8], and system simulation [9]- [11]. Agent-based modeling (ABM), one of simulation-based modeling methods, captures many of the challenges facing contemporary supply chain practices by dynamic modeling of the behaviors of firms and other entities in a supply chain [12].…”

mentioning

confidence: 99%

Evolutionary Location and Pricing Strategies in Competitive Hierarchical Distribution Systems: A Spatial Agent-Based Model

Cheng

Dong

et al. 2014

IEEE Trans. Syst. Man Cybern, Syst.

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Facing horizontal channel competition in a hierarchical distribution system, independent intermediaries such as wholesalers and retailers are keen to find the optimal location and pricing strategies that enable them to adapt to the increasingly competitive business environment. To help market intermediaries to address their challenges, we propose in this paper a spatial agent-based model (SAM), grounded in complex adaptive systems, which comprises four types of agents, namely the world, the manufacturer, firms, and consumers. We derive the firms' optimal behaviors in response to competition by evaluating the evolutionary location and pricing strategies using a genetic algorithm. We observe that a pyramid structure and the bullwhip effect in demand emerge from the evolutionary behavior of the SAM. We also find that buyers' searching ability enhanced by information technology has a significant effect on the degree of competition in a hierarchical distribution system. In addition, we find that firms that distribute elastic goods are likely to lower their prices to attract more buyers and move closer to their suppliers to save transport costs. In the case that the product demand is inelastic, intermediaries will move as close to their buyers as possible because they can maximize their profits in the SAM.Index Terms-Agent-based modeling, competitive location problem, complex adaptive system, hierarchical distribution system, location and pricing.

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

Cited by 22 publications

References 20 publications

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

Managing Hybrid Model Composition Complexity: Human–Environment Simulation Models

Evolutionary Location and Pricing Strategies in Competitive Hierarchical Distribution Systems: A Spatial Agent-Based Model

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