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.     

Economic life replacement under improving technology

The economic life (EL) method of asset replacement is analyzed under improving technology that impacts the maintenance cost, new asset cost, and salvage value. In particular, we prove that the asset EL is constant when all these costs decrease with the same rate. If these costs decrease geometrically, then the EL method with a corrected capital recovery factor calculates the optimal asset lifetime over the infinite horizon for arbitrary age-dependent deterioration and salvage value. In a general case, the EL method delivers an optimal replacement decision when the relative rate of technological change is less than 1%. For larger rates, we recommend to minimize the annual cost over two future replacement cycles, which was earlier proposed and implemented by Christer and Scarf, Journal of the Operational Research Society 45, 1994.     

Integrating noncyclical preventive maintenance scheduling and production planning for a single machine

This paper deals with the problem of integrating noncyclical preventive maintenance and tactical production planning for a single machine. We are given a set of products that must be produced in lots during a specified finite planning horizon. The maintenance policy suggests possible preventive replacements at the beginning of each production planning period, and minimal repair at machine failure. The proposed model determines simultaneously the optimal production plan and the instants of preventive maintenance actions. The objective is to minimize the sum of preventive and corrective maintenance costs, setup costs, holding costs, backorder costs and production costs, while satisfying the demand for all products over the entire horizon. The problem is solved by comparing the results of several multi-product capacitated lot-sizing problems. The value of the integration and that of using noncyclical preventive maintenance when the demand varies from one period to another are illustrated through a numerical example and validated by a design of experiment. The later has shown that the integration of maintenance and production planning can reduce the total maintenance and production cost and the removal of periodicity constraint is directly affected by the demand fluctuation and can also reduce the total maintenance and production cost.     

Optimizing capital investments under technological change and deterioration: A case study on MRI machine replacement

ABSTRACT

We study the multiple style and type parallel asset replacement problem (MST-PRES), which determines an optimal policy for keeping or replacing a group of assets that operate in parallel under a limited budget. Operating assets generally suffer from deterioration, which results in high operation and maintenance (O&M) cost and decreased salvage value, and technological improvements make it possible for new assets to operate more efficiently at a lower cost. In order to address these issues, we formulate a multi-objective mixed-integer programming (MIP) model that minimizes fixed and variable costs of purchasing new assets, O&M cost, inventory cost, and penalty cost for unmet demand minus salvage values, while considering technological advances and deterioration as a gain and loss in capacity, respectively. We apply our model to a case study involving two different styles of assets: a full-body magnetic resonance imaging (MRI) machine and a smaller extremity magnetic resonance imaging (eMRI) machine. Each has two types: high-field and low-field. We perform computational experiments and analyses using key model parameters and illustrate optimal replacement strategies considering the impact of technological advances and deterioration. Results show that the proposed MIP model provides valuable insights and strategies for companies, decision makers, and government entities on the capital asset management.     

A Solution Methodology for Probabilistic Capital Budgeting Problems Using Complex Utility Functions

Historically, the study of economic equipment replacement is primarily limited to that of a single machine or a single machining system. The replacement situation whereby machines under consideration are part of a large integrated system has received little attention. This paper proposes a framework, for the analysis of multiple-machine replacement within an integrated system context. The major difficulty of analyzing such a problem lies in the interactive nature of an integrated system; that is, how should the effects to the entire system be assessed as a result of alterations to one or more of its components. The emphasis of this work is on the issues regarding multiple machine replacement. A single-period model is utilized in order to simplify the presentation. A comprehensive example is also provided for illustration.     

Parallel machine replacement under horizon uncertainty

Construction projects usually get delayed for several time periods. When the planning horizon of a project is extended, projections for purchase and salvage of machinery within the planning horizon become inaccurate and less beneficial and often lead to unexpected costs. In this article, we formulate a parallel machine replacement (PMR) problem as a two-stage stochastic program with an uncertain planning horizon. We consider renting as an alternative to purchasing and maintaining the machinery. We show the application of the model through a case study in construction projects. Through numerical analysis, we derive managerial implications and show the value of the stochastic model.     

UNIT COST MODEL FOR THE TIMING OF CAPACITY CHANGE

The optimal capacity expansion time is an essential problem especially in capital intensive industries, and capacity expansion decisions have a great influence on the firm's operations and profitability. It can be said that the timing question is quite complex, and in practice the experience and intuition of the decision-makers have a central role. We can, however, use theoretical models to explain many essential relations and deepen our understanding of the nature of capacity changes. The actual object of this study is to develop a unit cost minimization model for the timing of capacity expansion. The model is based on the costs and capacities of old and new machines, and the arithmetic growth rate of demand. The analytical solution of the model shows that the relative timing of expansion can be presented with cost advantage and capacity change ratios. It is also shown that the analogical model can be used for capacity replacement and cutting. Finally, the model is extended, and it is shown that such timing can be found which minimizes unit costs and maximizes the profit of the planning period. The original contribution of the study is to suggest an alternative evaluation method for the timing of capacity changes and to present an analytical solution to the formulated problem. The presented model is applied to an illustrative case where capacity addition is planned either through expansion or replacement. The suggestion of the model to the case company is that it is preferable to replace the old machine with a bigger one rather than to acquire a totally new machine.     

Fuzzy Present Value Analysis Model For Evaluating Information System Projects

In this article, the economic evaluation of information system projects using present value is analyzed based on triangular fuzzy numbers. Information system projects usually have numerous uncertainties and several conditions of risk that make their economic evaluation a challenging task. Each year, several information system projects are cancelled before completion as a result of budget overruns at a cost of several billions of dollars to industry. Although engineering economic analysis offers tools and techniques for evaluating risky projects, the tools are not enough to place information system projects on a safe budget/selection track. There is a need for an integrative economic analysis model that will account for the uncertainties in estimating project costs, benefits, and useful lives of uncertain and risky projects. In this study, we propose an approximate method of computing project present value using the concept of fuzzy modeling with special reference to information system projects. This proposed model has the potential of enhancing the project selection process by capturing a better economic picture of the project alternatives. The proposed methodology can also be used for other real-life projects with high degree of uncertainty and risk.     

AFTER-TAX ECONOMIC REPLACEMENT ANALYSIS

This paper examines after-tax serial replacement analysis under current United States tax law. The law explicitly defines the difference between an asset disposal (retirement) and a like-for-like exchange (replacement). A gain or loss is only realized when an asset is retired while a replacement leads to the transfer of any residual book value balance to the acquired asset. This transferal greatly complicates analysis and leads to non-stationary solutions, even with time invariant costs. We analyze the effect of this movement in book value for assets on replacement decisions. Furthermore, a dynamic programming formulation is presented with a state space defined by asset age and initial book value, as current replacement models cannot correctly capture the after-tax cash flow implications of this balance transfer. The new model is compared to traditional after-tax replacement models which assume that a gain or loss is realized at each asset sale over the horizon. Examples illustrate that this assumption can lead to widely different solutions, especially in the cases where gains or losses from asset sales are large.     

Measuring maintenance performance – in search for a maintenance productivity index

A partial maintenance productivity goal is that the firm should seek to maximize its maintenance productivity in economic terms, and should aim at producing any level of output which is decided upon at minimum maintenance cost with respect to the production system's state. The state of objects or production systems is such a property, i.e., a multidimensional property. In this paper we amalgamate these various dimensions into a single measure of the property involved. All things considered it would seem, that in measuring partial maintenance productivity, minimization of maintenance costs is incorporated as a subgoal, based on the maintenance inputs called for an “optimal budget”. These imputed maintenance costs do not have to be calculated separately, but emerge as a by-product of finding a high productivity index. In our partial productivity model, the output prices of the produced products and input prices (maintenance costs) will change over time. Expected changes in the prices of outputs and of current inputs would be built into the model.     

基于失效风险的建筑物预防维修成本模型优化

建筑物预防性维修成本的最优控制问题,是企业现代化经营管理的一个重要组成部分,直接影响到企业的经济效益。针对承受重复荷载作用的建筑构件,失效概率随服役时间增加而增大的实际情况,提出了失效风险的概念。采用役龄回退因子描述了维修后失效概率降低的程度,在此基础上推算出满足可靠度约束条件,适用于特定时间段非等间隔检测期序列,计算出单位维修周期内的检测次数。通过对维修成本函数的分析,建立了基于等失效风险状态的维修成本优化模型。为房屋物业管理部门进行建筑物的维修和更换决策提供参考依据。     

煤炭资源开采价值的系统动力学分析

运用系统动力学的方法,将煤炭资源开采价值作为一个系统整体,对自然、勘探、生态和代际这4部分价值进行整合,得出煤炭开采价值系统应该由经济价值子系统、生态价值子系统和代际价值子系统构成,分析了每个子系统的因素变量及构建方程组模型。     

Economic and welfare impacts of commercializing a herbicide-tolerant,biotech wheat

A transgenic variety of spring wheat was proposed for deregulation in North America in 2002. (More recently, the developer shelved this plan.) In this paper, a quantitative model is used to analyze the possible economic impact of commercializing a crop for which there may be sizable consumer resistance. At issue is whether, and under what conditions, the economic benefits from biotech wheat could be outweighed by economic costs. The analysis also addresses the distribution of costs and benefits among stakeholders: producers, consumers, and US taxpayers. Specific attention is given to the impacts on consumers in non-biotech and biotech market segments, and those in the United States and foreign countries. Under base-case assumptions, the analysis suggests that commercialization of biotech wheat could lead to a small net loss of total economic welfare. Results depend critically on several model parameters: the rate of biotech adoption; unit cost savings for biotech producers; the share of the non-biotech market segment; and extra costs associated with a ‘dual marketing system’ for wheat.     

天明机械：又一匹黑马？

2011年8月16日,天明机械董事长卢明立这一天可谓过得忐忑而又焦急。当自主研制的“大功率变频技术刮板输送机成套设备”和“全路面大口径救援钻机”两项高端重大煤机装备分别在中国神华神东煤炭集团哈拉沟煤矿和山西保德煤矿试车成功的消息传来,他终于松了一口气：这距离自己的梦想又近了一步。     

电气设备的精细化维修

煤炭行业整体良性竞争有序进行,作为煤矿设备维修企业,应树立危机意识,开展精细化维修,努力降低维修成本,提升维修质量,才能在竞争中掌握主动权。     

Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems

In this paper, an integrated mathematical model of the multi-period cell formation and production planning in a dynamic cellular manufacturing system (DCMS) is proposed with the aim of minimizing machine, inter/intra-cell movement, reconfiguration, partial subcontracting, and inventory carrying costs. This paper puts emphasis on the effect of the trade-off between production and outsourcing costs on the re-configuration of the cells in cellular manufacturing systems (CMSs) under a dynamic environment, in which the product mix is different from a period to another resulting in the operational dynamism in the cells. The proposed model is verified by a number of numerical examples and related sensitivity analysis.     

A Review of: “MODELING THE SUPPLY CHAIN” BY JEREMY R SHAPIRO Duxbury Press,Pacific Grove,California, 2001, xv + 586 pp. ISBN 0-534-37363-1. List: $71.95.

In this paper, we measure economic profit in an inflationary environment. Inflation adjusted economic profit requires two principal alterations to Economic Value Added (EVA[rgrave]). First, because inflation increases the replacement cost of non-current assets above book value, one must make a downward adjustment to EVA[rgrave] to correctly measure economic profit. Second, we add a term to EVA[rgrave] to represent a manager's ability to increase product price as costs increase. This adjustment is positive because this ability adds value to a firm. When a firm's assets are largely current, the first adjustment is not necessary, and therefore, the second dominates. In this case, EVA[rgrave] underestimates economic profit. Economic profit remains positive when a firm's rate of return on invested capital, after tax and after depreciation, is less than the weighted average cost of capital by as much as the rate of inflation. Even when inflation is modest, unadjusted EVA[rgrave] has the potential to seriously misrepresent the operating performance of a firm.     

Applying possibilistic linear programming to aggregate production planning

This work presents a novel interactive possibilistic linear programming (PLP) approach for solving the multi-product aggregate production planning (APP) problem with imprecise forecast demand, related operating costs, and capacity. The proposed approach attempts to minimize total costs with reference to inventory levels, labor levels, overtime, subcontracting and backordering levels, and labor, machine and warehouse capacity. The proposed approach uses the strategy of simultaneously minimizing the most possible value of the imprecise total costs, maximizing the possibility of obtaining lower total costs, and minimizing the risk of obtaining higher total costs. An industrial case demonstrates the feasibility of applying the proposed approach to real APP decision problems. Consequently, the proposed PLP approach yields an efficient APP compromise solution and overall degree of decision maker (DM) satisfaction with determined goal values. Particularly, several significant management implications and characteristics of the proposed PLP approach that distinguish it from the other APP decision models are presented.     

Reducing the level of switching costs in mobile communications: The case of Mobile Number Portability

Switching costs are one of the most important economic forces that affect market competition in mobile communications. Both theoretical and empirical studies have shown that switching costs reduce market competition leading to higher prices, lower product and service quality, and lower customer welfare. Given their negative consequences, national regulatory authorities have designed policies aimed at reducing switching costs and fostering competition. One of the most important of these, in the mobile communications industry, is mobile number portability (MNP). The aim of this paper is to investigate the effect of MNP on switching costs in mobile phone services. First, a hierarchical Bayes model is proposed to measure switching costs at the customer level and to investigate the impact of MNP on them. Second, this study examines the drivers of MNP adoption by customers using a binary logit specification. The results reveal that this regulatory policy has significantly reduced the cost of switching and that MNP adoption partially depends on customer-related variables.     

A review of “ Edited by Richard H. Bernhard,North Carolina State University ” THE BUSINESS OF RISK by Peter G. Moore,Cambridge University Press,New York, 1984, x + 244 pages,ISBN 0521-24174 X ( hard cover), List $ 44.50; ISBN 0521-28497 X (paperback), List $ 16.95

Four replacement scenarios were analyzed for a vehicle fleet designed to haul sensitive packages at two different customer locations. In addition to completing an economic replacement analysis study, each option was analyzed according to availability requirements and other intangible attributes. Finally, a thorough sensitivity analysis was performed to examine the impact of reliability assumptions on both life cycle costs and the expected economic life of each option. Once all factors were analyzed, each critical input was graded and scored, leading to the final recommendation to replace the current equipment with a new technology.