Economic lot-size problem for a cleaner manufacturing system with warm-up period

Abstract

There are instances that production machines require a warm-up period to reach their anticipated productivity. This study extends an economic manufacturing quantity (EMQ) problem by considering warm-up issue in the model. Warming up the machine decreases production loss, emission, and machine depreciation. Therefore, this study helps industry to enhance the profitability and also to reduce the environmental impact by decreasing waste generation and improving machine efficiency. In this study, we divide our system into three subsystems based on the relationships between production and consumption. Then we provide a mathematical model for each subsystem (three in total). The first two models are single-item EMQ inventory problems and the third one is a multi-item single-machine EMQ problem. In the third model, a machine/facility manufactures some items under a limited manufacturing volume. The purpose of these proposed models is to find the optimum cycle length to minimize the total system cost that consists of manufacturing, inventory and setup costs. Finally, we propose exact solution procedures after proving the convexity of these mathematical models.

Model to reduce the cost of production in a bottling company using the EOQ, Linear Programming and Aggregate Planning

“…Likewise, the authors [20] demonstrated the models based on EPQ are very close to reality and showed that they are useful for reducing storage costs. Another variation of the model is implemented by the authors [21], who obtained as a result that the use of EMQ, in the application of the models with heating period, proved to achieve the expectations that were initially held, since a reduction in order, manufacturing and storage costs was verified. Additionally, [22] tests the use of the EOQ tool in a scenario where demand is stochastic.…”

Optimizing a bi-objective multi-period fish closed-loop supply chain network design by three multi-objective meta-heuristic algorithms

“…Constraint (19) ensures that the waste production rate is equivalent to the amount of returned goods transferred to the reprocessing centers from the producers. According to Constraint (20), the returned goods are dispatched to a reprocessing center from a production center only if there is an open reprocessing center in the potential place for this facility. Like Constraints ( 19)- (20), Constraints ( 21)-( 22), ( 23)-( 24), ( 25)- (26), and ( 27)- (28) state that the facilities' maximum capacity is defined as a limit on the shipped products, and these constraints specify an opening facility as a prerequisite for transporting the products.…”

“…According to Constraint (20), the returned goods are dispatched to a reprocessing center from a production center only if there is an open reprocessing center in the potential place for this facility. Like Constraints ( 19)- (20), Constraints ( 21)-( 22), ( 23)-( 24), ( 25)- (26), and ( 27)- (28) state that the facilities' maximum capacity is defined as a limit on the shipped products, and these constraints specify an opening facility as a prerequisite for transporting the products. Constraint (29) states that the total fish powder shipped to the fish powder market as the reprocessed good equals all the products returned from the manufacturers, processing centers, customers, and distribution centers, multiplied by the conversion rate.…”

“…Moreover, we develop a new bi-objective mathematical model for minimizing the fish CLSC cost and maximizing customer demand responsiveness in reverse and forward SCs. SC decisions should be pursued by respecting economic issues and customer requirements considerations [18], since the primary objective of every industry is to reduce system costs and enhance customers' satisfaction [19,20]. For model solving and studying the solution methods, we use some famous meta-heuristic algorithms.…”

Preservation technology investment, trade credit and partial backordering model for a non-instantaneous deteriorating inventory

“…Nobil et al [20] developed a model for single machine lot scheduling problem for negative exponential deteriorating items. Nobil et al [21] projected a model for economic lot size problem for cleaner manufacturing system with another interesting parameter warm-up period. A two-warehouse model with increasing demand under timevarying deterioration is developed by Sett et al [26].…”