Determining the fabrication runtime for a buyer-vendor system with stochastic breakdown, accelerated rate, repairable items, and multi-delivery strategy

Chiu, Singa Wang; You, Liang; Sung, Peng Cheng; Wang, Yunsen

doi:10.5267/j.ijiec.2020.6.002

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…In addition, our model's utilization drops 60.7% compared to a model without using uptime-reduction strategies (Chiu et al, 2020). For a 33.25%, 41.16%, and 60.7% utilization decline, we are paying the prices of a 3.83%, 7.58%, and 14.91% increase in E[TCU(t1Z*)], respectively.…”

Section: The Effect Of Uptime-reduction Strategiesmentioning

confidence: 88%

“…For α1 = 0.5 (as our example assumes), utilization drops 33.25%, from 0.2811 (without overtime option) to 0.1876.Implementing dual uptime-reduction strategies (namely, the options of overtime and outsourcing) creates significant utilization decline. Fig.9displays the outcome of a further analysis comparing our utilization with closely-relating models.In addition, our model's utilization drops 60.7% compared to a model without using uptime-reduction strategies(Chiu et al, 2020). For a 33.25%, 41.16%, and 60.7% utilization decline, we are paying the prices of a 3.83%, 7.58%, and 14.91% increase in E[TCU(t1Z*)], respectively.…”

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confidence: 88%

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Minimizing operating expenditures for a manufacturing system featuring quality reassurances, probabilistic failures, overtime, and outsourcing

Chiu¹,

Chiu²,

Pai³

et al. 2023

10.5267/j.ijiec

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Production management operating in recent competitive marketplaces must satisfy the client desired quality and shorter order lead-time and avoid internal fabricating disruption caused by inevitable defects and stochastic equipment failures. Achieving these operational tasks without undesirable quality goods, missing due dates, and fabrication interruption help the management minimize operating expenditures. Motivated by assisting manufacturing firms in the situations mentioned this study explores a manufacturing system that features quality reassurances through reworking or removal of defectives, correction of probabilistic failures, and partial overtime and outsourcing options for reducing uptime. This study finds the function of system operating expenditures through model building, mathematical formulations, optimization approaches, and algorithm proposition, shows its convexity, and derives the optimal batch time for the studied manufacturing model. Finally, this study offers numerical illustrations to confirm our work’s applicability and disclose its capability to provide various profound crucial system information that helps the management make strategic operating decisions.

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Section: The Effect Of Uptime-reduction Strategiesmentioning

confidence: 88%

mentioning

confidence: 88%

Minimizing operating expenditures for a manufacturing system featuring quality reassurances, probabilistic failures, overtime, and outsourcing

Chiu¹,

Chiu²,

Pai³

et al. 2023

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…The researchers numerically validated their model, algorithm, and results. Recent works [11][12][13][14] also explored the influence of various rework/quality assurance strategies on different manufacturing-inventory systems. To cope with the client increasing trend on short order lead-time, production planners regularly use effective strategies, such as outsourcing and expedited manufacturing rate, to reduce their fabrication uptime.…”

Section: Survey Of Previous Researchmentioning

confidence: 99%

Optimizing a multiproduct manufacturing system with delayed differentiation, outsourcing, expedited rate, and rework strategies

Chiu¹,

Ke²,

Chiu³

et al. 2021

J Appl Eng Science

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This study examines the effect of delayed differentiation, outsourcing, expedited fabrication rate, and rework strategies on optimal cycle-time decisions for a multi-item manufacturing system. Today’s manufacturing firms must simultaneously deal with externally increasing client multi-item requirements with rapid lead-time and high-quality products and internally on a limited capacity. This study is aimed at assisting manufacturers in meeting client needs in conditions of restricted-capacity and minimum total operating expenses, and adopts a delayed differentiation two-stage multiproduct manufacturing scheme to manage the end products’ commonality. The first stage produces all required common components, and the second stage fabricates individual finished goods. In both stages, we adopt the reworking of the inevitable nonconforming items produced to assure product quality. Furthermore, we implemented partial outsourcing of common parts’ batch and expedited the manufacturing rate of finished products to effectively reduce the uptimes in both stages. We explicitly developed a model to describe the characteristics of the problem. Mathematical analyses with optimization proved the cost function’s convexity and determined the cost-minimization rotation cycle policy. Finally, we numerically validated our model’s and results’ applicability and capability with a simulated example. Apart from creating a useful decision model, this study makes another important contribution to the existing literature in that its revelation of collective/individual effect of the manufacturing-relevant methods on the problem’s best-operating cycle policy and crucial performance indices helps manufacturers have better control over their operations and make effective and efficient managerial decisions.

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“…In the make-to-order environment, determining the production schedule is important [1][2][3][4][5][6][7][8][9][10]. This decision is made for satisfying various purposes, with the most common purpose being to meet the customer delivery due dates [1,4,[10][11][12][13][14][15]. Frequently, this production schedule decision is made in conjunction with other decisions.…”

Section: Introductionmentioning

confidence: 99%

Coordinating Production and Delivery Schedule of Multi-Product and Multi-Customer through Mathematical Programming

Astanti

2022

ASI

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Due to the shortage and high cost of shipping containers, manufacturers that distribute products for worldwide customers must optimize their delivery. Commonly, they complete their delivery schedule first before creating the production schedule. This article tries to address the scheduling problem arising in the process of creating the production schedule to meet the delivery schedule. The complexity of the situation is increased since there is concern about producing as few product types as possible in a single period and having a balance of production load over multiple periods. A mathematical programming model for addressing this production scheduling problem is proposed in the form of integer programming. This model can be solved using LINGO, a commercial mathematical programming software. Microsoft Excel® spreadsheets are used to store both the data input and the output of the mathematical programming model. The advantages of using Excel are its easy-to-read format and familiarity with most users in various companies. Computational experiments in several cases show that the proposed method is effective to create the production and delivery schedule in various problem settings as expected.

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Determining the fabrication runtime for a buyer-vendor system with stochastic breakdown, accelerated rate, repairable items, and multi-delivery strategy

Cited by 4 publications

References 23 publications

Minimizing operating expenditures for a manufacturing system featuring quality reassurances, probabilistic failures, overtime, and outsourcing

Minimizing operating expenditures for a manufacturing system featuring quality reassurances, probabilistic failures, overtime, and outsourcing

Optimizing a multiproduct manufacturing system with delayed differentiation, outsourcing, expedited rate, and rework strategies

Coordinating Production and Delivery Schedule of Multi-Product and Multi-Customer through Mathematical Programming

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