Optimal Jit Production and Delivery Lot Size Model That Considers Vendor Reworking Process and Variable Setup Cost

Chiu, Yufang; Chang, Ching-Yang

doi:10.1080/10170660909509126

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…Tsou et al (2009) followed the studies of Salameh and Jaber (2000), Chan et al (2003) and Papachristos and Konstantaras (2006) to develop an EPQ model with continuous quality characteristic, rework and reject situations. Chiu and Chang (2009) studied a JIT lot sizing problem with rework and variable setup cost. They showed that the lot size and the rework cost have a direct relation with the fraction of defectives.…”

Section: Rework and Scrapmentioning

confidence: 99%

Inventory control in a two-level supply chain with learning, quality and inspection errors

Khan¹

2021

Preprint

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A common measure of quality for a buyer or a vendor is the defect rate. Defects may represent an attribute, a dimension or a quantity. They may be classified as product quality defects or process quality defects. Product quality defects may be caused by human error which can de due to fatigue, lack of proper training, or other reasons. For example, an inspector may misclassify a defective fuel tank of a car as good. On the other hand, process quality defects maybe caused by a machine going out-of-control. While many researchers assume that the screening processes which separate the defective items are error-free, it would be realistic to consider misclassification errors in this process. Beside inspection errors, learning is another human factor that brings in enhancement in the overall performance of a supply chain. Learning is inherent when there are workers involved in a repetitive type of production process. Learning and forgetting are even more important in manufacturing environments that emphasize on flexibility where workers are cross-trained to do different tasks and where products have a short life cycle. Inventory management with learning in quality, inspection and processing time will be the focus of this thesis. A number of models will be developed for a buyer and/or a two level supply chain to incorporate these human factors. The key findings of this work may be summarized as 1. Inspection errors significantly affect the annual profit. 2. An increase in the unit screening cost reduces the annual profit to a great extent at slower rates of learning. 3. For the two-level supply chain we investigated, learning in production drops the annual cost significantly while the learning in supplier's quality results in a situation where there are no defectives from the suppliers. 4. Type II error may seem to be beneficial for a two level supply chain as the order/lot size goes down and thus affects the costs of ordering, production and screening. 5. Consignment stocking policy performs better than conventional stocking when holding costs go higher than a threshold value.

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Section: Rework and Scrapmentioning

confidence: 99%

Inventory control in a two-level supply chain with learning, quality and inspection errors

Khan¹

2021

Preprint

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“…Van Eijs [6] modified Goyal's model to make method of exhaustion more efficient. The model proposed by Sung & Gong [5] and Chiu & Chang [1] considered defective products. But Sung & Gong [5] did not consider re-working set up cost.…”

Section: Literature Reviewmentioning

confidence: 99%

“…But Sung & Gong [5] did not consider re-working set up cost. Chiu & Chang [1] ignored the replacement of material when defective products were re-worked. This research modified their models and porposed a new joint replenishment model with consideration of holding cost of material replacement and set up cost of replenishment.…”

Section: Literature Reviewmentioning

confidence: 99%

Inventory-Up-Level Joint Replenishment Model for Re-Working Materials and New Materials

Yang

Huang

Hou

2013

AMR

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In order to reduce cost, defective products are re-worked and regarded as new sources of materials with normal production schedule in the joint replenishment problem. In this research, inventory and replenishment problems with respect to the heavy loading of inventory system and production line shutdown will be solved. The break-even upper bound of safe inventory for the risk cost of over-inventory and the ordering costs of joint replenishment are considered. In the meanwhile, the limitation of inventory will impact the cycle time of material replenishment with consideration of new materials and re-worked defective products. Within the break-even upper bound of safe inventory, this research will find the optimal replenishment model with combining new materials and re-worked defective products.

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Determination of number of kanban in a cellular manufacturing system with considering rework process

Aghajani

Keramati

Javadi

2012

Int J Adv Manuf Technol

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Optimal Jit Production and Delivery Lot Size Model That Considers Vendor Reworking Process and Variable Setup Cost

Cited by 6 publications

References 16 publications

Inventory control in a two-level supply chain with learning, quality and inspection errors

Inventory control in a two-level supply chain with learning, quality and inspection errors

Inventory-Up-Level Joint Replenishment Model for Re-Working Materials and New Materials

Determination of number of kanban in a cellular manufacturing system with considering rework process

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