Optimal lot sizing with maintenance actions and imperfect production processes

Porteus (1986) explored an economic order quantity model with imperfect production processes that the approximate lot size is derived. Basically, he dealt with the lot size problem is rather meaningful. However, for mathematical simplicity, he adopted a truncated Taylor series expansion to present the approximate expected total cost function that results in overvalue of expected total cost. In this paper, we extend Porteus (1986) to present the optimal lot size model for defective items with a constant probability when the system is out-of-control and taking the maintenance cost into account. We show that there exists a unique optimal lot size such that the expected total cost is minimised. In addition, the bounds of optimal lot size are provided to develop the solution procedure. Finally, numerical examples are given to illustrate the theoretical results and compare optimal solutions obtained by using our approach and Porteus's approach. Numerical results show that our approach is better.     

Optimal lot sizing in an unreliable two-stage serial production–inventory system

This paper deals with a two‐stage lot sizing problem in an unreliable production environment in which the machine at the first stage (stage 1) is failure‐prone while the machine at the final stage (stage 2) is failure‐free. The process goods are obtained in batches by manufacturing and are transferred continuously from stage 1 to stage 2 where the finished goods are produced and then shipped out to customers. If the machine at stage 1 breaks down then the production of the interrupted lot is not resumed. Instead, a new production cycle is initiated after machine repair. The model is formulated assuming that the production rate of the machine at stage 1 is greater than that at stage 2 and the time to machine failure and repair time are arbitrarily distributed. Specific formulation of the model under exponential failure and exponential repair time distributions is derived and a procedure for finding the optimal production policy is presented. The dependence of the optimal production policy on the model parameters is also examined with numerical examples.     

Analysis of a dynamic lot‐sizing problem with production capacity constraint

We study a capacitated dynamic lot‐sizing problem with special cost structure involving setup cost, freight cost, production cost, and inventory holding cost. We investigate two cases of the problem categorized by whether the maximal production capacity in one period is an integral multiple of the capacity of a container and reveal the special structure of an optimal solution for each case. In the case where the maximal production capacity is an integral multiple of a container's capacity, the T‐period problem is solved using polynomial effort by a network algorithm. For the other case, the problem is transformed into a shortest path problem, and a network‐based algorithm combining dynamic programming is proposed to solve it in polynomial time. Numerical examples are presented to illustrate application of the algorithms to solve the two cases of the problem.     

Electronic spreadsheet implementation of a lot sizing procedure for a single-card kanban system

A cost based procedure to evaluate lot sizing alternatives for a single-card kanban system (also known as “push-pull” system) using a specific production strategy is implemented in an electronic spreadsheet. The spreadsheet and a case study are used to illustrate the cost procedure and sensitivity analysis.

Inventory carrying, storage, and handling costs are considered in the procedure. The lot sizing alternatives generated for the case study were based on the utilization of pallet and tray capacity, and a bottleneck process which complicated the implementation of the “push-pull” strategy.     

A numerical solution for a two-stage production and inventory system with random demand arrivals

This paper is about the study of a production lot sizing problem consisting of customers, one retailer, and one manufacturer. Demand from customers arrives randomly at a retailer one unit at a time. The retailer replenishes inventory from the manufacturer upon receiving a customer's order after its inventory depleted to zero. The manufacturer's production rate is assumed to be a finite constant. A production cycle starts when the manufacturer's inventory falls to or below zero and stops when its on-hand inventory reaches its optimal level. During the uptime in a production cycle, inventory is being built while randomly arriving orders from retailer are being fulfilled. The order arrival times from customers are independently and identically distributed, hence the inventory processes at both the manufacturer and the retailer become a renewal process that is difficult to solve analytically for a general distribution of order arrival time. Therefore, a numerical approach is used in developing a search procedure to obtain the optimal solution to the problem. Employing such a numerical approach, we also investigate how optimal solutions in different cases will change over the spectrum of some key parameters of the problem.     

Economic production quantity model with a shifting production rate

Typical models for determining the economic production quantity (EPQ) assume perfect product quality and perfect production processes. Deteriorating processes may affect production systems in several ways. They may decrease the quality of the items produced, cause production stoppage and breakdowns and/or reduce the production rate due to production process inefficiency. The purpose of this paper is to present an EPQ model that incorporates the effect of shifts in production rate on lot sizing decisions due to speed losses. The cycle starts with a certain production rate and after a random time, the production rate shifts to a lower value. A mathematical model to determine the optimal production policy under these conditions is developed and analyzed. Numerical examples are presented for illustrative purposes.     

Improved algorithms for dynamic lot sizing problems with incremental discount

We develop improved algorithms for the dynamic lot sizing problems with incremental discount, where the procurement cost is a concave piecewise linear function with m sections and the holding cost is linear. We decompose the problem carefully and present a new dynamic programming formulation. By using geometric techniques, we show that when m is fixed, the problem can be solved in O(T?log?T) time, and further O(T) time if the procurement cost is stationary.     

An economic production lot size model with increasing demand, shortages and partial backlogging

In this paper, an economic production quantity model is developed for a production–inventory system where the demand rate increases with time, the production rate is finite and adjustable in each cycle over an infinite planning horizon and shortages are permitted. The cost of adjusting the production rate depends linearly on the magnitude of the change in the production rate. During the stock‐out period, a known fraction of the unsatisfied demands is backordered while the remaining fraction is lost. The model is formulated taking the demand rate as a general increasing function of time and the optimal production policy is obtained for the special case of a linearly increasing demand rate. The proposed model is also shown to be suitable for a prescribed time horizon. A procedure to find approximately the minimum total cost of the system over a finite time horizon is suggested. A numerical example is taken to illustrate the solution procedure of the developed model.     

Economical production and transshipment policy for coordinating multiple production sites

In this article, we study the coordination mechanism dealing with a production–transshipment policy across the multiple regions supplying multiple products. It is assumed that each production site has its own dedicated demand region consuming multiple products. The main concern is how to determine both the production quantity and the lot-apportioning policy while minimising the relevant supply chain cost. This decision issue is formulated as a non-linear mathematical model to determine several relevant decision variables. We propose the solution procedure for deriving the production–transshipment policy minimising the overall supply chain cost.     

Lot sizing and unequal-sized shipment policy for an integrated production-inventory system

This article develops a single-manufacturer single-retailer production-inventory model in which the manufacturer delivers the retailer’s ordered quantity in unequal shipments. The manufacturer’s production process is imperfect and it may produce some defective items during a production run. The retailer performs a screening process immediately after receiving the order from the manufacturer. The expected average total cost of the integrated production-inventory system is derived using renewal theory and a solution procedure is suggested to determine the optimal production and shipment policy. An extensive numerical study based on different sets of parameter values is conducted and the optimal results so obtained are analysed to examine the relative performance of the models under equal and unequal shipment policies.     

Economic production quantity with rework process at a single-stage manufacturing system with planned backorders

In traditional inventory models such as the economic order quantity (EOQ) and the economic production quantity (EPQ) the sole objective is to minimize the total inventory-related costs, typically holding cost and ordering cost. These models do not consider the presence of defective products in the lot or rework of them. Recently, Jamal, Sarker, and Mondal (Jamal, A. A. M., Sarker, B. R., & Mondal, S., (2004). Optimal manufacturing batch size with rework process at single-stage production system. Computers and Industrial Engineering, 47(1), 77–89) proposed a model, which dealt with the optimum batch quantity in a single-stage system in which rework is done by addressing two different operational policies to minimize the total system cost, but their models do not consider planned backorders. In this direction, this paper develops an EPQ type inventory model with planned backorders for determining the economic production quantity for a single product, which is manufactured in a single-stage manufacturing system that generates imperfect quality products, and all these defective products are reworked in the same cycle. We also establish the range of real values of the proportion of defective products for which there is an optimal solution, and the close form for the total cost of inventory system. The use of the inventory model is illustrated with numerical examples. The classical EOQ, EPQ inventory models with or without planned backorders and Jamal, Sarker and Mondal’s model (Jamal, A. A. M., Sarker, B. R., & Mondal, S., (2004). Optimal manufacturing batch size with rework process at single-stage production system. Computers and Industrial Engineering, 47(1), 77–89) are shown to be special cases of the EPQ inventory model presented in this paper.     

A mathematical model on EPQ for stochastic demand in an imperfect production system

In the paper, we develop an EPQ (economic production quantity) inventory model to determine the optimal buffer inventory for stochastic demand in the market during preventive maintenance or repair of a manufacturing facility with an EPQ (economic production quantity) model in an imperfect production system. Preventive maintenance, an essential element of the just-in-time structure, may cause shortage which is reduced by buffer inventory. The products are sold with the free minimal repair warranty (FRW) policy. The production system may undergo “out-of-control” state from “in-control” state, after a certain time that follows a probability density function. The defective (non-conforming) items in “in-control” or “out-of-control” state are reworked at a cost just after the regular production time. Finally, an expected cost function regarding the inventory cost, unit production cost, preventive maintenance cost and shortage cost is minimized analytically. We develop another case where the buffer inventory as well as the production rate are decision variables and the expected unit cost considering the above cost functions is optimized also. The numerical examples are provided to illustrate the behaviour and application of the model. Sensitivity analysis of the model with respect to key parameters of the system is carried out.     

A continuous review inventory model with the controllable production rate of the manufacturer

Optimal operating policy in most deterministic and stochastic inventory models is based on the unrealistic assumption that lead‐time is a given parameter. In this article, we develop an inventory model where the replenishment lead‐time is assumed to be dependent on the lot size and the production rate of the manufacturer. At the time of contract with a manufacturer, the retailer can negotiate the lead‐time by considering the regular production rate of the manufacturer, who usually has the option of increasing his regular production rate up to the maximum (designed) production capacity. If the retailer intends to reduce the lead‐time, he has to pay an additional cost to accomplish the increased production rate. Under the assumption that the stochastic demand during lead‐time follows a Normal distribution, we study the lead‐time reduction by changing the regular production rate of the manufacturer at the risk of paying additional cost. We provide a solution procedure to obtain the efficient ordering strategy of the developed model. Numerical examples are presented to illustrate the solution procedure.     

Polyhedral and Lagrangian approaches for lot sizing with production time windows and setup times

In this paper, we solve the capacitated multi item lot-sizing problem with non-customer specific production time windows and setup times using two approaches: (i) using a Lagrangian relaxation-based heuristic and (ii) using reformulations and a commercial software. The results of the two approaches are analyzed and compared based on randomly generated data sets. The results show that the first approach finds feasible solution more rapidly but a steady state is reached very quickly. On the other hand the second approach quickly finds good lower bounds and finds good feasible solutions if more CPU time is allowed. It turns out that, for a wide variety of instances varying in size and other parameters, we can obtain feasible solutions within 1–5% of optimal within 10 s and also obtain solutions that are guaranteed within 1–2% of optimal within 60–120 s.     

Economic production quantity model for items with continuous quality characteristic,rework and reject

The economic production quantity (EPQ) model is a well-known and commonly used inventory control technique. However, the model is built on an unrealistic assumption that all the produced items need to be of perfect quality. Having relaxed this assumption, some researchers have studied the effects of the imperfect products on the inventory control techniques. This article, thus, attempts to develop an EPQ model with continuous quality characteristic and rework. To this end, this study assumes that a produced item follows a general distribution pattern, with its quality being perfect, imperfect or defective. The analysis of the model developed indicates that there is an optimal lot size, which generates minimum total cost. Moreover, the results show that the optimal lot size of the model equals that of the classical EPQ model in case imperfect quality percentage is zero or even close to zero.     

考虑缺货的模糊随机缺陷生产系统

针对不可靠的生产过程,研究了生产故障时间为模糊随机变量且允许缺货的缺陷生产系统.建立含缺货费和模糊随机重修费的经济生产批量模型.基于可信性理论,建立其期望费用模型,揭示了费用函数的性质,并证明了使费用最小的最优生产时间的存在性和唯一性,从而确定了最优生产时间的上下界.基于此,设计了最优生产时间的二分法求解过程.最后通过算例验证了所提出模型的有效性,并分析了缺货费用、重修费用和缺陷产品比例对最优生产策略的影响.     

Optimal production lot size and reorder point of a two-stage supply chain while random demand is sensitive with sales teams' initiatives

The paper develops a production-inventory model of a two-stage supply chain consisting of one manufacturer and one retailer to study production lot size/order quantity, reorder point sales teams’ initiatives where demand of the end customers is dependent on random variable and sales teams’ initiatives simultaneously. The manufacturer produces the order quantity of the retailer at one lot in which the procurement cost per unit quantity follows a realistic convex function of production lot size. In the chain, the cost of sales team's initiatives/promotion efforts and wholesale price of the manufacturer are negotiated at the points such that their optimum profits reached nearer to their target profits. This study suggests to the management of firms to determine the optimal order quantity/production quantity, reorder point and sales teams’ initiatives/promotional effort in order to achieve their maximum profits. An analytical method is applied to determine the optimal values of the decision variables. Finally, numerical examples with its graphical presentation and sensitivity analysis of the key parameters are presented to illustrate more insights of the model.     

An optimal production lot-sizing problem for an imperfect process with imperfect maintenance and inspection time length

This article develops an integrated model in considering the situations of an imperfect process with imperfect maintenance and inspection time for the joint determination of both economic production quantity (EPQ) and preventive maintenance (PM). This imperfect process has a general deterioration distribution with increasing hazard rate. Even with periodic PM, such a production system cannot be recovered as good as new. This means that the system condition depends on how long it runs. Also, the PM level can be distinct due to the maintenance cost. For convenience, it is assumed the age of system is reduced in proportional to the PM level. Further, during a production cycle, we need an inspection to see if the process is in control. This inspection might demand a considerable amount of time. In this article, we take PM level and inspection time into consideration to optimise EPQ with two types of out-of-control states. To see how the method works, we use a Weibull shock model to show the optimal solutions for the least costs.     

Solving a multi-level capacitated lot sizing problem with multi-period setup carry-over via a fix-and-optimize heuristic

This paper presents a new algorithm for the dynamic multi-level capacitated lot sizing problem with setup carry-overs (MLCLSP-L). The MLCLSP-L is a big-bucket model that allows the production of any number of products within a period, but it incorporates partial sequencing of the production orders in the sense that the first and the last products produced in a period are determined by the model. We solve a model which is applicable to general bill-of-material structures and which includes minimum lead times of one period and multi-period setup carry-overs. Our algorithm solves a series of mixed-integer linear programs in an iterative so-called fix-and-optimize approach. In each instance of these mixed-integer linear programs a large number of binary setup variables is fixed whereas only a small subset of these variables is optimized, together with the complete set of the inventory and lot size variables. A numerical study shows that the algorithm provides high-quality results and that the computational effort is moderate.