Industrial Engineering

This paper deals with an integrated production maintenance model where preventive maintenance (PM) activities are carried out at the end of each production run or at failure, whichever of them occurs first. PM activities take a fixed amount of time. However, due to the random nature of failures, the stock built during the production period may deplete before the next

This paper deals with an integrated production maintenance model where preventive maintenance (PM) activities are carried out at the end of each production run or at failure, whichever of them occurs first. PM activities take a fixed amount of time. However, due to the random nature of failures, the stock built during the production period may deplete before the next production run starts, leading to some loss in demand. After N production runs, the process is replaced (or undergoes a major repair), which brings it to the "as-good-as-new" condition. A mathematical model is derived for this problem and a model analysis conducted to characterize optimal solutions. Numerical examples are used to illustrate the proposed model and conduct a sensitivity analysis with respect to key model parameters.

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 his inventory level drops to a certain point, due to demand which is stochastic in nature. 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. The order quantity, reorder point and the inspection policy are decision variables. In the inspection policy involving determining sampling plan parameters, constraints on the buyer and manufacturer risks is 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.

In this paper, we develop an integrated model for the joint optimization of the economic production quantity, the economic design of " x-control chart, and the optimal maintenance level. This is done for a deteriorating process where the in-control period follows a general probability distribution with increasing hazard rate. In the proposed model, Preventive Maintenance (PM) activities reduce the shift rate to the out-of-control state proportional to the PM level. Compared to the case with no PM, the extra cost of maintenance results in lower quality control cost which may lead to lower overall expected cost. These issues are illustrated using an example of a Weibull shock model with an increasing hazard rate. 0740-817X Ó 1999``IIE''

We develop multistage lot-sizing models for imperfect production processes. The effect of inspection errors in screening non-conforming items at various stages has been incorporated. Inspection and restorstion of the processes at all stages have also been considered. Numerical examples are presented to illustrate various aspects of the models developed. It is shown that when inspection and restoration are introduced, lower costs are incurred and larger lot sizes are produced because of reductions in quality control costs.

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.

In this paper, we address the problem of determining optimum inspection schedules for a single deteriorating production system with a predetermined replacement cycle. It is assumed that, at different discrete points in time over the fixed planning horizon, the facility is inspected to detect its operating state and then it goes over an imperfect preventive maintenance routine to enhance its operating performance. Moreover, the facility undergoes minimal repair once detected in an ''out-of-control'' state. We also adopt the concept of discounted cash flow analysis to account properly for the effect of time value of money on the inspection policies. Under these settings, we formulate the discounted integrated inspectionmaintenance problem as a dynamic programming model with general time to failure distribution. After illustrating the model with a numerical example, we perform sensitivity analysis to investigate the effects of some input parameters on the expected present worth and the number of inspections.

The effect of ageing on the deterioration rate of most repairable systems cannot be ignored. Preventive maintenance (PM) is performed in the hope of restoring fully the performance of these systems. However, in most practical cases, PM activities will be only able to restore part of the performance. Bridging the gap between theory and practice in this area requires realistic modelling of the effect of PM activities on the failure characteristics of maintainable systems. Several sequential PM models have been developed for predetermined PM interval policies but much less effort has been devoted to age-based ones. The purpose of this paper is to develop an age-based model for imperfect PM. The proposed model incorporates adjustment factor in the effective age of the system. The system undergoes PM either at failure or after a predetermined time interval whichever of them occurs first. After a certain number of such PMs, the system is replaced. The problem is to determine both the optimal number of PMs and the optimal PM's schedule that minimize the total longterm expected cost rate. Model analysis relating to the existence and uniqueness of the optimal solutions is provided. Numerical examples are presented to study the sensitivity of the model to different cost function's factors and to illustrate the use of the algorithm.

In this paper, we consider the economic production quantity problem in the presence of imperfect processes. In the literature, the time to shift from the in-control state to the out-of-control state is assumed to be exponentially distributed. In this study, we consider general time to shift distributions and provide distribution-based and distributionfree bounds on the optimal cost. For the exponential case, we compare the optimal solutions to approximate solutions proposed in the literature. A numerical example is used to illustrate the analysis presented and to conduct a sensitivity analysis in order to see the effect of the input parameters on the various solutions to the problem.

In this paper, we compare recent efficient heuristics proposed for solving the joint replenishment problem. A heuristic based on the relaxation of a nonlinear programming formulation of the problem proposed by Hariga is the most efficient heuristic for solving the joint replenishment problem in view of its speed and quality of solution.

A bstract. This paper deals with multi-stage lotsizing models for imperfect production processes. The e ect of imperfect quality on lotsizing decisions and e ect of inspection errors are taken into consideration in the proposed models. Numerical examples are presented for illustration purposes. The developed models are very helpful for justifying quality assurance and quality improvement e orts.

With growing focus on supply chain management, firms realise that inventories across the entire supply chain can be more efficiently managed through greater cooperation and better coordination. This paper deals with inventory and production coordination in a three-layer supply chain involving suppliers, manufacturers and retailers. Each stage may have more than one firm. It is assumed that the cycle time at each stage is an integer multiple of the cycle time of the adjacent downstream stage. In addition, the produced lot at each stage is sent to the adjacent downstream stage in equal shipments. Shipments are sent as soon as they are produced and there is no need to wait until a whole lot is produced. A cost minimisation model and its solution procedure are derived. A numerical example is presented for illustrative purposes. This policy leads to considerable savings as compared to the scheme that allows shipments only after the whole lot is produced.

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Previous research on the joint vendor-buyer problem focused on the production shipment schedule in terms of number and the size of batches transferred between two parties. It is a fact that transportation cost is a major part of the total cost. However, the transportation cost is only considered implicitly as a part of fixed setup or ordering cost and thus the transportation cost is assumed to be independent of the size of the shipment. As such, the effect of the transportation cost is not adequately reflected in final planning decisions. There is a need for models involving transportation cost explicitly for better decision-making. In this study we analyze the vendor buyer lot-sizing problem under equal-size shipment policy. We introduce the complete solution of the problem in an explicit and extended manner that has not existed in the literature. We also consider the case where transportation cost is taken into account. The structure of the transportation cost is assumed to be an all-unit-discounted format. We develop a heuristic procedure to find a quality solution for the model with transportation cost. We give numerical examples to support the analysis.

This paper explores the role of Internet of Things (IoT) and its impact on supply chain management (SCM) through an extensive literature review. Important aspects of IoT in SCM are covered including IoT definition, main IoT technology enablers and various SCM processes and applications. We offer several categorisation of the extant literature, such as based on methodology, industry sector and focus on a classification based on major supply chain processes. In addition, a bibliometric analysis of the literature is also presented. We find that most studies have focused on conceptualising the impact of IoT with limited analytical models and empirical studies. In addition, most studies have focused on the delivery supply chain process and the food and manufacturing supply chains. Areas of future SCM research that can support IoT implementation are also identified.