Integrated inventory and inspection policies for stochastic demand

Ben‐Daya, Mohamed; Noman, Syed Mobasher

doi:10.1016/j.ejor.2005.12.053

Cited by 39 publications

(20 citation statements)

References 7 publications

(5 reference statements)

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“…The issue of simultaneous determination of procurement quantity and sampling scheme has already been examined in the context of forward supply chains, e.g. [15] and [16]. Contrary to existing contributions, we examine this issue in the reverse supply chain context.…”

Section: Introductionmentioning

confidence: 83%

The Value of Sampling Inspection in a Single-Period Remanufacturing System with Stochastic Returns Yield

Zikopoulos

Panagiotidou

Nenes

2010

IFIP Advances in Information and Communication Technology

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Abstract. We examine a reverse supply chain consisting of a collection site, where consumers return used products, and a remanufacturing facility. Some of the returned products are transported to the remanufacturing facility in order to be remanufactured and used to satisfy the stochastic demand for remanufactured products. The quality of returns is characterized by uncertainty, and therefore, before the procurement quantity determination, the remanufacturer has the alternative to inspect a sample drawn from the collected quantity in order to evaluate more accurately returns' quality. Using general assumptions for returns quality and remanufactured products demand distributions, we formulate the expected profit function for both sampling and no-sampling cases and we examine numerically the economic effectiveness of sampling. A key characteristic of the current paper is that returns' yield is expressed as the probability of a unit to be remanufacturable.

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Section: Introductionmentioning

confidence: 83%

The Value of Sampling Inspection in a Single-Period Remanufacturing System with Stochastic Returns Yield

Zikopoulos

Panagiotidou

Nenes

2010

IFIP Advances in Information and Communication Technology

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“…In reality, a fraction of the received lot may consist of non-conforming parts, known as "items of poor quality" [19]. In that case, the inspection policy has to be integrated into the productioninventory model to reduce the impact of raw material non-conformity on ordering and lot sizing decisions [20] and on the quality of the finished product [21]. Given that a 100% inspection process may be costly and time consuming, an acceptance sampling plan could be more adequate.…”

Section: Introductionmentioning

confidence: 99%

“…Other authors have assumed a 100% inspection on the refused lot. Ben-Daya, Noman [20], [28] studied an integrated inventory inspection models with and without replacement of non-confirming items. Moussawi-Haidar et al [29] presented an analytical method to optimize the lot size, sample size and acceptance number in an EOQ-type model that achieves a certain average outgoing quality limit.…”

Section: Introductionmentioning

confidence: 99%

Integrated quality strategy in production and raw material replenishment in a manufacturing-oriented supply chain

Hlioui

Gharbi

Hajji

2015

Int J Adv Manuf Technol

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Abstract:This paper deals with the coordination of production, replenishment and inspection decisions for a manufacturing-oriented supply chain with a failure-prone transformation stage, random lead-time and imperfect delivered lots. Upon reception of the lot, the manufacturer executes an acceptance sampling plan with a zero nonconforming criterion. If the sample does not contain non-conforming items, the lot is accepted; otherwise, it is rejected. In this work, two strategies regarding the refused sampled lot are studied. The first one involves a return of the lot to the supplier, who commits to improving the quality of the lot, while the second assumes that the manufacturer performs a 100% inspection and rectification operation. This work presents two main objectives. The first one is to jointly optimize, in a stochastic and dynamic context, the ordering point of raw material, the lot size of raw material, the final product inventory threshold and the severity of the sampling plan using a simulation-based optimization approach. The second one is to determine the best of the two quality control strategy. The in-depth study has shown that no strategy could be preferred in all the cases. For this reasons, we present an easy decision-making tool (Indifference curves) to help the manager to select the best quality control strategy when considering the entire supply chain.

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“…The above models, which are mainly designed to control received commodity from suppliers, are commonly developed to minimize an expected total cost including inspection, batches acceptance and rejection costs. Finally, economic single acceptance sampling plan have been integrated with economic ordering quantity (EOQ) model by Peters et al (1988), BenDaya et al (2006) and Ben-Daya and Noman (2008).…”

Section: Introductionmentioning

confidence: 99%

Joint production and quality control of unreliable batch manufacturing systems with rectifying inspection

Bouslah

Gharbi

Pellerin

2013

International Journal of Production Research

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Production control policy and economic sampling plan design problems have been studied separately in previous research. This paper considers a joint production control policy and economic single sampling plan design for an unreliable batch manufacturing system. The production is controlled by a modified hedging point policy which consists in building and maintaining a safety stock of finished product to avoid shortages during corrective maintenance. The main objective of this paper is to determine simultaneously the economic production quantity, the optimal safety stock level and the economic sampling plan design which minimize the expected overall cost. A stochastic mathematical model is developed and solved using a simulation optimization approach based on the response surface methodology. Simulation is used to imitate the complex dynamic and stochastic behaviour of processes as in the real-life industrial systems. The obtained results show clearly strong interactions between production quantity, inventory state and sampling plan design which confirm the necessity of jointly considering production and quality control parameters in an integrated model. Moreover, it is shown a significant impact of production system reliability on the economic sampling plan design and therefore on the quality of finished product delivered to consumers. Numerical example and sensitivity analyses are presented for illustrative purposes.

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Integrated inventory and inspection policies for stochastic demand

Cited by 39 publications

References 7 publications

The Value of Sampling Inspection in a Single-Period Remanufacturing System with Stochastic Returns Yield

The Value of Sampling Inspection in a Single-Period Remanufacturing System with Stochastic Returns Yield

Integrated quality strategy in production and raw material replenishment in a manufacturing-oriented supply chain

Joint production and quality control of unreliable batch manufacturing systems with rectifying inspection

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