Production and quality control policies for deteriorating manufacturing system

In this paper, a novel model for a deteriorating manufacturing system is analysed, considering repairs and overhauls of random durations. The machine manufactures one product and the model is further complicated because the quality of the parts’ produced deteriorates according to the wear of the machine and human interventions. When a breakdown occurs, either a repair or an overhaul is performed. The machine is restored to as-good-as-new conditions if the overhaul is selected, and conversely, its condition deteriorates following repairs. Multiple operational states are considered to define an ageing process. The decision variables of the model are the production rate and the repair/overhaul switching strategy. This paper provides new insights to this research area by considering the simultaneous production and repair/overhaul control policy under the effect of deteriorations. The optimal decision policy minimises the total incurred cost comprising the inventory, backlog, repair and overhaul costs over an infinite planning horizon. Our paper differs from other research projects in its consideration of the machine’s history, defined by the number of repairs and multiple operational states. A numerical example is given to illustrate the proposed approach and a sensitivity analysis has been conducted to confirm the structure of the obtained control policies.     

Impacts of collaborative investment and inspection policies on the integrated inventory model with defective items

For an imperfect production system, to reduce quality-related costs, a manager may consider investing capital in quality improvement. In general, the investment expense in reducing the defective rate of items is often paid by the vendor. On the other hand, the buyer may inspect the product quality as the order is received which implies it incurs an inspection cost. In a supply chain integrated system, to accomplish global optimisation, the vendor and buyer can agree to jointly invest capital to improve the imperfect production processes, and the buyer can remove the inspection programme as the defective rate reaches a certain low-level. Hence, this paper investigates the impacts of collaborative investment and inspection policies on an integrated inventory model with defective items. The objective of this study is to seek the optimal order quantity, shipping times from the vendor to the buyer per production run, and the defective rate that minimise the joint total cost per unit time. An algorithm is developed to find the optimal solution. Several numerical examples are presented to demonstrate the proposed model and solution procedure, and then several management insights are obtained from the numerical examples.     

An integrated inventory model involving manufacturing setup cost reduction in compound Poisson process

The collaboration of vendor and buyer is one of the key factors for successful supply chain management. The most common strategy for a cooperative system is to propose an integrated replenishment plan. Almost all inventory models assume that setup cost is deterministic and is not subject to control. However, in many practical situations, setup cost can be reduced at an added investment. The paper assumes that setup cost can be reduced at an added investment and shortage is permitted during the lead time. This article relaxes the assumption that the demand of lead time is deterministic and is assumed to be a compound Poisson process. A model is derived to determine an optimal integrated inventory policy with controllable setup cost. The expected annual integrated total cost function is derived and a solution procedure is established to find out the optimal solution. Finally, a numerical example is provided to illustrate the solution procedure.     

Reverse Logistics: a stochastic EOQ-based inventory control model for mixed manufacturing/remanufacturing systems with return policies

This paper focuses on mixed manufacturing/remanufacturing systems, where manufacturing or purchase of new items integrates product reuse or remanufacturing, with the purpose to achieve a complete and timely demand satisfaction. We formulate a stochastic Economic Order Quantity (EOQ)-based inventory control model for a mixed manufacturing/remanufacturing system. The model is intended to identify the need of placing a manufacturing/purchasing order, to avoid the occurrence of stock-out situations. We then formulate a total cost minimisation problem, to derive the optimal return policy, this latter being a financial incentive paid to customers to increase the flow of returned items. The model developed is investigated through simulations, in order to assess the effect of stochasticity (of demand, return fraction and return delay) on the optimal return policy of the system; then, it is validated through a case study, to derive indications concerning its practical application in real cases. Our study ultimately provides a framework for practitioners to establish EOQ policies in reverse logistics contexts and to evaluate the opportunity of establishing a return policy in those contexts.     

Joint inventory/replacement policies for parallel machines

In many manufacturing settings there is a significant cost associated with lost capacity due to machine failures. When this is combined with long lead times on the procurement of spare parts, it is often necessary to maintain inventories of critical machine components. Thus, the maintenance policy for the machines is inherently coupled to the inventory policy for spare parts. In this paper we identify and investigate the relationship between these two policies.     

The strip-packing problem for a boat manufacturing firm

This paper addresses the problem of minimizing the amount of wasted space when cutting a set of rectangular pieces from a single rectangular sheet of stock material. A simulated annealing algorithm is developed and is shown to significantly outperform three existing heuristics on a set of 37 real-world data sets. In addition, a mathematical programming formulation of the problem and several theoretical lower bounds are developed and used to demonstrate that the simulated annealing solutions are within 9.5% of the optimal solution, on average.     

Analysis of operating policies for manufacturing cells

We present an analytical model for error-recovery problems of unitary production cells and develop a framework for economic justification. Each production cell has its own machine and functional characteristics (e.g. precision, speed, operating cost). Each alternative operating policy of error-recovery for a production cell leads to a different system throughput, scrap rate, and required quantities of parts. However, error recovery cannot be accomplished without in-process inspections. Thus, the central problem discussed in this paper is to maximize profits or throughput rate by selecting an appropriate production cell along with an optimal set of inspection and error recovery policies.     

Optimal policies in multiproduct inventory models

Summary We consider a period review, dynamic multiproduct inventory model with stochastic demand, in which the cost of ordering consists of linear portions for each product as well as a nonlinear term. This nonlinear term depends for example, on the products we order. We prove the existence of an optimal policy and characterize such a policy. We show that an optimal policy reduces to the well-known (, S)-policy, if we spezialise the nonlinear ordering cost in a proper way. Finite horizon results are given.

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Zusammenfassung Wir betrachten ein periodisch kontrolliertes dynamisches Mehrprodukt-Lagerhaltungsmodell mit stochastischem Bedarf, bei dem sich die Bestellkosten aus einem linearen und einem nichtlinearen Anteil zusammensetzen. Der nichtlineare Anteil kann z. B. davon abhängen, welche Produkte bestellt werden. Es wird die Existenz einer optimalen Bestellpolitik gezeigt. Außerdem werden Eigenschaften einer solchen Politik nachgewiesen. Wir zeigen, daß bei Spezialisierung der nichtlinearen Bestellkosten eine optimale Politik eine (, S)-Politik ist. Die Ergebnisse beziehen sich auf den endlichen Planungshorizont.

     

Development and evaluation of cross-training policies for manufacturing teams

This study addresses the problem of developing and evaluating cross-training policies for manufacturing teams from a Human Resource Management (HRM) and Operations Management (OM) viewpoint. A cross-training policy can be regarded as a set of rules to determine the distribution of workers' skills. The specific way in which workers and machines are connected determines the agility of the workforce. In this article, we develop an integer goal programming model to support a consequent application of alternative cross-training policies. A simulation study is performed to assess the performance of the resulting cross-training configurations within three routing structures: a parallel structure, a serial structure, and a job shop structure. Results indicate that within all routing structures, the focus of cross-training policies depends on whether a HRM or an OM viewpoint is considered. Within the parallel and the serial structures, however, HRM and OM goals are compatible and can be integrated within a single cross-training policy. Within the job shop structure, the integration of both OM and HRM goals within one cross-training policy is more difficult.     

Production and subcontracting control for an unreliable manufacturing system with setups

This paper deals with the problem of joint production, setup and subcontracting control of unreliable manufacturing systems producing two product types. The production requires setups each time it switches from one product type to another. Subcontracting is an integral part of the decision-making process due to limited production capacity in existing facility. The objective is to propose an effective control policy for the considered system which simultaneously manages production, setup and subcontracting activities. The complexity of the problem lies in the interaction between internal manufacturing decisions and subcontracting that outsource a part of the production, in a dynamic and stochastic environment. An experimental optimisation approach is adopted to determine the optimal control parameters which minimise the average total cost. Extensive sensitivity analyses are performed to illustrate the robustness and the usefulness of the adopted approach. An in-depth study comparing five control policies across a wide range of system parameters is also conducted. Extended cases closer to reality are also investigated considering elements such as the preventive maintenance and the production of non-conforming products. The best control policy in terms of economic performance is then obtained. Valuable insights providing a better understanding of interactions involving production, setup, and subcontracting are discussed.     

Loading and control policies for a flexible manufacturing system

An experimental investigation of operating strategies for a computer-controlled flexible manufacturing system is reported. The system is a real one, consisting of nine machines, an inspection station and a centralized queueing area—all interconnected by an automatic material-handling mechanism. The operating strategies considered involve policies for loading (allocating operations and tooling to machines) and real-time flow control. A detailed simulation was employed to test alternatives. The results are different from those of classical job shop scheduling studies, showing the dependence of system performance on the loading and control strategies chosen to operate this flexible manufacturing system. Loading and control methods are defined that significantly improve the system's production rate when compared to methods which were previously applied to the system. Finally, some conclusions are presented concerning the control of these automated systems.     

A study of an integrated inventory with controllable lead time

The Japanese experience of Just-in-Time (JIT) production has shown that there are advantages and benefits associated with the efforts to reduce inventory lead time and the associated inventory cost. The length of lead time directly affects the customer service level, inventory investment in safety stock, and the competitive abilities of a business. In most of the literature dealing with inventory problems, either a deterministic model or probabilistic model, lead time is viewed as a prescribed constant or a stochastic variable, and is not subject to control. However, in many practical situations, lead time can be reduced by an additional cost. Moreover, the successful implementation of JIT production in today's supply chain enviromnent requires a new spirit of cooperation between the buyer and the vendor (Goyal and Srinivasan 1992). A desirable condition in long time purchase agreements in such a manufacturing environment is the frequent delivry of small quantities of items so as to minimize inventory holding cost for the buyer. The vendor also needs to minimize his or her total inventory costs. An integrated inventory model that allows the two trading parties to form a strategic alliance for profit sharing may prove helpful in breaking down the traditional barriers. This paper presents an integrated inventory model with controllable lead time. The model is shown to provide a lower total cost and shorter lead time compared with those of Banerjee (1986) and Goyal (1988), and is useful for practical inventory problems.     

Joint optimization of maintenance and inventory policies for a simple system

We examine age replacement and ordering decisions for a system with only one component subject to random failure and with room for only one spare in stock. The system incurs costs for replacement, shortage, holding, and breakage; the lead time for receipt of an ordered spare is constant. We consider the solvability and desirability of jointly optimizing these two traditionally separate decisions. We show that the problem has some convexity properties that make it amenable to minimization. For our data set, we find that using separate optimization gives an average loss of 3% relative to the joint minimum; about a tenth of die time the difference was more than 10%, but in general this loss can vary from zero to arbitrarily large.     

Multi-echelon service models for inventory systems under different rationing policies

In this paper we model the service performance of two-echelon divergent production networks consisting of one central stock-point feeding a number of end stock-points where the external demand is realized. The systems we consider allow all stock-points to hold inventory and use periodic review ordering policies at all levels. Whenever the lower echelon has insufficient inventory to cover all upper echelon requisitions some policy to ration the available material is needed. Concentrating on one push and one pull rationing policy, we explore the system dynamics and develop models for three popular measures of the system service performance. All models make use of non-dimensional ratios which drastically reduce the number of parameters involved. Although these models are only approximate, numerical and simulation results demonstrate the adequacy of the approximations involved.     

On deficiencies of common ordering policies for multi-level inventory control

We consider two common types of ordering policies for multi-level inventory control: installation stock (R,Q)-policies and echelon stock (R,Q)-policies. The batch quantities are assumed to be given, but each policy is optimized with respect to its reorder point R. We demonstrate that there is no bound for the worst case performance ratio of these policies when applied to distribution inventory systems with a central warehouse and a number of retailers.     

Optimal inventory policies for uniform replenishment systems with time-dependent demand

This study develops an analysis of lot size inventory systems where the replenishment rate is uniform and demand follows a power demand pattern. Shortages are not allowed. Holding cost, replenishing cost and purchasing cost are considered in inventory system control. The objective of the study is to find the economic production quantity that minimises total inventory cost per unit of time. We conclude that optimal inventory policies depend on the demand pattern index chosen to represent customer demand. Theoretical results are illustrated with a business case study. A sensitivity analysis is proposed to describe the optimal policy behaviour.     

Zero inventory and firm performance: a management paradigm revisited

According to the ‘zero inventory’ paradigm, inventory reflects waste and should be eliminated in order for performance to rise. In this study, we investigate the effect of inventory holding on firm performance, analysing 3057 firm years of data. Interpreting performance as a function of inventory, results show that firms with the lowest inventory have the worst performance (and vice versa). When understanding inventory as a function of performance, results indicate that low-performing firms carry the least inventory, whereas high-performing firms have the highest stocks. Besides questions of causality, our results do not support a paradigm which suggests that firms should move toward zero inventory.     

On optimal and approximate policies for a multistage production/inventory problem

A stochastic multistage production/inventory problem can be solved by an approximate procedure developed by Clark and Scarf. Previous researchers have made comparisons of the solutions obtained by this procedure with optimal solutions obtained by a Markov Decision Process (MDP) solution procedure and found that the Clark-Scarf procedure gives close to optimal solutions. Their experimentation was restricted to two-stage problems. In this paper we extend the comparison to three-stage problems. It is found that the differences in average costs per period grow noticeably as the number of stages of the problem increases. Observations that may facilitate the development of a heuristic procedure to improve the Clark-Scarf solution are given.     

Optimising replenishment policy for an integrated production inventory deteriorating model considering green component-value design and remanufacturing

This paper develops an integrated deteriorating production inventory model with green component design, remanufacturing and JIT deliveries. We provide a rigorous analysis to derive the number of deliveries, the optimal cycle time of deliveries, and the delivery sise for the integrated buyer-supplier inventory deteriorating model. Distinct from the former concept of average inventory level, our paper proposes a significantly different approach to deal with the first production batch and uses a revised method to approximate the relationship between the supplier's production and storage time. A manufacturing case example of Taiwan computer power-supply component producers is presented to illustrate the theory. It is shown that the parameters of component-value design and unit holding cost are the critical factors affecting the deteriorating inventory planning.