Optimal design of batch‐storage network using periodic square wave model

Yi, Gyeongbeom; Reklaitis, Gintaras V.

doi:10.1002/aic.690480815

Cited by 18 publications

(17 citation statements)

References 12 publications

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“…Note that the sets of suppliers K(j) and consumers M(j) are storage dependent. The material flow from process to storage unit (or from storage unit to process) is represented by the periodic square wave (PSW) model, as shown in Figure 5 in Yi and Reklaitis (2002). In the PSW model, material flow is represented in terms of four variables: batch size, cycle time i , storage operation time fraction x i in (or x i out ), and startup time t i in (or t i out ).…”

Section: Definition Of Variables and Parameterssupporting

confidence: 45%

“…where D is the average flow rate, B is the batch size, is the cycle time, tЈ is the startup time, x is the storage operation time fraction, and t is time (Yi and Reklaitis 2002). Note that D ϭ B/.…”

Section: Definition Of Variables and Parameterssupporting

confidence: 38%

“…Yi and Reklaitis (2000) developed a novel production and inventory analysis method called the periodic square wave (PSW) method, and used it to determine the optimal design of a parallel batch-storage system. They subsequently extended the PSW formalism to model the more complicated plant structure of a sequential multistage batch-storage network (Yi and Reklaitis, 2002). In another study (Yi and Reklaitis, 2003), the same authors suggested a nonsequential network structure that can deal with recycled material flows in a plant site.…”

Section: Introductionsupporting

confidence: 40%

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Optimal design of batch‐storage network with financial transactions and cash flows

Reklaitis

2004

AIChE Journal

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Section: Definition Of Variables and Parameterssupporting

confidence: 45%

Section: Definition Of Variables and Parameterssupporting

confidence: 38%

Section: Introductionsupporting

confidence: 40%

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Optimal design of batch‐storage network with financial transactions and cash flows

Reklaitis

2004

AIChE Journal

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“…In this study, the complex supply chain network is represented by a batch-storage network [12][13][14][15][16][17][18][19][20][21] that covers most supply chain structural components, for example, raw material purchasing, production, transportation, and finished product demand. The batch-storage network model introduced in this article extends our previous work 21 to include multitasking semicontinuous production processes which allow us to represent commodity polymer supply chain network.…”

Section: Introductionmentioning

confidence: 49%

Optimal Design of Generalized Batch‐Storage Network Considering Shortage Costs

Reklaitis²

2013

AIChE Journal

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Product shortages, which cause backlogging and/or lost sales costs commonly occur in the chemical industries, especially in the commodity polymer business. Shortage costs in a supply chain optimization model are studied under the framework of a generalized batch-storage network. A classical economic order quantity model with backlogging costs suggested an optimal time delay and final product delivery lot size. A product shortage can be mitigated by advancing production/transportation or by purchasing a substitute product from a third party as well as by a product delivery delay in the supply chain network. Optimal solutions that consider all means for recovering shortage are more complicated than the classical case. Four solutions are identified depending on the parametric range and variable bounds. The optimal capacity for production/transportation processes associated with a product in shortage can differ from that of a product not in shortage. An illustrative example is presented in support of the analytical results.

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“…The optimal design of a batch-storage network was previously studied using the periodic square wave (PSW) model. [11][12][13][14][15] In the present study, waste treatment processes are added to the network. As shown in Figure 1, off-spec materials produced from failed batches are collected into a storage unit and then, depending on economic factors, are either regenerated into feedstock materials through a process or disposed of to outside sinks.…”

mentioning

confidence: 44%