Optimizing replenishment policy in an EPQ-based inventory model with nonconforming items and breakdown

Chiu, Singa Wang; Chou, Chung-Li; Wu, Wen-Kuei

doi:10.1016/j.econmod.2013.07.004

Cited by 23 publications

(22 citation statements)

References 30 publications

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“…Sana [32] simultaneously considered rework, warranty, and preventive maintenance and determined the optimal buffer inventory. Chiu et al [33] considered abort/resume policy in EPQ system with machine breakdown and imperfect items. Taleizadeh and Wee [34] examined a manufacturing system with immediate rework and partial backordering.…”

Section: Economic Production Quantity With Defective Item and Warrantymentioning

confidence: 99%

Production-Inventory System for Deteriorating Items with Machine Breakdown, Inspection, and Partial Backordering

et al. 2019

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This study considers the effects of a machine breakdown, inspection, and partial backordering for deteriorating items. Most industries try to reduce facility unavailability by implementing a regular inspection and preventive maintenance since there is a possibility that some machines will breakdown during the production process. Moreover, an emergency purchase policy can be provided for quick response to customer’s backorder. The system also produces imperfect items with different rates before and after the inspection. Rework process and post-sales warranty are launched for the defective items. Unlike previous studies, we applied a fixed-point approach and renewal reward theorem to solve the deteriorating production-inventory model while considering machine breakdown, inspection, and partial backordering. A case example and sensitivity analysis are provided. The sensitivity analysis shows the important parameters that should be considered in designing the inspection plan and the replenishment policy when facility unavailability and imperfect items exist.

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Section: Economic Production Quantity With Defective Item and Warrantymentioning

confidence: 99%

Production-Inventory System for Deteriorating Items with Machine Breakdown, Inspection, and Partial Backordering

et al. 2019

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“…Taleizadeh et al [30] allowed a backordering alternative along with the rework prospect in their inventory model, whereas Chiu et al [31] and Taleizadeh et al [32] developed inventory models, ignoring the reworking facility. Random defect-rate contemplation was further established by Sana [33], Sarkar and Moon [34], Yoo et al [35], Chakraborty and Giri [36], Wee et al [37], Chiu et al [38], and Sarkar et al [39] using a number of other shop-floor conditions.…”

Section: Introductionmentioning

confidence: 99%

Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand

2018

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Market conditions fluctuate abruptly in today’s competitive environment and leads to imprecise demand information. In particular, market demand data for freshly launched products is highly uncertain. Further, most of the products are generally manufactured through complex multi-stage production systems that may produce defective items once they enter the out-of-control state. Production management of a multi-stage production system in these circumstances requires robust production model to reduce system costs. In this context, this paper introduces an imperfect multi-stage production model with the consideration of defective proportion in the production process and uncertain product demand. Fuzzy theory is applied to handle the uncertainty in demand information and the center of gravity approach is utilized to defuzzify the objective function. This defuzzified cost objective is solved through the analytical optimization technique and closed form solution of optimal lot size and minimum cost function are obtained. Model analysis verifies that it has successfully achieved global optimal results. Numerical experiment comprising of three examples is conducted and optimal results are analyzed through sensitivity analysis. Results demonstrate that larger lot sizes are profitable as the system moves towards a higher number of stages. Sensitivity analysis indicates that the processing cost is the most influencing factor on the system cost function.

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“…In addition to the above literature, a new direction of researches appears that considers randomness in the production system of the EPQ model. Chiu et al [32] extended the economic production quantity model with nonconforming items for a case with random machine breakdown. Bouslah et al [33] proposed joint lot sizing and production policy in an unreliable manufacturing system with random failure and repair.…”

Section: Introductionmentioning

confidence: 99%

Optimal Lot Size in a Manufacturing System with Imperfect Raw Materials and Defective Finished Products

Mokhtari

2018

Scientia Iranica

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In real-world manufacturing systems, it is inevitable to encounter imperfect raw materials and generate defective nished products. In order to cope with these practical problems, this paper studies a manufacturer that orders raw materials from an external source (supplier) and, then, produces a nished product. The raw materials contain imperfect quality items; in addition, the production system is defective. The imperfect raw materials are sold after the screening process, while the defective nished products go under a further rework process. It is also assumed that the defective rate of a machine is a random variable, resulting in three possible cases regarding the occurrence of backordering shortage. The aim is to determine economic order/production lot sizes for each case in such a way that the total cost of the system is minimized. The optimal closed-form solution is derived for each case separately. Moreover, the applicability of the proposed manufacturing model is illustrated via a numerical example.

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Optimizing replenishment policy in an EPQ-based inventory model with nonconforming items and breakdown

Cited by 23 publications

References 30 publications

Production-Inventory System for Deteriorating Items with Machine Breakdown, Inspection, and Partial Backordering

Production-Inventory System for Deteriorating Items with Machine Breakdown, Inspection, and Partial Backordering

Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand

Optimal Lot Size in a Manufacturing System with Imperfect Raw Materials and Defective Finished Products

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