Optimum Burn-in Time for a Bathtub Shaped Failure Distribution

An important problem in reliability is to define and estimate the optimal burn-in time. For bathtub shaped failure-rate lifetime distributions, the optimal burn-in time is frequently defined as the point where the corresponding mean residual life function achieves its maximum. For this point, we construct an empirical estimator and develop the corresponding statistical inferential theory. Theoretical results are accompanied with simulation studies and applications to real data. Furthermore, we develop a statistical inferential theory for the difference between the minimum point of the corresponding failure rate function and the aforementioned maximum point of the mean residual life function. The difference measures the length of the time interval after the optimal burn-in time during which the failure rate function continues to decrease and thus the burn-in process can be stopped.      

Determination of the optimal accelerated burn-in time under Arrhenius–Lognormal distribution assumption

Burn-in has been widely used as an effective procedure for screening out failed electronic products during the early-failure period, before shipment to the customers. Environmental stress such as temperature is increasingly being used to effectively shorten the burn-in time, and this method is usually called an accelerated burn-in test. When different stress levels are chosen for the burn-in operation, the burn-in times must be determined. An Arrhenius–Lognormal distribution can describe the lognormal lifetime of electronic products under different temperature levels. In this paper, the Arrhenius–Lognormal distribution and its mean residual life function are applied to the accelerated burn-in cost model, and a genetic algorithm is used to solve for the optimal burn-in time. We choose a real TFT–LCD module as an example, and determine its optimal accelerated burn-in time. A sensitivity analysis of the TFT–LCD module case shows the effect of model parameters on optimal burn-in time.     

Burn-in and the performance quality measures in heterogeneous populations

Burn-in is a widely used engineering method of elimination of defective items before they are shipped to customers or put into field operation. Under the assumption that a population is described by the decreasing or bathtub-shaped failure rate functions, various optimal burn-in problems have been intensively studied in the literature. In this paper, we consider a new model and assume that a population is composed of stochastically ordered subpopulations described by their own performance quality measures. It turns out that this setting can justify burn-in even in situations when it is not justified in the framework of conventional approaches. For instance, it is shown that it can be reasonable to perform burn-in even when the failure rate function that describes the heterogeneous population of items increases and this is one of the main and important findings of our study.     

Supply chain scheduling: Sequence coordination

A critical issue in supply chain management is coordinating the decisions made by decision makers at different stages, for example a supplier and one or several manufacturers. We model this issue by assuming that both the supplier and each manufacturer have an ideal schedule, determined by their own costs and constraints. An interchange cost is incurred by the supplier or a manufacturer whenever the relative order of two jobs in its actual schedule is different from that in its ideal schedule. An intermediate storage buffer is available to resequence the jobs between the two stages. We consider the problems of finding an optimal supplier's schedule, an optimal manufacturer's schedule, and optimal schedules for both. The objective functions we consider are the minimization of total interchange cost, and of total interchange plus buffer storage cost. We describe efficient algorithms for all the supplier's and manufacturers’ problems, as well as for a special case of the joint scheduling problem. The running time of these algorithms is polynomial in both the number of jobs and the number of manufacturers. Finally, we identify conditions under which cooperation between the supplier and a manufacturer reduces their total cost.     

Optimal burn-in for maximizing reliability of repairable non-series systems

Burn-in is a manufacturing process applied to products to eliminate early failures in the factory before the products reach the customers. Various methods have been proposed for determining an optimal burn-in time of a non-repairable system or a repairable series system, assuming that system burn-in improves all components in the system. In this paper, we establish the trade-off between the component reliabilities during system burn-in and develop an optimal burn-in time for repairable non-series systems to maximize reliability. One impediment to expressing the reliability of a non-series system is in that successive failures during system burn-in cannot be described precisely because a failed component is not detected until the whole system fails. For approximating the successive failures of a non-series system during system burn-in, we considered two types of repair: minimal repair at the time of system failure, and repair at the time of component or connection failure. The two types of repair provide bounds on the optimal system burn-in time of non-series systems.     

消费者公平偏好对制造商开通直销渠道的影响研究

研究了消费者公平偏好对制造商开通直销渠道的影响,并分析消费者公平偏好对制造商和零售商的最优决策、制造商开通直销渠道意愿、零售商利润、以及消费者剩余等的影响。最后通过算例分析消费者公平偏好对制造商开通直销渠道意愿的影响。研究发现:不存在消费者公平偏好时,制造商仅在直销成本较小时开通直销渠道;当直销成本较大时,制造商不应开通直销渠道。然而,消费者公平偏好会降低制造商开通直销渠道的意愿;即使无直销成本,若消费者公平偏好较大,制造商也可能不会开通直销渠道。     

Burn-in considering yield loss and reliability gain for integrated circuits

This paper presents burn-in effects on yield loss and reliability gain for a lifetime distribution developed from a negative binomial defect density distribution and a given defect size distribution, after assuming that the rate of defect growth is proportional to the power of the present defect size. While burn-in always results in yield loss, it creates reliability gain only if either defects grow fast or the field operation time is long. Otherwise, burn-in for a short time could result in reliability loss. The optimal burn-in time for maximizing reliability is finite if defects grow linearly in time and is infinite if defects grow nonlinearly in time. The optimal burn-in time for minimizing cost expressed in terms of both yield and reliability increases in the field operation time initially but becomes constant as the field operation time is long enough. It is numerically shown that increasing mean defect density or defect clustering increases the optimal burn-in time.     

节能情形下制造企业动态批量生产策略与节能方式选择

随着诸多严厉的环保政策的实行,节能管理已成为我国高耗能制造企业运营管理中的一个重要内容。通过构建自我节能、节能效益分享和节能量保证三种节能方式下制造企业的动态批量生产决策模型,首先分析了给定节能方式下制造企业的最优动态批量生产策略,其次探讨了制造企业最优节能方式选择。结果表明,最优动态批量生产策略满足“零库存生产”规则。进一步的数值实验分析结果表明:面临前两种节能方式时,当节能服务公司与制造企业的节能投资成本系数比率和采用合同能源管理的预计节能率较小时,制造企业应选择后者,反之应选择前者;面临后两种节能方式时,当采用合同能源管理的预计节能率较小时,制造企业选择两者无差异,反之应选择前者。     

An extended warranty policy with options open to consumers

An extended warranty model that includes a free repair period and an extended warranty period will be discussed. Consumers have choices to renew or not to renew at the end of free repair period. Different choices will have different cost implications for consumers and manufacturers. The exact expressions of the total expected discounted cost, and the long-run average cost per unit time for a consumer and the manufacturer are derived. Then the optimal policies for the consumers are obtained. Under the assumption that a consumer has applied his/her optimal policy, an optimal policy or an ε-optimal policy for the manufacturer is then determined analytically.     

权力结构影响下考虑预售的双渠道供应链决策研究

针对存在预售且通过网络与传统渠道销售的现实状况,基于消费者剩余理论和博弈论,构建不同权力结构下的双渠道供应链博弈模型:制造商主导的Stackelberg、权力对等的Vertical Nash和零售商主导的Stackelberg。比较三种权力结构下各成员最优策略及绩效,分析关键因素的敏感性,检验模型的鲁棒性。研究发现:三种博弈下各权力主体的最优策略及绩效均受渠道替代程度、单位生产成本等关键因素影响。渠道替代程度越高,制定的双渠道价格越高;消费者对价格更敏感,预售市场需求呈现向现售市场转移的趋势。     

Pricing and two-tier advertising with one manufacturer and one retailer

This paper considers the pricing decisions and two-tier advertising levels between one manufacturer and one retailer where customer demand depends on the retail price and advertisement by a manufacturer and a retailer. We solve a Stackelberg game with the manufacturer as the leader and the retailer as the follower. With price sensitive customer demand and a linear wholesale contract, we obtain the optimal decisions by the manufacturer and the optimal responses by the retailer. Our results show that cost sharing of local advertising does not work well, it is better for the manufacturer to advertise nationally and offer the retailer a lower wholesale price.     

汽车行业中买断销售策略分析

买断销售指的是销售商和制造商就某产品在一定区域内达成协议,销售商以买断价格从制造商处采购一定数量的产品,然后由销售商对产品进行定价对外销售.制造商通过采取买断销售实现了对产品的促销.在现实背景的基础上,分析了制造商应该在何时采取买断销售方式,以及买断策略下相应的决策问题.找到了制造商采取买断策略的条件,以及该策略下最优买断价格和买断数量决策,并发现在制造商的最优决策下,制造商和销售商能够实现双赢.     

Supply chain scheduling: Just-in-time environment

We study the benefits of coordinated decision making in a supply chain consisting of a manufacturer, a distributor, and several retailers. The distributor bundles finished goods produced by the manufacturer and delivers them to the retailers to meet their demands. The distributor is responsible for managing finished goods inventory. An optimal production schedule of the manufacturer, if imposed on the distributor, may result in an increased inventory holding cost for the distributor. On the other hand, an optimal distribution schedule of the distributor, if imposed on the manufacturer, may result in an increased production cost for the manufacturer. In this paper we develop mathematical models for individual optimization goals of the two partners and compare the results of these models with the results obtained for a joint optimization model at the system level. We investigate the computational complexities of these scheduling problems. The experimental results indicate that substantial cost savings can be achieved at the system level by joint optimization. We also study conflict and cooperation issues in the supply chain. The cost of conflict of a supply chain partner is a measure of the amount by which the unconstrained optimal cost increases when a decision is to be made under the scheduling constraint imposed by the other partner. We quantify these conflicts and show that the cost of conflicts are significant. We also show that a cooperative decision will generate a positive surplus in the system which can be shared by the two partners to make cooperation and coordination strategy more attractive.     

双渠道模式下制造商线上定制策略研究

本文针对制造商在传统零售渠道和线上网络渠道同时销售标准产品的情况下,是否应该开放线上定制策略的相关问题进行分析。首先通过圆形市场模型完成市场划分;其次,在制造商不开放线上定制策略和开放线上定制策略两种情况下分别构建制造商和零售商利润最大化模型,得到了两种情况下的市场均衡结果。通过分析和比较两种情况下制造商和零售商的最优决策结果发现,当标准产品的边际生产成本较大且开放线上定制策略的成本较小时,制造商应该开放线上定制策略;制造商开放线上定制策略后,会使标准产品的批发价格和零售价格增加,并削弱零售商的利润;定制产品的生产成本越高,制造商开放定制产品的动机越小;消费者对标准产品的适应成本越高,制造商开放定制产品的动机越大。     

An agent-based negotiation model on price and delivery date in a fashion supply chain

Price and due-date negotiation between supply chain members is a critical issue. Motivated by industrial practice, we consider in this paper a make-to-order fashion supply chain in which the downstream manufacturer and the upstream supplier are cooperative on due-date and competitive on price. We propose a two-phase negotiation agenda based on such characteristics, and aim to find an optimal solution to deal with the negotiation problem considering production cost and mutual benefit. We build an analytical negotiation model for a manufacturer-supplier pair, discuss their utilities, and examine the Pareto efficiency frontier from the theoretical perspective. After that, from an application perspective, we build an agent-based two-phase negotiation system where agents are used to represent the two parties to enhance communication. In the cooperative phase, a simulated annealing based intelligent algorithm is employed to help the manufacturer agent and the supplier agent search tentative agreement on due dates which can minimize the total supply chain cost. In the competitive phase, the two parties bargain on the pricing issue using concession based methods. They adjust the reservation value and aspiration value for pricing accordingly based on the integrated utility and the result of the previous phase. Simulation results show that, the proposed negotiation approach can achieve optimal utility of agents and reach a win-win situation for the bilateral parties. Sensitivity analysis is conducted to further generate insights on how different parameters affect the performance of the proposed system.     

一种带有生产费用扰动的供应链协调问题

本文研究了一个生产两个竞争零售商的供应链在生产费用发生扰动下的协调问题．生产费用发生扰动后，零售商的投资额与生产商的生产数量都会和原计划不同．研究发现批发价加投资补贴率的合同可以协调扰动后的供应链，通过调整批发价和补贴率，可使供应链总的利润在生产商与两个零售商之间分配，并用数值模拟分析了所得结果的合理性．     

In the determination of weight sets to compute cross-efficiency ratios in DEA

Data envelopment analysis (DEA) measures the production performance of decision-making units (DMUs) which consume multiple inputs and produce multiple outputs. Although DEA has become a very popular method of performance measure, it still suffers from some shortcomings. For instance, one of its drawbacks is that multiple solutions exist in the linear programming solutions of efficient DMUs. The obtained weight set is just one of the many optimal weight sets that are available. Then why use this weight set instead of the others especially when this weight set is used for cross-evaluation? Another weakness of DEA is that extremely diverse or unusual values of some input or output weights might be obtained for DMUs under assessment. Zero input and output weights are not uncommon in DEA. The main objective of this paper is to develop a new methodology which applies discriminant analysis, super-efficiency DEA model and mixed-integer linear programming to choose suitable weight sets to be used in computing cross-evaluation. An advantage of this new method is that each obtained weight set can reflect the relative strengths of the efficient DMU under consideration. Moreover, the method also attempts to preserve the original classificatory result of DEA, and in addition this method produces much less zero weights than DEA in our computational results.     

供应中断风险下制造商的后备采购与改善努力策略比较研究

在供应中断风险环境下,对制造商的后备采购策略和改善努力策略进行了比较分析.研究发现,制造商在改善努力策略时向主供应商的采购数量恒大于在后备采购策略时的采购数量.改善努力与后备采购策略的收益差总是随着改善努力成本投入的增大而呈现出递减的规律.当努力成本投入变得不经济时,制造商将放弃对主供应商的改善努力.     

Optimal pricing strategies under co-existence of price-takers and bargainers in a supply chain

We investigate how the co-existence of two types of customers, price-takers, and bargainers, influences the pricing decisions in a supply chain. We consider a stylized supply chain that includes one manufacturer and one retailer, and we characterize the optimal prices of the retailer and the manufacturer. We further discuss the effects of the fraction of the bargainers in the customer population and the relative bargaining power of the bargainers on these optimal prices. Our results show that, given the wholesale price, the lowest price at which the retailer is willing to sell (ie, cut-off price) increases with the relative bargaining power of the bargainers. Both posted and cut-off prices increase in the fraction of the bargainers in the customer population. Moreover, depending on the type of negotiation cost, the variations of both prices will vary. In equilibrium, both posted and cut-off prices do not monotonically increase with the fraction of the bargainers in the customer population. When the maximum reservation price of the customers is low, and/or the negotiation costs are high, and/or the relationship between the bargainer's negotiation cost and reservation price is high, the retailer may reduce both posted and cut-off prices as the fraction of the bargainers increases.     

Price discount based on early order commitment in a single manufacturer–multiple retailer supply chain

Early order commitment (EOC) is a strategy for supply chain coordination, wherein the retailer commits to purchasing from a manufacturer a fixed order quantity a few periods in advance of the regular delivery lead time. In this paper, we formulate and analyze the EOC strategy for a decentralized, two-level supply chain consisting of a single manufacturer and multiple retailers, who face external demands that follow an autocorrelated AR(1) process over time. We characterize the special structure of the optimal solutions for the retailers’ EOC periods to minimize the total supply chain cost and discuss the impact of demand parameters and cost parameters. We then develop and compare three solution approaches to solving the optimal solution. Using this optimal cost as the benchmark, we investigate the effectiveness of using the wholesale price-discount scheme for the manufacturer to coordinate this decentralized system. We give numerical examples to show the benefits of EOC to the whole supply chain, examine the efficiency of the discount scheme in general situation, and provide the special conditions when the full coordination is achieved.