Optimal inventories for repairable redundant systems with aging components

Complex systems that are required to perform very reliably are often designed to be “fault-tolerant,” so that they can function even though some component parts have failed. Often fault-tolerance is achieved through redundancy, involving the use of extra components. One prevalent redundant component configuration is the m-out-of-n system, where at least m of n identical and independent components must function for the system to function adequately.Often machines containing m-out-of-n systems are scheduled for periodic overhauls, during which all failed components are replaced, in order to renew the machine's reliability. Periodic overhauls are appropriate when repair of component failures as they occur is impossible or very costly. This will often be the case for machines which are sent on “missions” during which they are unavailable for repair. Examples of such machines include computerized control systems on space vehicles, military and commercial aircraft, and submarines.An interesting inventory problem arises when periodic overhauls are scheduled. How many spare parts should be stocked at the maintenance center in order to meet demands? Complex electronic equipment is rarely scrapped when it fails. Instead, it is sent to a repair shop, from which it eventually returns to the maintenance center to be used as a spare. A Markov model of spares availability at such a maintenance center is developed in this article. Steady-state probabilities are used to determine the initial spares inventory that minimizes total shortage cost and inventory holding cost. The optimal initial spares inventory will depend upon many factors, including the values of m and n, component failure rate, repair rate, time between overhauls, and the shortage and holding costs.In a recent paper, Lawrence and Schaefer [4] determined the optimal maintenance center inventories for fault-tolerant repairable systems. They found optimal maintenance center inventories for machines containing several sets of redundant systems under a budget constraint on total inventory investment. This article extends that work in several important ways. First, we relax the assumption that the parts have constant failure rates. In this model, component failure rates increase as the parts age. Second, we determine the optimal preventive maintenance policy, calculating the optimal age at which a part should be replaced even if it has not failed because the probability of subsequent failure has become unacceptably high. Third, we relax the earlier assumption that component repair times are independent, identically distributed random variables. In this article we allow congestion to develop at the repair shop, making repair times longer when there are many items requiring repair. Fourth, we introduce a more efficient solution method, marginal analysis, as an alternative to dynamic programming, which was used in the earlier paper. Fifth, we modify the model in order to deal with an alternative objective of maximizing the job-completion rate.In this article, the notation and assumptions of the earlier model are reviewed. The requisite changes in the model development and solution in order to extend the model are described. Several illustrative examples are included.     

Managing unofficial inventory: a piece of the materiel management foundation

The implementation plan will remain the same: target an area of opportunity, measure and document the amount and value of the unofficial inventory, establish PAR levels, implement the use of hand-held terminals to assist in inventory control, and integrate inventory control with the implementation of new programs that will impact ordering, receiving, distribution, and invoicing. It is anticipated that the inventory in the main OR alone can be reduced by $1.5 million if we move forward with a stockless JIT system. This would reduce the days of inventory on hand from approximately 100 days to between 7 and 14 days. This could also mean a holding cost reduction of $150,000. The merit of reducing unofficial inventory is evident. Managing unofficial inventory is merely one piece of the successful materiel management foundation. The other foundation pieces include contract compliance and price negotiations, systematic methods of ordering products, and timely distribution of products to the end user. PHS cannot effectively move forward to a new, innovative materiel system for the future until we first measure, analyze, and document the present conditions. Once the foundation is laid by improving present business practices, then the framework of the structure can be designed and constructed. The goal is to implement a system that utilizes the full potential of people, equipment, logistics, and information so that our customers, the patient caretakers, do not have to worry about anything except the delivery of quality care.(ABSTRACT TRUNCATED AT 250 WORDS)     

Pricing competition with inventory considerations in a hazard rate-prone market of durables

This paper addresses Bertrand-type pricing competition between two firms producing partially differentiated durables over a finite planning horizon. The demand for durables, characterized by increasing returns of scale to a price reduction, is led by the hazard rate. While the effect of inventories on pricing of non-durables is widely recognized, the management and marketing literature typically overlooks this effect in regard to horizontally competing firms for durables. In this paper we show that the pricing trajectory of durables may significantly alter when inventory dynamics are accounted for. In particular, the price may hike upwards before dropping; gradually grow; or even stay at the same level over the entire product life while it would only decline if inventories and related costs are disregarded. Furthermore, the well-known, optimal pricing strategy of following the pattern of sales does not necessarily confirm even for symmetric equilibria when the competing firms have either an inventory surplus or shortage.     

The retail inventory method: The third major costing system

An organization that has but a single product would be a rarity in the United States today. While single-product firms and tools such as break-even analysis may have been in vogue at the turn of the century, today jointness pervades the scene. The bank that issues a mortgage to a customer also may have managed his or her checking account or granted a student loan to his or her daughter. The department store that sold a suit one week earlier may have attracted the customer with its furniture, toys, and cosmetics. The hospital whose obstetrical team delivered the baby may have been chosen because its excellent orthopedics department set the husband's broken leg three years prior. The sporting goods manufacturer may sell its golf clubs because of its reknown for skis and tennis rackets. It makes no difference whether it is products or services or departments; all share equipment, time, and reputation. The list goes on forever; jointness is the rule, not the exception.Management can pretend that there is only one product and attempt to isolate its effects, as if it were in a vacuum. However, pretending does not eliminate jointness and the purifying assumption is apt to mislead analysis. So how should jointness be treated?Other than the mathematical programming models of the last forty years, only one model for dealing with jointness has been widely adopted for most of the twentieth century; that model is the retail inventory method. The retail system typically is used by department stores to control inventories that consist of 100,000 or more items.The retail system recognizes costs and prices, inflation and obsolescence, mistakes and successes. It tracks purchases and sales, deals with discounts and transfers, and controls investment while providing an estimate of ending inventory. Fortunately, the retail system, the favorite of the department store and the boutique, could be used in the factory as well as in a variety of service and nonprofit organizations.This article briefly reviews the retail method and then uses linear programming (LP) and postoptimality analysis to modernize the traditional conceptions—to attempt to make a good system even better.Many constraints are studied including overlapping seasons, sales quotas, target inventories, product life cycles, and spatial and monetary limitations, among others. In the process, one comes to appreciate the size of the inventories being controlled, the human and departmental interactions, and the usefulness of the LP-retail system (“knotty retail” is perhaps an appropriate name) not only to generate cash budget estimates and to manage stock levels, but also to select the most satisfying alterations of managerial policy.The article concludes by discussing further constraints and other types of organizations that might benefit from adapting the retail system.     

The cost of inflated planned lead times in MRP systems

Much of the current literature in the field of production and inventory control systems stresses the need to revise traditional forms of thinking regarding production processes, the role of inventories for work in process, and the need for reduced lead times or flow times. Group technology, manufacturing cells, and other means of incorporating repetitive manufacturing techniques into traditional job-shop settings constitute the leading edge in system development.Still, there is resistance to these dramatic changes, and traditional “business as usual” methods still predominate. This study attempts to illustrate graphically the cost justification associated with reduction in lead times which generally results from these new concepts. In most job shops today, lead times are much longer than they need to be due to inflation of lead time estimates. Actual lead times for the manufacture of fabricated and assembled products have been shown to be a direct consequence of the planning lead times used in the MRP planning process—a form of self-fulfilling prophesy.The research employs a simulation model of a factory using MRP as a planning tool in a multiproduct, multilevel production environment. Manufacturing costs constitute the dependent variable in the experiments, defined as the sum of material costs (including expedite premiums), direct labor costs (including overtime premiums), inventory carrying costs, and overhead costs. The independent variable being manipulated is the planned lead time offset used in the MRP planning process. Twenty values of planned lead time are evaluated ranging from a value that includes no slack time at all (pure assembly line) up to a value that allows 95% slack (queue) time which, unfortunately, is not uncommon in many job shops today. Stochastic variables in the model include customer demand and actual processing times—the sum of set-up and run times.The result of the study is a cost curve formed over the range of independent lead time variables that is constructed using nonlinear regression techniques. The conclusions from the resultant graph clearly indicate the cost consequences of long lead times, with exponential cost increases beyond the 80–90% queue time level. Total costs are 41% higher at the maximum lead time allowance compared to the minimum. Clearly, this study demonstrates the need for lead time reduction, either through downward adjustment of MRP planned lead times or by introducing new manufacturing concepts.     

A new focus on inventory performance and bottom-line profits

This article is about a new way to measure inventory performance and about putting a dollar focus on inventory management priorities. It reviews the financial impact of inventories and shows how the information from any materiel requirements planning (MRP), MRP II, ERP, DRP, or orderpoint system can be used for setting individual objectives for inventory reduction, measuring performance by inventory segment, and monitoring continuous improvement. It will also consider the merits of paying performance bonuses to materiel planners and review some inventory reduction results.     

THE RESURGENCE OF INVENTORY RESEARCH: WHAT HAVE WE LEARNED?

Abstract. Recent empirical and theoretical research on business inventories is surveyed and critically evaluated. While most inventory research has had macroeconomic motivations, we focus on its microtheoretic basis and on potential conflicts between theory and evidence. The paper asks two principal questions. First, how can inventories, which are allegedly used by firms to stabilize production, nonetheless be a destabilizing factor at the macroeconomic level? Second, why, if firms are following the production-smoothing model, is production more variable than sales in many industries? We suggest that the so-called (S,s) model may help answer both questions.     

What inventories tell us about aggregate fluctuations—A tractable approach to (S,s) policies

We estimate a DSGE model with (S,s) inventory policies. We find that (i) taking inventories into account can significantly improve the empirical fit of DSGE models in matching the standard business-cycle moments (in addition to explaining inventory fluctuations); (ii) (S,s) inventory policies can significantly amplify aggregate output fluctuations, in contrast to the findings of the recent general-equilibrium inventory literature; and (iii) aggregate demand shocks become more important than technology shocks in explaining the business cycle once inventories are incorporated into the model. An independent contribution of our paper is that we develop a solution method for analytically solving (S,s) inventory policies in general equilibrium models with heterogeneous firms and a large aggregate state space, and we illustrate how standard log-linearization methods can be used to solve various versions of our inventory model, generate impulse response functions, and estimate the model׳s deep structural parameters.     

Inventory management in the just-in-time age

JIT will change our conventional thinking concerning the management of inventories and streamline our methods for inventory control. Proper selection and implementation of these methods will yield substantial benefits by improving customer service, shortening delivery lead times, and significantly reducing inventory investment. It does not, however, eliminate the need for sound inventory planning.     

How to use benchmarking to reduce planning and purchasing costs

Each year at budget time, the standard question asked of the materiel management group is "Why do you have so many people?" Our answer had been that we do not have enough people. With more people, we could lower total cost and manage inventories better. The inevitable standoff occurs with each side feeling that the other does not understand the need for materiel management services. In early 1993, we decided to be prepared to answer the famous question of Dr. W. Edwards Deming, "How do you know?" We wanted to show people we really did know our business and thus initiated a project to benchmark planning, purchasing, and scheduling services of other companies. This article shares not only the results of the benchmarking efforts, but also the techniques for getting started.     

Implementing structure and control over unofficial inventories in a multispecialty group practice

Materiel managers have been in control of most aspects of the supply chain except for the inventories of the end users, which account for 70 percent of the inventory supply dollars. When the Materials Manager at Lexington Clinic in Lexington, Kentucky, was approached by the Clinic's Chief Executive Officer to implement cost containment measures, the Materials Manager seized the opportunity to implement a six-step program aimed at controlling those supply dollars. Through requisition training, enforcing approval levels, limiting the number of requisitioners, and establishing par levels on floor inventories, the clinic's "unofficial" inventory supply dollars were reduced by 7 percent in the first 12 departments where the par levels were established. The program was hailed as a tremendous success and a positive experience for everyone, from nurses to warehouse clerks.     

Cultural change--empowerment at Sweetheart Cup Company, Inc., Bakery Division

Sweetheart Cup Company always has been associated with fun products--fast food containers, straws, ballpark drink glasses, and maybe the most fun of all--ice cream cones! But making these products of pleasantry at times has not been as festive as it would seem. Sweetheart Cup Company has had its ups and downs in terms of many of the typical manufacturing measurements, but in 1994--under the direction of newly appointed Chief Operating Officer Bill McLaughlin--Sweetheart Cup Company embarked on a new mission. This time everyone would be involved, from headquarters staff in Owings Mills to the fourth-floor oven area workers in the Dallas bakery. The new process goal, "Business Excellence," as we called it, was really an implementation of Class A ERP/MRP II.     

Economic impact of enhanced forest inventory information and merchandizing yards in the forest product industry supply chain

Forest products industry should maximize the value of timber harvested and associated products in order to be competitive in global markets. Enhanced forest inventories and merchandizing yards can help in maximizing value recovery in the forest products supply chain. This study develops an optimization model to analyze the economic impact of enhanced forest inventory information and merchandizing yard operations in the forest products supply chain. The application of the model is demonstrated by using a case study of a hypothetical forest industry in northwestern Ontario, which obtains four log assortment grades from the surrounding eight forest management units. The model analyzes five different scenarios with 0%, 25%, 50%, 75%, and 100% certainty of tree quality in forest inventory information. The results of the study show that with full certainty of tree quality information, it is possible to gain 49% in gross profit in comparison with a scenario with no certainty. The usefulness of enhanced forest inventory and merchandizing yard in the entire supply chain of forest products industry is recognized by maximizing total value of wood fiber (by allocating right log to the right product), reducing fluctuations in raw wood fiber supply, and minimizing inventory carrying costs and lost sales.     

The relationship between information technology capability,inventory efficiency,and shareholder wealth: A firm-level empirical analysis

Inventories represent an important strategic resource for firms, with implications for shareholder wealth. As such, firms expend considerable effort in managing their inventories efficiently. Among other factors, information technology (IT) capability can play an important role in enabling inventory efficiency and financial performance. However, insight into the chain-of-effects linking IT capability, inventory efficiency, and stock market returns and risk remains limited. In this paper, we provide a conceptual model outlining the relationships between these constructs. Next, we evaluate the model using secondary information on firms from multiple industries across the 10-year time period of 2000–2009. Our analysis confirms that firms’ IT capability plays a significant role in enhancing their inventory efficiency, which, in turn, is observed to increase stock market returns. Our results also reveal that firms’ IT capability directly reduces their stock market risk and enhances their stock market returns. Taken together, these findings, along with the conceptual model that we advance, have important research and managerial implications.     

Toward a better understanding of lead times in MRP systems

Lead times in MRP systems represent the planned amount of time allowed for orders to flow through the manufacturing system. Setting lead times is a major issue in the operation of MRP systems. There exists, however, very little documentation on just how lead times should be set.This study examines the effects lead times have on MRP-based manufacturing logistics systems. In particular, it examines the effects that lead times have on backlogs, order tardiness, and finished component inventories.A major finding is that changes to the level of planned lead times have both transient and steady state effects that may not necessarily operate in the same direction. A simple methodology is presented for setting the level of planned lead times when the criterion is finished component inventory.     

A cost evaluation method for dynamic line balancing

A procedure is presented for calculating stochastic costs, which include operator (labor) and inventory costs, associated with dynamic line balancing. Dynamic line balancing, unlike the traditional methods of assembly and production line balancing, assigns operators to one or more operations, where each operation has a predetermined processing time and is defined as a group of identical parallel stations. Operator costs and inventory costs are stochastic because they are functions of the assignment process employed in balancing the line, which may vary throughout the balancing period, and the required flow rate. Earlier studies focused on the calculation of the required number of stations and demonstrated why the initial and final inventories at the different operations are balanced.The cost minimization method developed in the article can be used to evaluate and compare the assignment of operators to stations for various assignment heuristics. Operator costs and inventory costs are the components of the cost function. The operator costs are based on the operations to which operators are assigned and are calculated for the entire work week regardless of whether an operator is given only a partial assignment which results in idle time. It is assumed that there is no variation in station speeds, no learning curve effect for operators' performance times, and no limit on the number of operators available for assignment. The costs associated with work-in-process inventories are computed on a “value added” basis. There is no charge for finished goods inventory after the last operation or raw material before the first operation.The conditions which must be examined before using the cost evaluation method are yield, input requirements, operator requirements, scheduling requirements and output requirements. Yield reflects the output of good units at any operation. The input requirement accounts for units discarded or in need of reworking. The operator requirements define the calculation of operator-hours per hour, set the minimum number of operators at an operation, and require that the work is completed. The scheduling requirements ensure that operators are either working or idle at all times, and that no operator is assigned to more than one operation at any time. The calculation of the output reflects the yield, station speed, and work assignments at the last operation on the line.An application of the cost evaluation method is discussed in the final section of the article. Using a simple heuristic to assign operators, the conditions for yield, inputs, operators, scheduling, and output are satisfied. The costs are then calculated for operators and inventories.In conclusion, the cost evaluation method for dynamic balancing enables a manager to compare the costs of assigning operators to work stations. Using this method to calculate the operator and inventory costs, a number of different heuristics for assigning operators in dynamic balancing can be evaluated and compared for various configurations of the production line. The least cost solution procedure then can be applied to a real manufacturing situation with similar characteristics.     

Too much inventory? How do you know?

How much inventory does a company need to support its business goals? Companies must consider what effect their inventory investment decisions have on the strategic direction of their business. Too often, a company's investment decisions are carried out not by the company's strategists, but by individuals who are unaware of the strategic direction of the business.     

如何在降低库存成本的同时取得满意客户服务质量

库存水平与顾客服务质量是两个效益悖反的指标,如何能以较合理的库存水平实现较高的顾客服务质量呢? 文中通过客户的 ABC 分析、产品的 ABC 分析以及产品-客户九象限图分析,探讨了解决这个问题的方法.     

基于Arena的随机需求和随机提前期二级库存仿真优化

讨论了由一个供应商和多个经销商组成的二级库存优化问题,该系统中每个经销商的客户需求以及供应商和经销商的订货提前期都是随机的,供应商和每个经销商都采用(T,s,S)混合策略进行库存管理。首先建立了该二级库存系统优化问题的数学模型,然后设计了解决该问题的仿真流程并基于仿真软件Arena建立了仿真模型,通过对由一个供应商和三个经销商所组成的二级库存系统的仿真实验表明,利用计算机仿真方法能够很好地解决随机需求和随机提前期的二级库存系统优化问题,其所得结果更贴近实际系统。     

Governance and control in distributed ledgers: Understanding the challenges facing blockchain technology in financial services

As blockchain platforms are becoming increasingly noticeable in financial services and beyond, questions arise regarding their suitability to compete with or replace existing payment systems and marketplaces and redesign the financial infrastructures of the future. Prominent among these concerns are issues around governance and control in distributed ledgers: How are distributed ledger technologies governed? Can blockchains address complex administration problems? What key issues of note for practitioners and academics have emerged thus far? In this paper we aim to review the existing governance practices of established or popular blockchain and decentralized autonomous organization (DAO) systems with a view to understanding how they hold up in times of crises. What questions are raised when they are compromised or faced consensus challenges in coordinating action especially around control and accountability? We use a translational process, generating focal insights about present concerns from the reference point of completed academic studies and extensive practitioner consultation. Rather than adopting a declarative approach attempting to provide all the answers, we draw insights from the IT platform governance literature to offer a critical perspective for asking the right questions around key governance issues in financial infrastructure such as decision rights, control mechanisms, and incentives.