Simultaneous determination of the optimal production–inventory and product inspection policies for a deteriorating production system

In this paper, we attempt to find a method for the optimization of production–inventory and product inspection policies for deteriorating production systems. Taking advantage of the nature of a deteriorating production system, a strategy would be not to inspect the first s items of the batch. Therefore, an inspection policy which disregards the first s (DTF-s) items of the batch is proposed. Under the DTF-s policy, we do not inspect the first s produced items but inspect only those items from the (s+1)th till the end of the production run. The objective of this study was the joint determination of the production lot size and the inspection policy s, resulting in a minimization of the expected average cost per unit time. Based on this model, the underlying conditions necessary for the existence of an optimal policy are given. Two commonly used inspection strategies, no inspection and full inspection are discussed. Under both inspection strategies, an optimal production–inventory lot is bounded by the traditional economic quantity. The case of full inspection is shown to be an extension of previously reported results. The option of investing in the process of quality improvement is also discussed. Finally, numerical examples are given to illustrate the method and its advantages in the conclusion.Scope and purposeThis paper considers the relationship between production, inventory and inspection in a deteriorating production system which may transit from the “in-control” state to the “out-of-control” state after a period of operation. Once the transition to the “out-of-control” state has occurred, it is assumed that some percentage of the items produced are defective or of substandard quality. However, in many cases, defects in a defective item can only be identified by an inspection process which carries an inspection cost. Those inspected items which are found to be defective are reworked at some cost before being shipped. On the other hand, defective items which are not inspected will be passed to the customer, incurring a much larger warranty cost. In order to operate such a system economically, tradeoffs among production setup, inventory, inspection and defective cost must be analyzed. Deterioration of the production system is an inherent process in all manufacturing industries. An understanding of the relationship among production, inventory and inspection for such systems will help managers to maintain efficient and economic control of operations.     

Coordinated procurement/inspection and production model under inspection errors

In this study, we investigate integrating the acquisition of input materials, material inspection and production planning, where type I and type II inspection errors are allowed, and the unit acquisition cost is dependent on the average quality level. This study aims to find an optimal purchase lot size (or here, equivalently, the fixed production rate multiplied by the production run time), input quality level and the associated inspection policy that minimize the total cost per item including the order cost, materials purchase cost, setup cost, inventory holding cost, and the quality-related cost. Furthermore, the boundaries, conditions and properties for the optimal production run time are obtained under an optimal inspection policy when the input material quality level is fixed. These findings will facilitate the establishing of an efficient algorithm for an optimal solution. The study demonstrates that a partial inspection approach could dominate over both the commonly used policies of full or no inspection, which is different from a previous report where the optimal inspection policy is either full or no inspection. A numerical example is performed to evaluate the impact of the two types of inspection errors and the process deterioration because of a nonconforming process input on the optimal solution, where a Weibull shift distribution is used to simulate the process failure time. Finally, conclusions are addressed.     

Determining the production lot size with a heuristic inspection policy for controlling the quality of input materials and products

This study simultaneously determines the optimal production lot size and an inspection policy for input materials and products, where an unreliable process produces products with a discrete general shift distribution. This work proposes a heuristic inspection policy for materials and products, by first obtaining the inspection range for the input material without considering product inspection, and by further determining the product inspection range based on the obtained range of the input material inspection. The optimal inspection policy shows that common policies of no or full inspection are never optimal. This study includes the optimal production lot size based on the obtained inspection policy. Numerical examples demonstrate the impacts of input quality level, process reliability and unit nonconforming cost on the optimal solution, which adopts a discrete Weibull shift distribution to model the process failure time. Finally, this study addresses the conclusions.     

A mixed inspection policy for CSP-1 and precise inspection under inspection errors and return cost

This paper is to deal with a mixed policy between precise inspection and CSP-1 with inspection errors (Types I and II) and return cost. First, the concept of a renewal reward process is employed to obtain the long-term net profit of the mixed inspection policy. Then, with respect to non-repairable and repairable products, we determine the following four decision variables such that the unit net profit is maximal: (1) the optimal clearance number, (2) the optimal sampling frequency, and (3) the proportions which should be taken precise inspection for the non-inspected items in the procedure of CSP-1 and the non-defectives identified by CSP-1. Overall, the analytical results indicate that depending on seven parameters (Type I error, Type II error, the selling price of an item, the unit repair cost, the unit return cost, the unit cost of precise inspection, and the process defective fraction), there are three possible optimal inspection policies for CSP-1: “Do not inspect”, “Do 100% inspection”, or any setting for (i, s); for both of the non-defectives identified in CSP-1 and the non-inspected items, there are three possible proportions which should be performed a precise inspection: all, none, or any proportion.     

Two EPQ models with imperfect production processes,inspection errors,planned backorders,and sales returns

In practice the items received in a lot may contain defective items, and during the screening process to eliminate the defective items, the inspector may incorrectly classify a non-defective item as defective (a Type I error) or incorrectly classify a defective item as non-defective (a Type II error). In this paper, we develop two economic production quantity models with imperfect production processes, inspection errors, planned backorders, and sales returns. A closed form solution is obtained for the optimal production lot size and the maximum shortage level for both models. We provide two numerical examples, one in which the defective probability and Type I and Type II inspection errors follow uniform distributions, and the second in which we assume they follow beta distributions. Sensitivity analyses are performed to see the impact of the defective probability, the probability of the Type I inspection error, the probability of the Type II inspection error, the holding cost, and the backordering cost on the optimal solutions. We obtain similar results on the sensitivity analyses for both numerical examples. The results show that the time factor of when to sell the defective items has a significant impact on the optimal production lot size and the backorder quantity. The results also show that if customers are willing to wait for the next production when a shortage occurs, it is profitable for the company to have planned backorders although it incurs a penalty cost for the delay.     

Economic selection of process mean and lot‐sizing decisions for multi‐newsvendor supply chain

Two related problems are integrated in this paper, the first is the targeting problem and another is production/inventory decisions in a supply chain. The supply chain under consideration consists of a supplier of raw material, a single producer, and multiple newsvendors. The producer can adjust the process mean before starting the production run. Once set to a certain target value, the process mean is not changed until the production lot is completed. At the end of a production run, the producer screens the lot and uses specification limits to evaluate the quality of the item. Nonconforming items are scrapped with no salvage value; however, conforming items are delivered to newsvendors who are subjected to random demand. If demand on a newsvendor in a season is lower than anticipated, surplus items will be returned to the producer at a certain transportation cost. We first develop a mathematical model that maximizes the expected total profit of the supply chain. Then, a table for two special functions is devised to simplify the solution method and is used to find the optimal solution of the proposed model. We also study the significance of this integration by comparing the performance of the proposed model with an independent model where the process mean selection and lot‐sizing decisions are found separately.     

Optimum process mean and manufacturing quantity settings for serial production system under the quality loss and rectifying inspection plan

In 1994, Al-Sultan presented a single sampling plan applied in determining the optimum process mean for two machines in a serial production system. However, Al-Sultan did not consider the quality cost for the product within the specification limits, pointed out that the non-conforming items in the sample of accepted lot is replaced or eliminated from the lot, and proposed an integrated model with production and quality. In this study, the author considers the problem of quality loss for the modified Al-Sultan’s model with k machines in a serial production system based on a single sampling rectifying inspection plan. Taguchi’s symmetric quadratic quality loss function is applied in evaluating the product quality. Then, the author further proposes a modified and integrated economic manufacturing quantity (EMQ) model based on the application of the modified Al-Sultan’s model for obtaining the maximum expected total profit of product per unit of time. The numerical results show that the price of an accepted products sold has the most important effect on both the process means and the expected total profit per unit of time.     

An integrated production–distribution inventory system involving probabilistic defective and errors in quality inspection under variable setup cost

This paper presents a probabilistic defective vendor–buyer integrated inventory model with the consideration of quality inspection errors at the buyer's end and setup cost as function of capital investment. An integrated inventory model is established to find the optimal solutions of lot size, setup cost, and the total number of shipments from the vendor to the buyer in one production run, so that the joint expected total cost incurred has the minimum value. We consider three types of continuous probabilistic defective function to find the associated cost of the system. The expected total cost function is derived for each of these three distributions, its convexity is proved via differential calculus. An efficient iterative algorithm is designed to obtain the optimal solution of the model. The computational effort and time are small for the proposed algorithm and it is simple to implement. Numerical examples and sensitivity analysis are used to demonstrate the application and the performance of the proposed methodology. The computational results indicate that if we make decisions with the capital investment in reducing setup cost, it will help to lower the system cost, and we obtain a significant amount of savings to increase the competitive edge in business.     

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.     

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.     

Robust planning in optimization for production system subject to random machine breakdown and failure in rework

This study is concerned with robust planning in optimization, specifically in determining the optimal run time for production system that is subject to random breakdowns under abort/resume (AR) control policy and failure in rework. In most real-life production processes, generation of defective items and breakdowns of manufacturing equipment are inevitable. In this study, random defective rate is assumed and all manufactured items are screened. The perfect quality, reworkable and scrap items are identified and separated; failure-in-rework is assumed. The system is also subject to random machine breakdown; and when it occurs, the AR policy is adopted. Under such policy, the production of the interrupted lot will be immediately resumed when the machine is restored. Mathematical modeling and derivation of the production-inventory cost functions for both systems with/without breakdowns are presented. The renewal reward theorem is used to cope with the variable cycle length when integrating cost functions. The long-run average cost per unit time is obtained. Theorems on convexity and on bounds of production run time are proposed and proved. A recursive searching algorithm is developed for locating the optimal run time that minimizes the expected production-inventory costs. A numerical example with sensitivity analysis is provided to give insight into the optimal operational control of such an unreliable system.     

Lot size variability effects on manufacturing lead time

This paper presents a queueing model for a single-stage manufacturing system. The arrival process at the facility is the superposition of the unco-ordinated arrival processes of various items and is represented by a compound Poisson process. It is shown that the expected waiting time of an average unit depends on the expected batch size and the batch size variability, whereas the expected batch completion time depends only on the expected batch size. The optimal processessing rate is also derived as a function of the appropriate cost factors. A lot sizing model is developed which provides the optimal batch size as a function of inventory-related costs. Finally, it is demonstrated through simulation that the Poisson arrival approximation is less severe when the item mix is composed of a large number of items.     

An EMQ model in an imperfect production process

The intention of this article is to develop a framework of production policy (resumption and non-resumption) in order to find out optimal safety stock, optimal production rate and production lot size. It encompasses specific versions of the concept of quality and inventory model, stochastic machine breakdown and its correcting and regular repair paths with safety stocks. This framework hopefully serves to simplify answers to the important questions: How much safety stocks, production rate and production lot size are required to minimise the total expected system cost. The optimal production rate, production lot size, production run time and safety stocks are determined numerically and the joint effect of process deterioration, machine breakdown and its repair (correcting and preventive) on the optimal decision is investigated for a numerical example. Such an investigation should also yield logistics directions for the design of products and their manufacturing processes.     

Application of optimal control theory to product pricing and warranty with free replacement under the influence of basic lifetime distributions

This study investigates optimal policies for determining price and warranty length when free replacement of defective items is the business policy and the demand is dependent on price, warranty, and cumulative sales. We apply optimal control theory to a profit-maximization model that takes into consideration the expected warranty cost per item. The maximization of market values is based on a pre-determined life cycle and spans across both expansion and saturation phases of the market. We further investigate the optimal policies for a number of basic lifetime distributions, when the demand function is under the setting of separable and logistic growth. We found that as the growth of a product enters different phases of the market, optimal decision policies are characterized by simultaneously increasing or reducing both price and warranty length.     

Optimal periodic and random inspections with first,last and overtime policies

It has been assumed for a standby unit that periodic inspection is performed more easily to detect failures, but such a strict periodic mode would be impractical if the unit is executing some procedures without stops. From the above viewpoint, this paper first optimises a random inspection policy in accordance with random procedure times, compares it with periodic inspection and computes a modified checking cost for random inspection to determine the case where such a random inspection would be adopted. Second, this paper proposes three new inspection models in which inspections with deterministic policies are scheduled strategically while their performances need to be limited by completion times of operation procedures. These policies are called inspection first, inspection last and inspection overtime. The total expected inspection and downtime costs of each model until failure detection are obtained, and optimal policies which minimise them are derived analytically. Furthermore, the three inspection policies are compared with periodic inspection, inspection first and last are compared with each other, and a modified checking cost for inspection overtime is discussed when the policy would be better than periodic inspection.     

Implementing an optimal policy for set-up time reduction in an economic production quantity model

An economic production quantity (EPQ) system consisting of single and multiple items with an optimal policy of set-up time reduction and a fixed increment cost are discussed in the present study. The set-up time reduction ratio as a decision variable under various cases of demand in the EPQ model is considered. It is assumed that the set-up cost is linearly related to the set-up time. The set-up time reduction ratio and the lot size are solved simultaneously to obtain an optimal value of the total annual cost. Numerical examples are presented to demonstrate the accuracy of the proposed method.     

Integrated inventory control and inspection policies with deterministic demand

In this paper, we develop integrated inventory inspection models with and without replacement of nonconforming items. Inspection policies include no inspection, sampling inspection, and 100% inspection. We consider a buyer who places an order from a supplier. When a lot is received, the buyer uses some type of inspection policy. The fraction nonconforming is assumed to be a random variable following a beta distribution. Both the order quantity and the inspection policy are decision variables. In the inspection policy involving determining sampling plan parameters, constraints on the buyer and manufacturer risks are set in order to obtain a fair plan for both parties. A solution procedure for determining the operating policies for inventory and inspection consisting of order quantity, sample size, and acceptance number is proposed. Numerical examples are presented to conduct a sensitivity analysis for important model parameters and to illustrate important issues about the developed models.     

Economic ordering policy for an item with imperfect quality subject to the in-house inspection

This article considers a production/inventory system where each lot of items received or produced contains a random proportion of defective units, items of imperfect quality. The purchaser contacts a 100% inspection in order to identify the perfect (acceptable) quality items. The model examines the following two options for the imperfect quality items: sell them to a secondary market, as a single batch and at a price lower to that of new ones, or rework them at some cost and then use them as new ones to satisfy demand. After inspection, the good quality items are sent to the working inventory warehouse in batches of equal size. For both of these cases, the optimal ordering lot size and the optimal number of batches are obtained. A numerical example illustrates the solution procedure and sensitivity analysis results are reported.     

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.     

EPQ model with learning consideration,imperfect production and partial backlogging in fuzzy random environment

The article scrutinises the learning effect of the unit production time on optimal lot size for the uncertain and imprecise imperfect production process, wherein shortages are permissible and partially backlogged. Contextually, we contemplate the fuzzy chance of production process shifting from an ‘in-control’ state to an ‘out-of-control’ state and re-work facility of imperfect quality of produced items. The elapsed time until the process shifts is considered as a fuzzy random variable, and consequently, fuzzy random total cost per unit time is derived. Fuzzy expectation and signed distance method are used to transform the fuzzy random cost function into an equivalent crisp function. The results are illustrated with the help of numerical example. Finally, sensitivity analysis of the optimal solution with respect to major parameters is carried out.