可用度约束条件下的设备不完美预防维修策略

针对2M1B生产系统,基于设备实际维修情况,提出了故障设备不完美预防维修策略。首先,考虑设备随时间不断劣化的情况,基于准更新过程,建立了生产周期内设备随机故障次数的表达式,计算了设备维修总费用。其次,通过分析缓冲区内库存的变化轨迹,以生产周期内设备随机故障次数为基础,计算了缓冲区库存费用,综合设备维修费用和缓冲区库存费用,构建了周期内生产总成本模型。以满足系统最低要求的可用度水平为约束条件,以预防维修周期和缓冲区库存量为决策变量,以生产周期内单位时间总成本为目标函数,通过离散迭代算法获得最优预防维修周期和此周期下的最佳缓冲区库存量。最后,通过数值分析验证了模型的有效性,为制定最佳维修策略提供了有效依据。     

基于仿真的生产设备预防性维修周期研究

为了对生产系统中的设备故障加以有效的控制，从而减少设备故障的发生，文章对生产设备的预防性维修周期问题进行了研究。通过建立生产设备预防性维修的费用模型，利用仿真的方法对不同维修策略的预防性维修周期进行优化选择。该模型综合考虑了修复性维修成本、预防性维修成本和生产损失成本。最后以故障分布形式为威布尔分布的设备为例进行仿真实验，得出设备最优维修周期结果，并阐述了经济原则对预防性维修周期的影响。     

基于故障率修正参数的生产设备预防性维修研究

点检定修制是生产设备预防性维修的1种重要方法,是全员、全过程对设备进行动态管理的1种设备管理方法。点检定修制的核心是确定点检周期,即预防性维修周期。为此引入故障率修正参数,建立了基于单位时间净生产效益的生产设备预防性维修模型,并通过仿真的方法确立最佳预防性维修周期和维修次数,阐述了维修程度的不同对预防性维修周期的影响以及预防性维修对企业增加利润的重要性。结果表明,选择合理的故障率修正参数可以有效降低故障率,增大平均单位产值,从而为管理者制定有效的维修计划提供决策。     

MTO 管理模式下钢铁企业生产合同计划建模与优化

基于对钢铁企业MTO管理模式下合同计划的编制策略、约束条件和优化目标的研究，建立了合同计划优化模型，模型综合考虑了拖期惩罚费用、设备能力均衡利用和库存成本等优化目标，并采用加权法将多目标优化模型转换为单目标优化模型，针对模型的特点设计了求解模型的特殊PSO算法，以某钢铁企业的实际合同计划问题作为实例，在算法不同参数组合下进行了系统的测试，实验结果表明模型和算法是令人满意的。     

基于三阶段时间延迟模型的设备预防维修策略

针对设备劣化过程中出现多种非正常状态的问题,提出基于三阶段时间延迟理论的设备维修模型.首先,设备从缺陷到故障的过程并不只服从同一分布,因此,基于三阶段时间延迟模型,将设备故障分为初始缺陷、严重缺陷和故障3个状态,不同阶段定义不同的分布函数以模拟设备的劣化过程;其次,分析设备缺陷、故障发生的时刻与阈值时间点之间的关系,对维修情况进行分类,建立维修总期望费用模型,以单位时间维修费用最小为决策目标,求解出最佳预防维修周期时间和最佳阈值时间;最后,利用遗传算法求解数学模型,通过算例分析验证模型的有效性.所提出方法有助于企业根据维修计划定期进行预防维修检测,根据不同情况对设备出现的初始缺陷状态和严重缺陷状态进行预防维修.     

印染行业不可靠生产系统生产控制模型

基于印染行业自身特性,建立了适合于该行业特点的不可靠生产系统的生产控制模型。该模型不但考虑了生产设备时有故障和修复事件的发生,而且也把由于生产系统操作条件及生产原料属性的波动造成合格产品呈随机分布的情况纳入模型框架,其中当不同产品间生产切换时,所需切换时间及切换费用也被引入模型,并假设此时设备的故障过程为Markov过程。结合单设备单产品情况,给出了其最优生产控制策略。为实现印染行业生产的优化控制及建立完善的MES系统提供了理论支持。     

基于时间延迟的多类型维修与经济生产批量联合优化研究

针对目前未能较好的综合考虑多维修类型与经济生产批量联合优化的问题，首先考虑多类型维修关系，基于时间延迟理论求出故障和缺陷次数的表达式；其次，在此基础上，综合考虑生产费用和维修费用的基础上，构建了多类型维修和经济生产批量联合优化模型，以单位时间内总费用最小为优化目标，获得最优检查间隔期和经济生产批量；最后，通过算例分析验证了模型的有效性，说明了第一类缺陷检查次数的多少对费用和经济生产批量影响不大。     

需求随机的变质性产品生产计划模型

研究了能力约束的有限计划展望期生产计划问题,各周期的需求随机,库存产品存在变质且变质率为常数。建立了问题的期望值模型,目标函数为极小化生产准备成本、生产成本、库存成本的期望值。提出了随机模拟、遗传算法和启发式算法相结合的求解算法。用数值实例对模型和算法进行了验证,优化结果表明模型和算法是有效的。     

流程工业生产和维修计划数学模型

在流程工业生产中维修计划是极其重要的.在同时考虑生产和定期维修计划的情况下,开发了流程工业混合整数线性规划模型.该模型可安排生产和定期维修计划,实现生产、延期交货、故障维修和定期维修的综合成本最小化.模型考虑到前期维修期间的设备故障的可能性.模型表达式具有通用性,因此适合多种生产环境.     

基于粒子群算法的供应链生产、配送集成计划研究

针对单工厂、多产品、多周期、多配送中心的供应链网络,构建了生产、配送集成计划模型,提出了用于求解该问题的粒子群算法方案,阐明了该算法方案的具体实现过程。采用分离策略提出独立决策下的生产计划模型和配送计划模型。仿真实例的计算结果表明集成决策可以有效地降低供应链成本。     

需求随机波动下多设备批量生产系统的视情维护策略研究

针对需求随机波动情况下多设备批量生产系统的设备维护问题,提出了一种基于滚动生产计划和设备退化状况的视情维护策略。首先,通过滚动时域规划方法预测不同产品的随机需求并在此基础上以总生产成本最小确定滚动生产计划。其次,在每一滚动生产周期开始前检测系统中各设备的退化水平,利用Gamma过程描述退化增量,以最小维护成本率确定当前退化状态下各设备的最佳维护时间,同时为避免生产过程中断利用提前延后维护策略对预防维护进行动态调整。在系统层,利用生产转换时机对需要维护的组件进行组合维护。再次,引入时间约束和服务水平约束,建立批量生产与视情维护的联合优化模型,以总成本最小为目标,确定实际生产计划和维护计划。最后,通过算例以整个生产计划期内的总成本和故障次数为度量验证了所提出的多设备批量生产系统视情维护策略的有效性。     

Optimal economic production quantity policy for randomly failing process with minimal repair,backorder and preventive maintenance

This study examines the feasibility of using an economic production quantity (EPQ) model incorporating maintenance and production programs to model an imperfect process involving a deteriorating production system. In response to failure, defective parts were produced and minimal repairs performed to create an in-control state. The conditions are studied in the case of the EPQ model undergoing a backorder owing to rejection of defective parts after a failure. Following production run period, two types of periodic preventive maintenance (PM) exist: imperfect and perfect. The probability of perfect PM being performed depends on the number of imperfect PM performed since the last renewal cycle. For the EPQ model, the optimal run time for minimising the total cost is discussed. Various special cases are considered, including the PM learning effect. Finally, this investigation presents a numerical example to illustrate the effects of PM ability, repair cost and defect number on total costs and production period. This study finds that enhancing maintenance ability reduces production related costs. The product system can be produced more efficiently using a PM program.     

A mathematical model on EPQ for stochastic demand in an imperfect production system

In the paper, we develop an EPQ (economic production quantity) inventory model to determine the optimal buffer inventory for stochastic demand in the market during preventive maintenance or repair of a manufacturing facility with an EPQ (economic production quantity) model in an imperfect production system. Preventive maintenance, an essential element of the just-in-time structure, may cause shortage which is reduced by buffer inventory. The products are sold with the free minimal repair warranty (FRW) policy. The production system may undergo “out-of-control” state from “in-control” state, after a certain time that follows a probability density function. The defective (non-conforming) items in “in-control” or “out-of-control” state are reworked at a cost just after the regular production time. Finally, an expected cost function regarding the inventory cost, unit production cost, preventive maintenance cost and shortage cost is minimized analytically. We develop another case where the buffer inventory as well as the production rate are decision variables and the expected unit cost considering the above cost functions is optimized also. The numerical examples are provided to illustrate the behaviour and application of the model. Sensitivity analysis of the model with respect to key parameters of the system is carried out.     

Joint production and maintenance strategy for economic production quantity model with imperfect production processes

In this study, an economic production quantity (EPQ) model is generalized by considering maintenance and production programs for an imperfect process involving a deteriorating production system with increasing hazard rate. There are two types of preventive maintenance (PM), namely imperfect PM and perfect PM. The probability that perfect PM is performed depends on the number of imperfect maintenance operations performed since the last renewal cycle. Following a failure, the delayed repair performs some restorations and reduces production rate to restore the system into an operating state (in-control state), but leaves its lower production rate until perfect PM is performed. That is, the production run period not always starts in normal production rate. This study considers backorders, as well as loss of inventory due to the lower production rate. For the EPQ model, the optimum run time, which minimizes the total cost, is discussed. Various special cases are considered, including the maintenance learning effect. Finally, a numerical example is presented to illustrate the effects of PM ability, repair cost and production decreasing rate on total costs and production period.     

Planning and optimizing the maintenance of paper production systems in a paper plant

Manufacturing and production plants operate physical assets that deteriorate with usage and time, thus, maintenance actions are required to restore the assets back to their original predetermined operational conditions. But since, organizational resources are limited and scarce. The objective of an effective maintenance program is to minimize total cost of inspection and repair, and equipment downtime. In this paper, we describe a new multi-criteria optimization framework for deriving optimal maintenance schedules for preventive maintenance which considers availability, maintenance cost and life cycle costs as the criteria for optimization. The Simulink toolbox of the Matlab has been interfaced with Genetic algorithm for optimization. After getting solution, Stochastic Petri nets has been used to model the system and find out the effect of optimized maintenance schedules on system performance. The application of the proposed framework has been discussed on a practical case of a paper plant.     

基于服务性能合同模式下单部件系统视情维修策略研究

针对供应商系统维修的低效率以及维修成本参数较难获得的问题,提出了基于服务性能合同模式(PBC)下的单部件系统最优视情维修策略模型。首先,基于Gamma分布,描述单部件系统连续递增的退化过程,依据系统实时检测状态与预防维修阈值、故障阈值之间的关系,实施不同的维修策略;其次,分析单位更新周期内的检测次数和使故障设备恢复如新的维修方式,以供应商利润率最大化为目标函数,以最佳维修阈值与检测间隔时间为决策变量,建立以利润为中心的视情维修优化模型;最后,利用改进灰狼算法求解数学模型,通过算例验证所提出模型的有效性,并进行了各维修费用参数对目标函数以及最优维修策略的灵敏度分析。     

The economic production lot size model extended to include more than one production rate

We study an extension of the economic production lot size model, where more than one production rate can be used during a cycle. Moreover, the production rates, as well as their corresponding runtimes are decision variables. We decompose the problem into two subproblems. First, we show that all production rates should be chosen in the interval between the demand rate and the production rate which minimizes unit production costs, and should be used in an increasing order. Then, given the production rates, we derive closed‐form expressions for all optimal runtimes as well as the minimum average cost. This analysis reveals that it is the size of the setup cost that determines the need for being able to use several production rates. We also show how to derive a near‐optimal solution of the general problem.