Finite Life Cycle Research Articles

Discussion of signature‐based models of preventive maintenance

Discussion of signature‐based models of preventive maintenance

An infinite life cycle assessment model to re-evaluate resource efficiency and environmental impacts of circular economy systems

Challenges exist in life cycle assessment (LCA) to evaluate resource efficiency and environmental impacts of circular economy systems. Rules attributing recycling benefits/burdens are inconsistent, causing system boundary ambiguity. Besides, LCAs covering one or several life cycles fail to capture the complete resource path, which leads to unfair assessment results for the primary life cycle. This paper develops an infinite life cycle assessment model, which integrates LCA, substance flow analysis, and a state transition matrix into an infinite-life-cycle framework. On this basis, algorithms are formulated to quantify the resource efficiency and attribute environmental impacts following the principle of whole first, then allocation. Our model is demonstrated by a case study of lead-acid batteries. Results show that the resource efficiency of lead in the infinite life cycle assessment model is at least 118.75% higher than that of primary lead derived from the typical finite life cycle models. Measured by the index of environmental toxicity potential, environmental impacts are transferred from the primary product life cycle to recycled product life cycles, with the range fluctuating from 66.26% to 68.12%. Our model enables scholars to make more reasonable assessments for circular economy systems based on traditional LCA adjustment. From the infinite-life-cycle perspective, sustainable production policies should focus on increasing the recycling rate of waste products rather than limiting the exploitation of natural resources.

New-Product Diffusion in Closed-Loop Supply Chains

Problem definition: We study the sales planning problem of a producer who sells new and remanufactured versions of a durable good over a finite life cycle. We investigate whether slowing down product diffusion by choosing to partially satisfy demand might be profitable for the producer. Academic/practical relevance: We provide new insights into sales management in closed-loop supply chains by uncovering the role key market characteristics play in profitability of partial demand fulfillment as well as its optimal timing and magnitude. Methodology: We develop a dynamic model in which demand arrives as a slightly modified Bass diffusion process, and end-of-use products required for remanufacturing are constrained by earlier sales. Results: The optimal sales plan involves partial demand fulfillment when the product diffusion rate is high, the profit margin from remanufacturing is large, and the remanufactured item is in limited demand. Partial demand fulfillment extends to earlier stages of the life cycle as the diffusion rate grows, the demand for remanufactured items shrinks, or the number of consumers who return their end-of-use items increases. It is profitable to backlog more customers when the word-of-mouth effect dominates the diffusion process or when the demand for remanufactured items is lower. Finally, the benefit of delaying product diffusion tends to increase with diffusion rate. Managerial implications: Our findings suggest that deliberately backlogging some customers may be an effective lever (in the absence of flexibility to dynamically adjust prices) for durable-good producers in fast-clockspeed industries to improve their total profits from the jointly optimized sales of new and remanufactured items.

A stage-dependent economic order quantity model for high-tech products with a finite life cycle

Due to the rapid development of technology, producers’ marketing strategies and changing the taste of customers, the life cycle of high-tech products has become shorter over time. In this paper, we develop a new stage-dependent economic order quantity (EOQ) model for lot sizing high-tech products that consider the demand variations over the life cycle. First, we identify three stages: (I) initial increase, (II) steady state and (III) final decrease, during the life cycle, and then we generate a three-piece linear approximation. Afterwards, we determine the optimal ordering policy of each stage such that the total inventory costs, including ordering and holding costs, are minimised. The findings indicate that the optimal order quantity in each period of the first stage (initial increase) is an even multiple of the order quantity in the first period. Under the assumption of constant demand rate in the second stage (steady state), the optimal order quantities in every period of this stage are the same. In addition, the optimal order quantity in each period of the third stage (final decrease) is less than that of the previous period. Finally, we solve a numerical example and perform a sensitivity analysis to illustrate the efficiency of the developed model.

Managing high-end ex-demonstration product returns

Some manufacturers demonstrate their products so that customers can gain experience before making a purchase. We present a novel application of a closed-loop supply chain where product returns from demonstrations of high-end IT equipment are substantial and the major delay in the system is due to the long demonstration time at the client sites. In addition, the product lifecycle is short and the value erodes rapidly over time, with steep drops in the resale revenue when new product generations are introduced. We present a finite lifecycle model that captures the key trade-offs in this environment, that is, either to reuse a collected ex-demo product for a next demonstration or to salvage its residual value in the secondary market and use a new product to satisfy the next demo request. We derive two cost/revenue signals that enable us to distinguish between fast and slow value erosion. We show that the fast/slow erosion decision is dynamic and depends on the rate of value erosion and the length of the demonstration time. We analyze the optimal demo pool strategies and show that in the case of fast erosion it may be better to postpone reuse activities until later in the lifecycle. We illustrate our model using empirical data from a large IT manufacturer and formulate several guidelines so as to better manage high value ex-demonstration product returns.

Lentiviral-Mediated shRNA Approaches: Applications in Cellular Differentiation and Autophagy.

Acute myeloid leukemia (AML) is characterized by the accumulation of immature white blood cell precursors in the bone marrow and peripheral circulation. In essence, leukemic cells fail to differentiate and are stalled at a particular step of hematopoietic maturation and are unable to complete their development into functional blood cells with a finite life cycle. They are thus said to possess a "differentiation block." Pharmacological override of this block is one attractive avenue of therapy, termed "differentiation therapy." The most successful example of this therapeutic strategy is the use of the physiologic retinoid all-trans-retinoic acid (ATRA) in the treatment of acute promyelocytic leukemia (APL). In this chapter, we will outline the methods used to characterize the mechanisms mobilized by retinoid signaling and will use the activation of a key regulator of autophagy, ATG7, as an example of the functional characterization of a retinoid regulated gene during differentiation. We will discuss how lentiviral delivery of shRNA constructs into cultured APL cells, such as NB4, can be used to functionally deplete key proteins. We will also describe how the effect of protein knockdown on ATRA-induced differentiation and autophagy can be assessed using quantitative PCR, Western blotting, and flow cytometry.

Assessment of the maintenance cost and analysis of availability measures in a finite life cycle for a system subject to competing failures

This paper deals with the assessment of the maintenance cost and the performance of a system under a finite planning horizon. The system is subject to two dependent causes of failure: internal degradation and sudden shocks. We assume that internal degradation follows a gamma process. When the deterioration level of the degradation process exceeds a threshold, a degradation failure occurs. Sudden shocks arrive at the system following a doubly stochastic Poisson process (DSPP). A sudden shock provokes the system failure. A condition-based maintenance (CBM) with periodic inspection times is implemented. Recursive methods combining numerical integration and Monte Carlo simulation are developed to evaluate the expected cost rate and its standard deviation. Also, recursive methods to calculate the reliability, the availability and the interval reliability of the system are given. Numerical examples are provided to illustrate the analytical results.

Software code flexibility profitability in light of technology life cycle

This paper analyzes the crucial flexibility management facets of software code development, namely, reusable software code. Maximizing a reusable code level represents a normative engineering rationale of the highest adaptability for the code, which utterly generates future costs savings. However, given the finite life cycle of the technology, the optimal managerial financial-economic decision might not coincide with the pure engineering facet, which evolves from the reusable code’s tradeoff between initial investment and future project savings. The cost–benefit considerations of optimal software flexibility are converted into technology-based cyclical discounted cash flows. The study provides software development project managers with a powerful decision support tool to assess pro-engineering profitability of flexible code development. Numerical simulations on a set of literature-derived parameter values justify a pure reusable strategy in only 4.2% of the cases. Finally, the model illustrates the opportunity to adapt and optimize organizational structure as a substitute for software flexibility strategy.

Analysis of the reliability and the maintenance cost for finite life cycle systems subject to degradation and shocks

• Analysis of the maintenance cost in a degradation-threshold-shock model for finite life cycle systems. • Modeling of compound availability measures for a degradation-threshold shock model. • Development of recursive methods to assess the maintenance cost and the availability measures. • Implementation of the recursive method to solve a practical case. This paper deals with a deteriorating system subject to two different causes of failure: internal continuous degradation and sudden shocks. The degradation process is modelled using a gamma process. It is assumed that the system fails when the deterioration level reaches a critical threshold. Furthermore, sudden shocks arrive at the system at random times following a non-homogeneous Poisson process. When a sudden shock takes place, the system fails. To control the system reliability, a condition-based maintenance is applied. Under this maintenance policy, availability measures of the system are obtained. It is shown that these measures fulfil Markov renewal equations. A recursive method is developed to compute these measures. Furthermore, the maintenance cost of this system is analysed. Traditionally, the maintenance cost is analysed assuming an infinite time span. However, most systems have a finite life cycle and the application of the asymptotic approach is questionable. In this paper, the maintenance cost is analysed considering a finite life cycle. A recursive method, which combines numerical integration and Monte Carlo simulation, is developed to obtain the expected cost rate in the finite life cycle and its associated standard deviation.

A stochastic production inventory model for deteriorating items with products’ finite life-cycle

The article deals with a production inventory system for deteriorating items where the production rate of the system is a random variable within a finite range and the unit production cost depends on production lotsize as well as the rate of production. In the model, the maximum life-cycle of the products is finite and all the products are totally expired at the end of the life-time of the product. Shortages are allowed and partially backlogged. The backlogging rate is depended on length of the waiting time for the next replenishment. The main objective is to find out the optimal production lot-size such that the average expected cost per unit time of the inventory system is minimum. The different cases according to the value of the product’s life-time, production run-time and cycle length of the system are discussed analytically and numerically. A numerical example and its sensitivity analysis along with its managerial insights are presented to illustrate the behavior of the proposed production-inventory model.

Replacement policies for age and working numbers with random life cycle

ABSTRACTIt has been modeled for several replacement policies in literatures that the whole life cycle or operating interval of an operating unit should be finite rather than infinite as is done with the traditional method. However, it is more natural to consider the case in which the finite life cycle is a fluctuated parameter that could be used to estimate replacement times, which will be taken up in this article. For this, we first formulate a general model in which the unit is replaced at random age U, random time Y for the first working number, random life cycle S, or at failure X, whichever occurs first. The following models included in the general model, such that replacement done at age T when variable U is a degenerate distribution, and replacement done at working numbers N summed by number N of variable Y, are optimized. We obtain the total expected cost until replacement and the expected replacement cost rate for each model. Optimal age T, working number N, and a pair of (T, N) are discussed analytically and computed numerically.

Joint optimal maintenance and inspection for a k-out-of-n system

In the present paper, a k-out-of-n system with hidden failures is considered. The system is inspected periodically over a finite lifecycle. Hidden component failures accumulate and cause system failure when their cumulative number reaches n − k + 1. Every system failure presents an additional opportunity for inspection and, therefore, is called “opportunistic”. The objective is to find the optimal periodic inspection policy and the optimal maintenance action at each inspection for the entire system. Three types of maintenance are considered: minimal repair, preventive replacement and corrective replacement. In view of the failures being hidden, the maintenance decision is based on the optimal number of minimal repairs before replacement (of either type). Due to the unavailability of a closed-form solution, joint optimisation of inspection and maintenance policies resulting in the minimum total expected cost is performed using exhaustive search and genetic algorithm (GA), both with integer inspection period constraint, and a GA implementation with quasi-continuous inspection period. Although both exhaustive search and GA with integer inspection period provide identical results, the genetic algorithm presents a more efficient procedure and requires less computational time, which becomes more noticeable with increasing complexity of the problem, as in the case of GA with quasi-continuous inspection period. Based on the simulation results, some insights are made regarding the system’s operation and cost optimisation. Expressions are derived for the expected number of system failures in terms of the cost ratio and component failure intensity. In addition, a criterion is derived for establishing acceptable level of expected system failures over the system’s lifecycle. This can be useful when designing the system or analysing its performance.

FMEA에서 주기적인 고장원인 감시하의 기대손실모형에 대한 소고

. (2013) studied the optimal monitoring interval of systems with finite life cycle. It is assumed that there are several failure modes from several failure causes and the occurrence of causes follows a homogeneous Poisson process. The total expected cost is used as an optimization criterion. In this article, we derive newly the total expected cost under the same assumptions and consider some extended models.

Income Taxation and Finite Horizons in a Human Capital Model

We address the issue ofcapital vs. labor income taxation in an overlapping generationsmodel with a positive externality in the human capital production.We compare the performance of the economy in the steady stateunder different tax policies. Three results are obtained. First,the size of the tax revenue required strongly affects the optimal(welfare maximizing) capital-labor income tax portfolio. Inparticular, a zero physical capital income tax rate need notbe optimal. Second, the way in which the finite life cycle issplit between the working and the retirement period also matters.And third, the size of the externality in the human capital productionalso affects the optimal income tax rate mix.

Is innovation possible, or even imperative, for facility management?

Argues that all TQM strategies have a finite life cycle and that thinking on quality is beginning to meet its limits. Asks how you motivate employees for yet another process of change. Discusses the role of the facilities manager and of education.

Long-Term Cycles and the Prediction of Petroleum Demand

Summary A great amount of effort is expended in attempting to predict both short- and long-term petroleum demand. This effort has become more difficult because oil markets have become more unpredictable. This paper presents a new look at long-term petroleum demand trends in terms of the presents a new look at long-term petroleum demand trends in terms of the derivative of Hubbert's life-cycle curve. The data reveal a long-term trend with fluctuations that result from recurring business cycles. It seems reasonable to extrapolate this trend into the future. A straight-line equation was derived by the least-squares method and extrapolated to the year 2000. Results suggest that average year-to-year growth of demand will be slightly positive until 2000, but the peak oil consumption that was reached in 1979 will not be exceeded until well into the 1990's, if at all. Introduction Strategic planning in any business must operate with certain assumptions about overall product demand. Estimation of both short- and long-term market movement requires much effort, particularly as oil markets have become more unpredictable. It is useful to diverge from the focus on short-term uncertainties and determine whether recent events can fit into a coherent, longterm viewpoint. Fig. 1 gives total U.S. liquid-hydrocarbon demand through 1984. Before 1973, demand increased almost continuously along a smooth curve. Planning could be done with the ostensible assurance of an expanded future market to absorb new production capacity. Although forecasters were aware, on an abstract basis, that petroleum is a finite resource and that exponential growth, therefore, must cease at some distant point, few near-term (5- to 10-year) projections assumed anything other than continued exponential growth (Fig. 1). The previously unprecedented changes in price and demand after 1973 spawned a decade of heightened efforts to predict and to influence (by government action) the demand for liquid hydrocarbons. After 1975, a resumption of exponential demand growth led many forecasters to the simplistic assumption that the 1973–75 period was only an aberration. It was asserted that after the oil-price increases had been absorbed into the economy, the market would continue to expand at an exponential rate until some time in the future as determined by economics and the depletion of the resource. Others, however, seriously discussed whether the limits to growth were being approached and whether demand would soon level out. It was pointed out that continuing the historical demand growth rate of 6%/yr would result in a clearly impossible 18-fold increase in only 50 years. In fact, any rate of exponential growth (a constant percentage rate of increase per year) becomes impossible if extrapolated far enough into the future. A hybrid forecast from the 1975–79 period would have assumed continuing market growth, but perhaps at a constant rate rather than an exponentially increasing rate (Fig. 1). What, then, can be expected for the future? It is obvious from Fig. 1 that there is no longer any basis for the simple extrapolation of past trends to predict future market demand. We could be poised to resume demand growth, to enter a period of stable demand, or to encounter further reductions. None of these scenarios appears to be incompatible with history. There are, of course, extensive efforts under way to apply increasingly sophisticated computer models and detailed economic analyses to the problem of predicting future demand patterns. This paper will not delve into those efforts but will be paper will not delve into those efforts but will be confined to looking at broad historical trends. Petroleum Production Petroleum Production Hubbert first drew widespread public attention to the finite life cycle of petroleum resources. In a remarkably prescient work, he fitted a logistic curve to U.S. prescient work, he fitted a logistic curve to U.S. production data through 1961 and predicted that U.S. domestic production data through 1961 and predicted that U.S. domestic production would reach a maximum in 1970. As shown production would reach a maximum in 1970. As shown in Fig. 2, U.S. domestic production (Curve B) did peak in 1970, although at a higher value than calculated by the Hubbert curve (Curve A). The Hubbert curve can be strictly constrained by geological analysis. The logistic equation used is Np = npa/(1+ae(-bt),...........................(1) where a = constant, b = constant, Np = cumulative production, nps = ultimately discoverable reserves, and t = time. A value for npa was calculated from geological analysis, and then values for a and b were determined by curvefitting the actual production data. The value of npa fixes the total area under the curve of production rate, Q = dNp/dt, vs. time. JPT P. 669

Different production strategies for a wall-paper factory

The problem which is analysed in this paper is from a wall-paper factory. The products here has a finite life cycle, which is known. The demand is uncertain but has to be supplied. Furthermore the set up costs are high compared with the variable production and inventory costs. The main contribution of this paper is the approach which makes it possible to analyze the production-inventory problem of a wall-paper factory. This approach leads to a suggestion of a concrete production-strategy for a wall-paper factory.