Real time disruption management for a two-stage batch production–inventory system with reliability considerations

Paul, Sanjoy Kumar; Sarker, Ruhul A.; Essam, Daryl

doi:10.1016/j.ejor.2014.02.005

Cited by 93 publications

(62 citation statements)

References 44 publications

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“…Cárdenas-Barrón and Sana (2014) focus on coordination of supply chain. Paul, Sarker, and Essam (2014) introduced a two-stage batch production-inventory system and obtained an optimal recovery plan. Their production may be disrupted either at one or both stages, while our production may be disrupted at any time in this research.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal production and inventory decisions under demand and production disruptions

Shang

Wang

et al. 2015

International Journal of Production Research

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Unanticipated events may take place and disrupt demand and/or production in a supply chain. Conditional on the type, magnitude and duration of disruptions, changes may be called to revise the original production plan. We analyse different disruption scenarios and propose optimal production-inventory models for products facing demand and production disruptions. To lower the cost, we optimise the production run time, purchasing times and order quantity for the manufacturer. Numerical experiments are conducted to examine the influences of disruption time and magnitude on optimal production and purchasing decisions.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal production and inventory decisions under demand and production disruptions

Shang

Wang

et al. 2015

International Journal of Production Research

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“…We assume deterministic lead time (Dejonckheere et al, 2003) and thus order crossover phenomena (Reizebos, 2006) are neglected in this study. Moreover, for simplicity, as well as on the basis of the studies available in literature (see, e.g., Chatfield et al, 2004;Zhang, 2004;Paul et al, 2014;Kurano et al, 2014), we assume one player per supply chain echelon. Implications of this assumption will be discussed in the conclusions.…”

Section: Overviewmentioning

confidence: 99%

How many to produce? The impact of machine flexibility on the performance of a supply chain

Bottani

Montanari

Rinaldi

2015

IJSCIM

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This work analyses the impact of machine flexibility on the performance level of a supply chain. A simulation model is developed to reproduce different supply chain configurations, with one player per echelon. Machine flexibility is modelled as the capability of the manufacturer to produce different kinds of products, in response to the customer's requests, and of the supply chain to manage those products. By means of simulation, six supply chain configurations are investigated, resulting from the combination of different numbers of supply chain players (from 3 to 5) and of products managed by the supply chain (1 or 3). For each scenario, we compute some economic outcomes (i.e., cost of holding stocks, stock-out cost, production or order cost and total supply chain cost), as well as the supply chain lead time and the bullwhip effect. Design of experiments and statistical analysis of outcomes are used to assess the significance of the effects measured. Results of the study provide some guidelines about the effect of machine flexibility on the supply chain performance.

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“…For experimentation, we have generated the test problems by using a uniformly random distribution. To judge the quality of the heuristic solutions, the model is also solved by applying a pattern search technique, which is a standard search algorithm for solving constrained optimization problems [12]. Both the heuristic and the pattern search technique were coded in MATLAB R2012a, and were executed on an Intel core i7 processor with 8.00 GB RAM and a 3.40 GHz CPU.…”

Section: Solution Approachmentioning

confidence: 99%

“…When there is demand, but the item is out of stock and the customer will not wait for the stock to be replenished, lost sales cost exists. Lost sales cost is determined as unit lost sales cost multiplied by lost sales units [12].…”

Section: B Formulation For the Recovery Planmentioning

confidence: 99%

“…Recently, this back order and lost sales concept was also applied to manage transportation [9] and supply [10] disruption in a two-stage supply chain, which consists of a single supplier and a single retailer. This concept was further extended to develop a real time disruption management model, for managing both a single and multiple production disruptions in a single-stage [11] and two-stage [12] production inventory system. A few other studies considered supply disruption while developing a supply chain model, for examples, Parlar and Perry [13] developed inventory models that considered supplier availability with deterministic product demand.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Managing supply disruption in a three-tier supply chain with multiple suppliers and retailers

Paul

Sarker

Essam

2014

2014 IEEE International Conference on Industrial Engineering and Engineering Management

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Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Abstract -In this paper, a supply disruption management model is introduced in a three-tier supply chain with multiple suppliers and retailers, where the system may face sudden disruption in its raw material supply. At first, we formulated a mathematical model for ideal conditions and then reformulated it to revise the supply, production and delivery plan after the occurrence of a disruption, for a future period, to recover from the disruption. Here, the objective is to minimize the total cost during the recovery time window while being subject to supply, capacity, demand, and delivery constraints. We have also proposed an efficient heuristic to solve the model and the results have been compared, with another established solution approach, for a good number of randomly generated test problems. The comparison showed the consistent performance of our developed heuristic. This paper also presents some numerical examples to explain the usefulness of the proposed approach.

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Real time disruption management for a two-stage batch production–inventory system with reliability considerations

Cited by 93 publications

References 44 publications

Optimal production and inventory decisions under demand and production disruptions

Optimal production and inventory decisions under demand and production disruptions

How many to produce? The impact of machine flexibility on the performance of a supply chain

Managing supply disruption in a three-tier supply chain with multiple suppliers and retailers

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