A review of: “PROJECT MANAGEMENT IN MANUFACTURING AND HIGH TECHNOLOGY OPERATIONS” by Adedeji B. Badiru,John Wiley and Sons,Inc., New York, 1988, xxii + 319 pp., ISBN 0471-62892-1, List $44.95.

The conventional approach to considering working capital cash flows in capital budgeting is to omit them or include some ad hoc figures at the initiation and termination of the project. The authors argue for an endogenous system of estimating relevant working capital cash flows on a periodic basis. Otherwise, the present value of working capital cash flows is biased against the project's acceptance. Examples of calculating working capital cash flows as related to changes in annual sales are presented for three time patterns of sales and contrasted to the conventional method. An empirical study of the linear relationship of net working capital and sales revenue of 770 companies is reported, and an alternative cash flow model is offered thai includes working capilal cash flows.     

Selecting make-to-stock and postponement policies for different products in a chemical plant: A case study using discrete event simulation

We present a guideline for selecting the inventory management policy for a specialty chemical plant that produces products with limited shelf life, by producing multiple grades of bulk chemical and packaging them into a large variety of bottles. The policy for each product was selected based on a cost-benefit analysis, using the multiple objectives of maximizing the on time order fulfillment, minimizing the production (cleaning and shelf life expiration) and inventory costs. To generate realistic cost estimates, we developed a discrete event simulation model that included demand variability, planning and scheduling policies, and operational details. We evaluated three different policies: make-to-stock (MTS), postponement, and combined MTS/postponement. We also evaluated different storage media and optimized the number of storage units for products selected for postponement. A combined MTS/postponement policy, in which postponement is applied to products with low to medium demand and high expiration provided lowest costs without significantly impacting the customer on time order fulfillment. For all other products, a MTS policy is applied to maximize order fulfillment on time, reduce cleaning costs and to reduce number of storage units.     

A production rate control policy for stochastic repair and remanufacturing systems

We consider the control of a manufacturing system responding to planned demand at the end of the expected life of each individual piece of equipment and unplanned demand triggered by a major equipment failure. The difficulty of controlling this type of production system resides in the variable nature of the remanufacturing process. In practice, remanufacturing operations for planned demand can be executed at different rates, referring to different component replacement and repair strategies. We formulate this problem as a multi-level control problem and propose a suboptimal control policy. The proposed control policy is described by inventory thresholds triggering the use of different execution modes. Determination of the control policy parameters is based on parameter optimization of analytical cost expressions. A numerical example based on a real case is presented. Our analysis demonstrates that the use of the proposed control approach can lead to a significant reduction in the total average cost, as compared to current practices.     

A Model of the Asset Disposition Decision of the RTC

The purpose of this paper is to develop a model of the asset disposition decision for the Resolution Trust Corporation (RTC). In this paper, we focus on the primary goal of the RTC—to maximize the net present value of the cash flows generated through holding and selling the assets it acquires. A major decision it faces is whether to hold or sell assets. This decision ultimately depends on the RTC's discount rate versus that of the marginal buyer. A second question relates to the decision of which assets to sell first and which ones to delay sale. The model developed in this paper characterizes the asset disposition decision process of the RTC for different types of assets. We develop a set of optimal disposition rules based on the simple premise of a multi-period cash flow maximization. In addition, we test some of these rules by analyzing RTC disposition performance. Through this exercise, we hope to provide some guidance to the RTC in implementing its enormous task as well as to policy makers in charting the progress of the RTC. The main results of this analysis indicate that liquid assets and retail deposit franchises should be sold as quickly as possible. Illiquid assets that are performing and do not have high servicing costs are good candidates to finance through senior/subordinated securities or sale with seller financing by the RTC. Illiquid non-performing assets are good candidates for equity participation financing by the RTC. The sales proceeds obtained by the RTC will be increased if buyers have greater certainty with respect to expected cash flows and RTC sales policies.     

Single item inventory control under periodic review and a minimum order quantity

In this paper we study a periodic review single item single stage inventory system with stochastic demand. In each time period the system must order none or at least as much as a minimum order quantity Q_min. Since the optimal structure of an ordering policy with a minimum order quantity is complicated, we propose an easy-to-use policy, which we call (R, S, Q_min) policy. Assuming linear holding and backorder costs we determine the optimal numerical value of the level S using a Markov Chain approach. In addition, we derive simple news-vendor-type inequalities for near-optimal policy parameters, which can easily be implemented within spreadsheet applications. In a numerical study we compare our policy with others and test the performance of the approximation for three different demand distributions: Poisson, negative binomial, and a discretized version of the gamma distribution. Given the simplicity of the policy and its cost performance as well as the excellent performance of the approximation we advocate the application of the (R, S, Q_min) policy in practice.     

Focus, Transparency and Value: The REIT Evidence

We trace the effects of corporate focus by examining the relationships among focus, cash flows and firm value. In contrast to past studies that examine the effects of diversifying across SIC-code-defined industries, we show that diversification, even within a single industry, reduces value. Our evidence, drawn from a panel of real estate investment trusts, indicates that this reduction is not due to poor managerial performance. Project-level cash flows are actually higher for less focused firms. However, these gains are offset by higher management, administrative and interest expenses. Thus, the corporate cash flows available to shareholders are not related to focus. Finally, we provide empirical evidence that links the effect of focus on value to informational asymmetries which cause the equity of diversified firms to be less liquid. We attribute some of the effect of focus on the cost of both debt and equity to informational asymmetries or transparency costs.     

A continuous model for supply planning of assembly systems with stochastic component procurement times

This paper studies a customized product assembly scenario where some components cannot be stocked due to high component cost and risk. We consider the case where these key components are ordered after a demand has been registered with a promised delivery date. Component lead-times are stochastic and associated distribution function is known in advance. The objective is to determine the ordering time for each component such as to minimize the sum of expected holding and backlogging costs. An approach to solve this problem is proposed and the algorithm is tested on a randomly generated data set.     

Inventory control in a two-echelon dual-channel supply chain with setup of production and delivery

This paper considers a two-echelon dual-channel supply chain model with setup of production and delivery and develops a new inventory control policy for the supply chain. Previously, a two-echelon supply chain model without setup of production and delivery is considered and a one-for-one inventory control policy is applied to the supply chain. In the inventory control policy, production is stopped when the warehouse inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. Moreover, delivery to the retailer is stopped when the store inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. The total cost that consists of inventory holding costs and lost sales cost is considered, and setup costs are not considered in the total cost. Once setup costs are introduced, the one-for-one inventory control policy is no longer appropriate. Then, this paper develops a new control policy for the two-echelon dual-channel supply chain with setup of production and delivery. As performance measure, the total cost that consists of inventory holding costs, lost sales cost, and production and delivery setup costs is considered, and the total cost calculated on the basis of Markov analysis demonstrates the effectiveness of the proposed control policy.     

Production lot sizing with a secondary outsourcing facility

An extended economic production quantity (EPQ) model under stochastic demand is investigated in this paper, where a fixed lot sizing policy is implemented to reduce the complexity of production planning and inventory control, and outsourcing with a secondary facility is used to supplement the lot sizing policy and to cope with the random demand. The considered cost includes: setup cost for the batch production, inventory carrying cost, backorder cost when the demand cannot be met immediately during the production period, and outsourcing cost when the total demand is greater than the lot size in one replenishment cycle. Under some mild conditions, the expected cost per unit time can be shown to be convex. Extensive computational tests have illustrated that the average cost reduction of the proposed model is significant when compared with that of the classical lot sizing policy. Significant cost savings can be achieved by deploying the production lot sizing policy with an outsourcing strategy when the mean demand rate is high.     

Efficient location of industrial activity cells in a global supply chain

Inefficient locations for production, distribution and reverse logistics plants will result in excess costs no matter how well material requirements planning (MRP), inventory control, distribution and information sharing decisions are optimized. In this paper we study ways in which aspect of activity cell location decisions can be analyzed within an extended MRP model. This model has previously been extended by including distribution and reverse logistics components in a compact form, presented in Grubbström et al. (2007). Our aim is to demonstrate the basic differences between an approach to location problems with MRP “under the same roof” as the global supply chain, in which transportation time delays and direct transportation costs have substantial influence. We discuss possibilities of how to present location aspects in the supply chain model obtained from combining input–output analysis and Laplace transforms in four sub-systems, namely manufacturing, distribution, consumption and reverse logistics, and show how the transportation costs and lead time influenced by the location of all these activities affect the resulting net present value (NPV). Our aim is to build a model supporting decisions concerning the structure of a supply chain as an alternative to a mixed integer programming formulation. The model developed is based on the use of continuous functions describing spatial distributions of cost and customer demand. Continuous functions are embedded in the MRP extension previously introduced in Grubbström et al. (2007).Location decisions influence (i) production costs, because timing influences the cost of activities involved in creating a product, cf. (Grubbström and Bogataj, submitted for publication), and (ii) logistics costs, which refer to the procurement and physical transmission of materials through the supply chain. In this current paper we wish to combine both of these aspects into a comprehensive model, where we show the interaction between the “space of flows” and the “space of places” as Giovanni Arrighi distinguishes one from the other in his book The Long Twentieth Century.     

Batch quantities when forecasts are improving

This paper considers the choice of initial batch quantities when demand forecasts are improving. We assume that the standard deviation of the demand per period is decreasing exponentially and approaching a long-run value. A discrete time stochastic single-level inventory model is considered. There are traditional holding and backorder costs as well as an ordering cost. The ordering periods must be determined in advance, and we wish to determine a suitable schedule.     

Multiproduct Price Regulation Under Asymmetric Information

We discuss the regulation of a multiproduct monopolist when the firm has private information about cost or demand conditions. The regulator offers the firm a set of prices from which to choose. When there is private information only about costs, the firm should always have a degree of discretion over its pricing policy. When uncertainty concerns demand, whether discretion is desirable depends on how demand elasticities vary with the scale of demands. If a positive demand shock is associated with a reduction in the market elasticity, discretion is good for overall welfare; otherwise it is not.     

On delineating supply chain cash flow under collectionrisk

The credit terms for accounts receivable (AR) offered by sellers to buyers not only create a time lag between supply chain physical flow and cash flow, but also increase the collection risk contributed by late collection and default. Previous studies describing the relationship between the two major supply chain flows did not consider the collection risk, which poses a serious challenge to companies with limited cash resources when seeking growth opportunities in sales. This study first delineates the relationship between the two flows during a growth period without imposing any constraints. A stochastic optimization model is then developed to observe the managerial implications of cash flow risk under tight cash constraints.     

ALTERNATIVE MODELS FOR FINDING CUMULATIVE PAID CAPITAL AND REMAINING BALANCE FOR A UNIFORM SERIES OF CASH FLOWS

The purpose of this paper is to propose models for finding the cumulative amount of paid capital up to a certain point in time for a discrete uniform series of cash flows, and also the unpaid capital amount of a similar séries of cash flows. An exponential model for finding the present worth for a séries of cash flows that is increasing exponentially is used to find the sum of paid capital. The second model that is used for finding the unpaid capital is developed based on the first model. The major advantages of the first model over the existing models is that it provides a direct tool for finding the cumulative amount of paid capital or unrecovered investment. The proposed models are easy to use since they are independent of finding the amount of the cash flow A. The cumulative paid interest up to a certain point in time can be found by subtracting the total repaid capital from the amount of total paid money up to that point.     

Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems

This paper presents a method to find the optimal production, repair/replacement and preventive maintenance policies for a degraded manufacturing system. The system is subject to random machine failures and repairs. The status of the system is deemed to degrade with repair activities. When a failure occurs, the machine is either repaired or replaced, and a replacement action renews the machine, while a repair action brings it to a degraded operational state, with the next repair time increasing as the number of repairs increases as well. A preventive maintenance action is considered in order to improve the reliability of the machine, thereby reducing the amount of disruptions caused by machine failures. The decision variables are the production rate, the preventive maintenance rate and the repair/replacement switching policy upon machine failure. The objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, preventive maintenance, inventory holding and backlog costs over an infinite planning horizon. The proposed model is based on a semi-Markov decision process, and the stochastic dynamic programming method is used to obtain the optimality conditions. A numerical example is given to illustrate the proposed model, and a sensitivity analysis is considered in order to confirm the structure of the control policy and to illustrate the usefulness of the proposed approach.     

An integrated production–distribution model for the dynamic location and allocation problem with safety stock optimization

The design and management of a multi-stage production–distribution system is one of the most critical problems in logistics and in facility management. Companies need to be able to evaluate and design different configurations for their logistic networks as quickly as possible. This means coordinating the entire supply chain effectively in order to minimize costs and simultaneously optimize facilities location, the allocation of customer demand to production/distribution centers, the inbound and outbound transportation activities, the product flows between production and/or warehousing facilities, the reverse logistics activities, etc.Full optimization of supply chain is achieved by integrating strategic, tactical, and operational decision-making in terms of the design, management, and control of activities. The cost-based and mixed-integer programming model presented in this study has been developed to support management in making the following decisions: the number of facilities (e.g. warehousing systems, distribution centers), the choice of their locations and the assignment of customer demand to them, and also incorporate tactical decisions regarding inventory control, production rates, and service-level determination in a stochastic environment. This paper presents an original model for the dynamic location–allocation problem with control of customer service level and safety stock optimization. An experimental analysis identifies the most critical factors affecting the logistics cost, and to finish, an industrial application is illustrated demonstrating the effectiveness of the proposed optimization approach.     

Incorporating uncertainty into a supplier selection problem

Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.     

Probability Distribution of the Project Payback Period Using the Equivalent Cash Flow Decomposition

For stochastic cash flows, probabilistic approaches to determine a complete distribution of payback period are very limited. The payback analysis based on the net present value (NPV) has several advantages. For annual cash flows, however, the NPV-based method does not provide a complete payback distribution. This article proposes a new technique, the equivalent cash flow decomposition (ECFD), which converts an annual cash flow into an equivalent subannual cash flow at a desired level of precision. The ECFD technique can be used in conjunction with any probabilistic cash flow technique. This article demonstrates that the ECFD technique overcomes the discontinuity limitation of the conventional NPV-based payback period method and generates a complete distribution of the payback period of annual cash flows. Examples indicate that the proposed method is robust with the accuracy comparable to Monte Carlo simulation.     

Optimal economic ordering policy with deteriorating items under different supplier trade credits for finite horizon case

This paper develops and solves a general finite horizon trade credit economic ordering policy for an inventory model with deteriorating items under inflation and time value of money when shortages are not allowed. The time horizon is divided into different cycles each of which has its own demand rate and its own trade credit period offered from the supplier to his retailer so that the retailer should pay his supplier before or after the end of the permissible trade credit of that cycle. Up to the end of the trade credit of a cycle, the retailer is free of charge, but he is charged on an interest for those items not being sold before this end. The retailer can also earn the interest of the money from the generated sales revenue in any cycle by depositing such revenue into an interest bearing account. The objective of the retailer is then to minimize his net total relevant costs. A closed form of this net total cost is derived and the resulting model is solved. Then rigorous mathematical methods are used to show that, under some seemingly possible conditions, there exist a unique vector of the relevant decision variables that solve the underlying inventory system. A numerical example which shows the applicability of the theoretical results is given.     

CALCULATION OF THE UNIFORM CASH FLOW WHICH IS EQUIVALENT TO A CUBICALLY VARYING CASH FLOW

Finding the uniform annual cash flow which is equivalent to a given irregular cash flow is an elementary but frequently arduous calculation. A closed form result is developed from which the uniform annual cash flow may be calculated provided that the actual cash flow varies with time according to a polynomial whose degree does not exceed three. An example which concerns finding the equivalent annual energy dissipation cost in electric system distribution transformers is included.