Production planning and inventory control in a company manufacturing PC parts: A case study

In this paper, we present a case study on the production planning and inventory system in a company manufacturing personal computer (PC) parts. In the case study, the targets are specified for developing a system for production planning and inventory control. The current state of the company is analysed for clarifying the points necessary to achieve the targets. Also, a system based on the analysis is proposed and its effects are estimated.     

Determination of recovery effort for a probabilistic recovery system under various inventory control policies

In this study we investigate the desired level of recovery under various inventory control policies when the success of recovery is probabilistic. All the used and returned items go into a recovery process that is modelled as a single stage operation. The recovery effort is represented by the expected time spent for it. The effect of increasing recovery effort on the success probability together with unit cost of the operation is included by assuming general forms of dependencies. Alternative to recovered items, demand is satisfied by brand-new items. Four inventory control policies that differ in timing of and information used in purchasing decision are proposed. The objective is to find the recovery level together with inventory control parameter that minimize the long-run average total cost. A numerical study covering a wide range of system parameters is carried out. Finally computational results are presented with their managerial implications.     

Lowering Inventory Systems Costs by Using Regression-Derived Estimators of Demand Variability*

Scientific techniques for inventory management typically are applied to systems containing many items. Such techniques require an estimation of the demand variance (and mean) of each item from historical data. This research demonstrates a significant potential for improvement in system cost performance from using least-squares regression fits of a variance-to-mean functional relation instead of the standard statistical variance estimate. Even when there is a moderate degree of heterogeneity among items and when the form of the variance-to-mean relation is misspecified, substantial cost savings may be realized. The cost of statistical uncertainty may be reduced by half. The research also provides evidence that system cost is fairly insensitive to the number of items used to fit the regression. This paper provides the underlying reason why a regression-derived variance estimator yields lower cost: it is less variable than the usual individual item variance estimator.     

A DISCRETE-IN-TIME PROBABILISTIC INVENTORY MODEL FOR DETERIORATING ITEMS

A probabilistic scheduling-period inventory model continuous in units and discrete in time is developed for deteriorating items where deterioration is assumed to be a constant fraction of the on-hand inventory. The model is developed under the conditions of instantaneous delivery and no shortages. An example followed by sensitivity analysis is given to illustrate the derived results.     

Multi-item production lot-size inventory model with varying order cost under a restriction: A geometric programming approach

In this paper we present a geometric programming approach for determining the inventory policy for multiple items having varying order cost, which is a continuous function of the order quantity, and a limit on the total average inventory of all items. Our model is a generalization of that of Gupta and Gupta for unrestricted single-item order quantity model with varying order cost and assumes the same order cost function. This cost function relates well to real-life situations since it increases as the order quantity increases and, at the same time, it is easy to handle when deducing previous work as special cases of our model since it is easily reducible to a constant. An example is solved to illustrate the method.     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

A Note on the Effect of Sudden Obsolescence on the Optimal Lot Size

In most management situations, the decision to hold inventory involves some element of obsolescence risk The traditional approach to this problem, in both theory and practice, is to incorporate obsolescence costs in the inventory holding cost. This note explores this issue and demonstrates that the traditional approach is appropriate for items subject to sudden obsolescence; that is, for items with demand lifetimes that are exponentially distributed.     

Cost and Shortage Trade-Offs in Aggregate Production Planning*

It is exceedingly difficult, if not impossible, to measure shortage costs. To bypass this difficulty in aggregate production planning, this paper develops an optimal policy function (piecewise linear or a curve) for trade-offs between shortages and the sum of production and inventory costs. The optimal management decision is based on this function. It should be of major interest in production planning since similar functions for inventory management have been successfully applied in practice.     

Generalization of multi-item,multi-retailer distribution system

The procedure developed by Muckstadt and Roundy is generalized. In a multi-echelon inventory system with a single warehouse and multi-retailers, some di erent items with constant demand rates are distributed. Considering set-up and holding costs as well as the cost of joint shipment of items from the warehouse to any retailer, the objective is to minimize the total costs of the system. In the proposed algorithm the assumption of nested policies is relaxed. The procedure introduced works for both nested and non-nested policies.     

Inventory control for the supply chain: An adaptive control approach based on the identification of the lead-time

In this paper, an Internal Model Control (IMC) scheme is incorporated in production inventory control systems in a complete supply chain. This control scheme presents a good target inventory tracking under the perfect knowledge of the system. Furthermore, the inventory tracking and load disturbance rejection control problems can be tackled separately. However, the closed-loop performance of the IMC scheme may be degraded due to a mismatch between the modelled and actual delay or to the fact that delays may be time-varying. Thus, the IMC control scheme is enhanced in this work with a novel method for the online identification of lead times based on a multimodel scheme. In this way, all benefits of the IMC scheme can be exploited. A detailed discussion of the proposed production inventory system is provided including a stability and performance analysis as well as the identification capabilities of the algorithm. Several simulation examples illustrate the efficiency of the approach.     

基于改进策略的混合型制造/再制造系统分析

在制造和再制造并存的混合型系统中,制造商需要同时协调新产品生产过程和旧产品再制造过程,这种双向物流的集成运作使得传统的生产规划和库存管理方式不再适用,如何构建一种有效的控制策略来协调生产过程和再制造过程就显得十分关键。本文在优化库存信息的基础上提出了一种适用于混合系统的改进策略,同时考虑到系统复杂性,主要采用控制理论中的传递函数技术构建了系统模型。仿真结果表明,本文提出的改进策略不仅可以有效协调新产品生产过程和旧产品再制造过程,而且还可以显著改善系统性能。     

An echelon inventory-based single-stage cost function for a two-station tandem system

We propose an alternative cost-accounting function for inventory control problems on a make-to-stock setting. Our proposal is based on observing that the traditional holding and backlog parameters introduce some odd short term distortions on the inventory state space. Our single-stage cost function accounts for echelon inventories and possesses a pair of cost parameters for each echelon inventory variable, depending on whether it is positive or negative. With the modified cost-accounting function, we study a twostation tandem system producing a single product, and investigate how it compares with the performances obtained with the usual single-stage cost function. The results available so far show that the optimal policies approach a multi-echelon base stock structure for each machine. Also, the service levels achieved are better under the modified function without increasing the levels of finished goods inventory.     

Multiechelon (R,S) Inventory Model*

Most studies in multiechelon inventory systems have concentrated on understanding the specific aspects of a system's behavior. The problem of optimal policy computation has largely been ignored. In this paper, we investigate a two-echelon inventory system experiencing stochastic demand and a pull system of inventory allocation. Both echelons use an order-up-to-level type control policy. A mathematical model is developed to determine the optimal order level at all echelons and validated through simulation. Two simple algorithms to locate the optimum solution are presented. The use of graphical tools in optimal policy calculation is also discussed.     

Shop floor control system for tool rooms

A shop floor control system (SFCS), which is the most important component of any production control system, ff has a direct e ect on the productivity of a tool room. The SFCS presented in this paper aims at streamlining various tool room activities, such as process planning, operations scheduling, loading, progress monitoring, and performance monitoring. The system discussed in this paper is characterized by simplicity and is user friendly. Basic information, consisting of three types of information (order details, process details, and part details), is input through interactive dialogue sessions. On-line updating of the process information is carried out, again through interactive dialogue sessions. The basic input to the system along with the on-line updating enables a number of useful and important reports and documents to be generated ff by the system for e ective control of the shop floor. The reports generated include operations scheduling, process sheet, part list, ffi job card, load pending report, e ciency report, etc. This SFCS is developed for a medium sized tool room in an automotive company and its successful implemention reduced paperwork and improved resource management and has resulted in productivity. It can be said that this system offers a first venture into computer integrated manufacturing (CIM) for a tool room.     

Testing for Nonlinear Dependence in Inventory Data

This paper describes the properties of nonlinear dynamical systems in demand data and assesses the implications for inventory management. A test from Brock, Dechert, and Scheinkman (BDS) [6] for detecting nonlinearities is presented. This test assists inventory managers with two issues. First, it can be used to detect departures from the independence and stationarity assumptions of particular inventory models, thereby identifying the need for more suitable models. Second, the BDS test can determine whether forecasting model improvements are possible, and can measure improvements in the forecasting model process. The corresponding reductions in forecast errors improve inventory management and lead to reduced inventory costs. Using actual weekly demand for oil filters, this paper demonstrates the use of the BDS test and the effects of nonlinearities in demand data on inventory model performance.     

An Empirical Study of Inbound Consolidation Opportunities

The current deregulated transportation environment has fostered wider freight rate differentials based on shipping weight. As a result, grouping inventory items for the purpose of consolidating inbound replenishment orders can be cost-effective. The pressure in some industries for just-in-time delivery of small lots has also created new opportunities for consolidation of orders. The objective of this research is to identify inventory-transport conditions where a consolidation strategy has cost-reduction potential. Logistics cost generated by ordering an ensemble of items consolidated into groups is compared to those generated by two independent, item reorder strategies. Using data from 150 ensembles, the cost-reduction potential of consolidating was correlated with characteristics of the individual inventory items in an ensemble, a dominant group of items in the ensemble, and the ensemble itself. Finally, response functions were derived and used to test the external validity of the results. For this purpose we used 25 randomly selected inventory ensembles obtained from a retail merchandising firm.     

MRO inventory reduction—challenges and management: a case study of the Tennessee Valley Authority

Emphasis on maintenance, repair, and operations inventory (or MRO inventory) can lead to improved inventory control, reduced operational costs, enhanced productivity, and increased cost accounting accuracy. To review the benefits of MRO inventory reduction, as well as highlight the management challenges associated with the process, a case study of the Tennessee Valley Authority (TVA) is presented. TVA is a not-for-profit electric power generation entity. TVA standardised inventory policies and procedures. Their comprehensive five-year plan included employee training, changes in organisational structure and strategy, reduced MRO inventories and the establishment of new growth drivers. Net inventory reductions of $47 million were realised. Suggestions for future MRO inventory reductions as well as replication of the management involvement and improvement process in other organisations are included.     

Solving the Economic Lot-Scheduling Problem Using the Method of Prime Subperiods

In recent years the reported successes of Japanese production systems, particularly the just-in-time approach to inventory control, has caused managers to focus more of their attention on efficient decision-making procedures for determining production schedules that minimize inventory costs. One such potential area of attention is the economic lot-scheduling problem (ELSP), which occurs in a variety of manufacturing environments where machining operations are prevalent. The economic lot-scheduling problem addresses the determination of lot sizes for N products with constant demand (and cycled through one machine with a given production rate) to minimize setup and inventory costs. The most successful solution approaches to the ELSP have been based on the concept of a basic period that is of sufficient length for the production of all items, even though each item might not be produced during each repetition of the basic period. This paper proposes a heuristic approach to the solution of the ELSP (referred to as the method of prime subperiods), which is an extension of the basic period approaches. The procedure is described and demonstrated via an example and then tested using a set of six example problems previously employed in the literature related to the ELSP. The results indicate as good or superior performance by the proposed method of prime subperiods.     

航空公司机上周转品多基地库存优化模型

在民航业日益激烈的市场竞争环境下，航空公司对成本控制的精细化管理显得尤为重要。本文基于航空公司的实际背景，针对为旅客提供的机上周转品，建立了一个多基地库存系统的库存优化模型。该模型以系统的总库存成本最小为目标，在考虑需求、回收、调运、安全库存等因素下，决策一个订货周期内的订货及调运方案。基于最优解的分析，在成本参数满足一定条件下，可以得到系统最优的期初订货量；在此基础上，可以将该模型转化为一个网络流模型，参考最小费用最大流算法，设计了一个多项式求解算法来求解该网络流模型，进而得到各基地之间的最优调运量，并证明该算法的最优性；此外，根据期初订货量可行解的范围，设计了一个求解原库存模型的启发式算法。通过实例分析，验证了该模型与两种算法的有效性。     

An arborescent inventory model in a supply chain system

This study develops an arborescent (tree-like) inventory model with a constant demand rate. By considering the integration of the producer, distributors and retailers, a mathematical model and an economic ordering policy are developed. It can be shown that the integrated approach results in an impressive cost-reduction compared with an independent decision by the partial party. A numerical example of an arborescent inventory system is attached to demonstrate the economic ordering policy with the help of mathematical software - Maple V.