An improved solution to the replenishment policy for the EMQ model with rework and multiple shipments

Cárdenas–Barrón, Leopoldo Eduardo; Sarkar, Biswajit; Treviño-Garza, Gerardo

doi:10.1016/j.apm.2012.10.017

Cited by 60 publications

(23 citation statements)

References 19 publications

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“…Kim et al [37] derived a model for multi-stage production system considering defective items. Similarly, Cárdenas-Barrón et al [38] developed an EMQ model for imperfect production associated with rework and multiple shipment strategies. Sarkar et al [39] derived an economic manufacturing quantity (EMQ) model under the effects of reliability and inflation.…”

Section: Literature Review and Research Gapmentioning

confidence: 99%

A Multi-Objective Optimization of Energy, Economic, and Carbon Emission in a Production Model under Sustainable Supply Chain Management

2018

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Nowadays, many industries are focusing on automation in manufacturing for high production and good quality to meet the needs of customers in a short period of time. This trend has produced a forward shift in technology in the form of advancement, which ultimately increases energy demand. For that reason, researchers have started working on sustainable development associated with cleaner-energy policies to avoid increasing energy consumption for enhanced manufacturing technology in developed countries. The other important issue affecting our world is global warming, which is the result of greenhouse gas emissions. That is the reason, renewable energies like solar energy have dramatically increased during recent years to compensate for the energy demand and reduced carbon footprint for cleaner production. This paper considers a supply chain management of automobile part manufacturing industry with suppliers to optimize the production quantity with multiple objectives i.e., minimizing the total cost of production including minimum quantity lubrication is a first objective, reduction of the carbon footprint is the second, and minimizing the cost of energy considering renewable energy is the last objective. This study considers a situation, where imperfect quality items are managed and controlled by the suppliers as outsourcing operations. A weighted goal programming methodology is utilized to solve the proposed mathematical model including sustainable suppliers. Sensitivity analysis of the model is performed for different scenarios with respect to the energy utilization. The optimal result of minimum production cost and carbon emissions is the evidence of successful pragmatic application in automobile industry. The results validate the model to provide the basis for sustainability in supply chain environment considering manufacturer and suppliers.

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Section: Literature Review and Research Gapmentioning

confidence: 99%

A Multi-Objective Optimization of Energy, Economic, and Carbon Emission in a Production Model under Sustainable Supply Chain Management

2018

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“…More recent studies can be found in Diponegoro and Sarker (2006), Ben-Daya, Darwish, and Ertogral (2008) and Mungan, Yu, and Sarker (2010). Improved solution procedures to compute the discrete lot size can be found in Cárdenas- Teng (2011), Cárdenas-Barrón et al (2012) and Cárdenas-Barrón, Sarkar, and Treviño-Garza (2013). These works have focused on the optimal EPQ strategy by either excluding the delivery policies, or assuming that the delivery quantity is fixed or known beforehand.…”

Section: Introductionmentioning

confidence: 96%

Joint production and shipment lot sizing for a delivery price-based production facility

Lee

2013

International Journal of Production Research

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A joint economic production quantity (EPQ) and delivery quantity model for a production system is investigated in this paper. More specifically, an EPQ policy is implemented in the production system, while a smaller shipping quantity is periodically dispatched to the customer. The production system is also responsible for the shipment cost, i.e. a delivery price-based procurement from the customer. The considered cost includes setup cost to launch the batch production, inventory carrying cost, and transportation cost, where the transportation cost is a function of the delivery quantity. A per unit time cost model is developed and analysed to determine the optimal production and delivery quantities. Under some mild conditions, it can be shown that the joint cost function is convex with respect to the production quantity; and the number of delivery is an integer in each replenishment cycle. Computational study has demonstrated the significant impact of the joint decision model on the operating cost. In particular, the reduction in total cost can be more than 15% when inventory carrying costs, and/or transportation costs, are high.Keyword: economic production quantity; periodic delivery; transportation cost; joint cost model IntroductionThe inventory replenishment problem of simultaneously determining optimal production and delivery strategies in a production facility is addressed in this paper. This study is motivated by the following observations. A sequential decision process is most often observed in the production-replenishment-delivery operation management. First, an economic production quantity is determined in the production system (as a supplier) at the upper echelon, with the objective to minimise the production-inventory cost to meet the demand. This is often addressed in the well-known production inventory models. Second, the optimal shipping quantity to the customer at the lower echelon is determined to minimise the delivery or transportation cost, which can be frequently found in the study of logistic or transportation management. Third, the integration of production (supply) and delivery (demand) in these systems is often stressed and discussed in many researches, but lack of a formal methodology to address the coordinated production-replenishment-delivery problem. The popularity of this decision process suggests that a joint analytical decision model that integrates both production and delivery strategies with transportation cost will be useful.The economic production quantity (EPQ) model, e.g. see Hadley and Whitin (1963) or Silver, Pyke, and Peterson (1998), is a classical inventory replenishment policy where both production and demand rates are assumed deterministic and constant. Each replenishment cycle starts when there is no on-hand inventory and a fixed quantity (lot size or batch) is launched in the production facility. An analytical model is developed to determine the optimal EPQ so that the sum of setup cost and inventory carrying cost is minimised. For an extended study of implementing thi...

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“…In this model carbon foot print and carbon emission costs were considered witout any energy consideration. Cárdenas-Barrón et al [25] developed the benefit of multi-shipment in an economic manufacturing model without having any concept of energy matter. Giotitsa et al [26] strives an appropriate approach for production of energy and its distribution.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management

Sarkar

2019

Energies

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A smart production system is essential to produce complex products under the consumption of efficient energy. The main ramification of controllable production rate, amount of production size, and safety stocks is simultaneously optimized under proper utilization of energy within a smart production system with a random breakdown of spare parts. Due to the random breakdown, a greater amount of energy may be used. For this purpose, this study is concerned about the optimum safety stock level under the exact amount of energy utilization. For random breakdown, there are three cases as production inventory meets the demand without utilization of the safety stock, with using of the safety stock, and consumed the total safety stock amount and facing shortages. After the random breakdown time, the smart production system may move to an out-of-control state and may produce defective items, where the production rate of defective items is a random variable, which follows an exponential distribution. The total cost is highly nonlinear and cannot be solved by any classical optimization technique. A mathematical optimization tool is utilized to test the model. Numerical study proves that the effect of energy plays an important role for the smart manufacturing system even though random breakdowns are there. it is found that the controllable production rate under the effect of the optimum energy consumption really effects significantly in the minimization cost. It saves cost regarding the corrective and preventive maintenance cost. The amount of safety stock can have more support under the effect of optimum energy utilization. The energy can be replaced by the solar energy.

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An improved solution to the replenishment policy for the EMQ model with rework and multiple shipments

Cited by 60 publications

References 19 publications

A Multi-Objective Optimization of Energy, Economic, and Carbon Emission in a Production Model under Sustainable Supply Chain Management

A Multi-Objective Optimization of Energy, Economic, and Carbon Emission in a Production Model under Sustainable Supply Chain Management

Joint production and shipment lot sizing for a delivery price-based production facility

Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management

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