基于能耗结余窗口的可持续制造系统维护决策

面向烟草的可持续生产系统,提出基于能耗结余窗口的多层级维护决策。在设备层,通过综合烟草设备的退化规律、内部维护效果以及外部环境工况等条件,建立了综合成本、可用度以及能耗的多目标预知维护规划模型,动态规划各台烟草设备的预知维护时机。在系统层,将单台设备进行维护作业时系统待机的时机作为能耗结余窗口,综合考虑设备间能耗优化的关联性、批量生产等特征进行维护时机调整,降低了调度复杂性,并有效减少烟草批量制造过程中的停机次数。算例分析表明,与传统的机会维护策略相比,提出的基于能耗结余窗口的多层级维护决策能够显著降低系统运维产生的能耗。     

浅谈离心泵常见故障及解决办法

针对离心泵维护、检修上存在的问题，通过定期监测，采用频谱分析技术判断出故障原因和程度，全面掌握设备安全状况，为设备的预知性维修提供了切实的依据，有助于综合效益和管理水平的提高，同时也有利于降低维修费用、提高设备的安全性。     

浅谈离心泵常见故障及解决办法

针对离心泵维护、检修上存在的问题，通过定期监测，采用频谱分析技术判断出故障原因和程度，全面掌握设备安全状况，为设备的预知性维修提供了切实的依据，有助于综合效益和管理水平的提高，同时也有利于降低维修费用、提高设备的安全性。     

投影寻踪方法在设备预知维护中的应用研究EI北大核心CSCD

提出了一种融合投影寻踪的自回归分析方法实现设备的预知维护。该预知维护方法是从设备关键部件处提取振动信号,经分析和计算得出24种特征指标用以描述设备运行状态;对24种特征指标分别提取一个时间序列并各自进行自回归分析,得到各自对应的预测因子;利用投影寻踪将前述预测因子投影到二维空间,然后分别建立预测因子投影值与相对应的特征指标值的拟合函数,进而推算出24种特征指标的未来值;再通过对24种特征指标的未来值在最佳投影方向矩阵下进行投影,根据投影值的分布情况判断设备未来运行状态是否存在异常,从而实现设备的预知维护。最后利用美国西储大学轴承数据中心网站公开发布的轴承探伤测试数据集中的内圈故障数据和山西省某洗煤厂主井皮带机的减速器故障数据进行了验证。     

投影寻踪方法在设备预知维护中的应用研究

提出了一种融合投影寻踪的自回归分析方法实现设备的预知维护。该预知维护方法是从设备关键部件处提取振动信号,经分析和计算得出24种特征指标用以描述设备运行状态;对24种特征指标分别提取一个时间序列并各自进行自回归分析,得到各自对应的预测因子;利用投影寻踪将前述预测因子投影到二维空间,然后分别建立预测因子投影值与相对应的特征指标值的拟合函数,进而推算出24种特征指标的未来值;再通过对24种特征指标的未来值在最佳投影方向矩阵下进行投影,根据投影值的分布情况判断设备未来运行状态是否存在异常,从而实现设备的预知维护。最后利用美国西储大学轴承数据中心网站公开发布的轴承探伤测试数据集中的内圈故障数据和山西省某洗煤厂主井皮带机的减速器故障数据进行了验证。     

考虑租赁延迟的设备预防维护策略优化研究

根据租赁设备的维护实际情况,给出了租赁延迟的定义,提出一种更接近设备运行真实情况的周期预防维护策略模型。该策略综合考虑设备的休眠期、预防维护和小修等因素对维护费用的影响,从出租方角度出发,建立以维护总费用最小化为目标的周期预防维护模型,并给出模型取得最优策略的相关理论证明和最优值的求解算法。最后是算例分析,研究表明,该策略符合租赁设备维护的实际情况,可为租赁企业提供有效的设备维护解决方案。     

一种玻壳研磨设备预防性维护周期的决策方法

针对传统的基于固定时间周期的玻壳研磨设备的预防性维护策略难以有效满足设备玻壳生产线优化的特点。本文研究了一种基于神经网络模型的玻壳研磨设备预防性维护周期动态决策方法。基于本企业运行数据验证表明,该方法对玻壳研磨设备的预防性维护周期进行动态决策是可行的,对降低玻壳研磨设备的预防性维护成本,提高研磨设备的利用率等具有重要作用。     

备件约束下租赁设备的维护策略研究

从租赁企业视角出发,引入备件库存及备件运输等因素,建立租赁设备的等周期修复非新预防维护模型,通过最小化包括备件成本在内的租赁维护总成本,获得租赁设备的优化维护策略,以指导租赁企业设备维护计划的有效管理。     

设备点检定修模式的建立及应用

通过对设备点检定修模式的探索,形成适合企业自身设备特点的点检定修模式,摒弃传统事后维修设备管理方法,真正实现设备预知维修的目的,以利于企业进一步细化设备管理、提高设备运行效率。     

基于可靠度限制的周期性预防维护模型研究

实施周期性的预防维护可以减缓设备的老化速度,进而增加设备的使用寿命.考虑设备经维护后会改善的情况.提出并构建了一个改善因子模型,以此描述设备维护改善的效果,该改善因子模型综合考虑了预防维护成本、设备年龄以及维护过程学习效应等因素影响.在改善因子模型基础上,基于无限时间域的概念,构建了包含预防维护成本、最小修复成本、置换成本等在内的成本函数.在可靠度限制下,推导出了单位时间成本函数和最佳维护时间间隔的计算模型,给出了计算最佳参数的流程.最后,进行了实例分析.     

Maintenance Strategies and Failure‐Cost Model for Medical Equipment

This paper proposes a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of the equipment. The proposed model is simulated in Scilab using real data extracted from maintenance history of anaesthesia machine from Draeger. The analysis using survival approach reveals that conducting preventive maintenance on the selected medical equipment had a positive impact on survival of equipment. The model is then used to analyse the cost of maintenance scenarios, and an appropriate scenario is proposed for anaesthesia machine. A new failure‐cost model is developed, which may be used to calculate the number of failures of equipment and the annual maintenance cost. The proposed models may be used as a planning tool for selecting maintenance strategies for various medical equipments. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal decision of an economic production quantity model for imperfect manufacturing under hybrid maintenance policy with shortages and partial backlogging

Considering the characteristics of the stochastic shift of the machine state and the uncertainty of the product quality of production, in this paper, we develop an optimisation decision of economic production quantity model for an imperfect manufacturing system under hybrid maintenance policy with shortages and partial backlogging. We assume that the production process is imperfect stemming from the machine reliability and the probability of out-of-control, a hybrid maintenance policy combined of emergency maintenance and preventive maintenance is executed during each production run. Three decision models based on the scenarios of machine breakdown and repair time are developed. The optimal production quantity and maintenance inspection number during each production run are solved with minimising the expected average cost of the system. Numerical examples are used to demonstrate the effectiveness and feasibility of the model. Sensitivity analysis is conducted to analyse the impacts of key parameters on the optimal decision. Some implications related to the effective and economical execution of maintenance policy for practitioners are derived.     

Effect of maintenance policies on the just-in-time production system

Using simulation, experimental design, and regression analysis, mathematical models are developed here to describe the effect that maintenance policy, machine unreliability, processing time variability, ratio of preventive maintenance time to processing time, ratio of minimal repair time to preventive maintenance time, and production line size have on various measures of performance, namely total production line output and production line variability of the just-in-time production system. The analysis of the data shows that under different situations, different maintenance policies do not have the same effect on the production line performance. The following conclusions were obtained; when the number of production machines is low (five machines or less), and/or when the ratio of minimal repair time to preventive maintenance time is high, maintenance policy III leads to a higher performance than maintenance policy II. Otherwise maintenance policy II, which is more sensitive to the change of the ratio of minimal repair time to preventive maintenance time, leads to a higher performance. The results of the study can be utilized in choosing a maintenance policy as a function of the production process parameters. Once a policy is chosen, the practitioner can select the most important factors to control under that policy in order to minimize the machine idle time, maximize the production process reliability, improve productivity, and therefore increase the production line performance.     

A method combining rules with genetic algorithm for minimizing makespan on a batch processing machine with preventive maintenance

This paper considers the problem of minimising makespan on a single batch processing machine with flexible periodic preventive maintenance. This problem combines two sub-problems, scheduling on a batch processing machine with jobs’ release dates considered and arranging the preventive maintenance activities on a batch processing machine. The preventive maintenance activities are flexible but the maximum continuous working time of the machine, which is allowed, is determined. A mathematical model for integrating flexible periodic preventive maintenance into batch processing machine problem is proposed, in which the grouping of jobs with incompatible job families, the starting time of batches and the preventive maintenance activities are optimised simultaneously. A method combining rules with the genetic algorithm is proposed to solve this model, in which a batching rule is proposed to group jobs with incompatible job families into batches and a modified genetic algorithm is proposed to schedule batches and arrange preventive maintenance activities. The computational results indicate the method is effective under practical problem sizes. In addition, the influences of jobs’ parameters on the performance of the method are analyzed, such as the number of jobs, the number of job families, jobs’ processing time and jobs’ release time.     

Adaptive time dynamic model for production volume prediction

Data from a continuously operating high volume lathe was collected over a period of a number of months. This machine would periodically fail and unplanned maintenance was often necessary. Failures were due to a myriad of causes. At the beginning of each month, management was required to estimate production output for the month. This paper shows how this goal might be facilitated via a sequence of Bayesian models analysing previous data. The validity of the procedure is justified by an empirical study.     

维修服务契约的最优设计和分析

本文研究了一个带服务契约的机器维修模型.为了合理优化设计机器维修服务契约,本文利用多服务器排队系统理论对具有多台机器和多个修理工的机器维修模型进行分析,得到了每台机器产生的纯收益和代理商的纯收益期望值;利用非合作博弈论对维修服务契约进行分析,得到了最优保修期、保修费和修理工数目.我们发现最优保修期和修理工数目均与保修价格函数无关.而且,对于固定寿命的机器,机器总数几乎不影响最优保修期的设定.     

Scheduling with non-decreasing deterioration jobs and variable maintenance activities on a single machine

There is a situation found in many manufacturing systems, such as steel rolling mills, fire fighting or single-server cycle-queues, where a job that is processed later consumes more time than that same job when processed earlier. The research finds that machine maintenance can improve the worsening of processing conditions. After maintenance activity, the machine will be restored. The maintenance duration is a positive and non-decreasing differentiable convex function of the total processing times of the jobs between maintenance activities. Motivated by this observation, the makespan and the total completion time minimization problems in the scheduling of jobs with non-decreasing rates of job processing time on a single machine are considered in this article. It is shown that both the makespan and the total completion time minimization problems are NP-hard in the strong sense when the number of maintenance activities is arbitrary, while the makespan minimization problem is NP-hard in the ordinary sense when the number of maintenance activities is fixed. If the deterioration rates of the jobs are identical and the maintenance duration is a linear function of the total processing times of the jobs between maintenance activities, then this article shows that the group balance principle is satisfied for the makespan minimization problem. Furthermore, two polynomial-time algorithms are presented for solving the makespan problem and the total completion time problem under identical deterioration rates, respectively.     

Preventive maintenance and replacement policies for deteriorating production systems subject to imperfect repairs

This paper presents a special case of integration of the preventive maintenance into the repair/replacement policy of a failure-prone system. The machine of the considered system exhibits increasing failure intensity and increasing repair times. To reduce the failure rate and subsequent repair times following a failure, there is an incentive to perform preventive maintenance on the machine before failure. When a failure occurs, the machine can be repaired or replaced by a new one. Thus the machine's mode at any time can be classified as either operating, in repair, in replacement or in preventive maintenance. The decision variables of the system are the repair/replacement switching age or number of failures at the time of the machine's failure and the preventive maintenance rate. The problem of determining the repair/replacement and preventive maintenance policies is formulated as a semi-Markov decision process and numerical methods are given in order to compute optimal policies which minimise the average cost incurred by preventive maintenance, repair and replacement over an infinite planning horizon. As expected, the decisions to repair or to replace the machine upon a failure are modified by performing preventive maintenance. A numerical example is given and a sensitivity analysis is performed to illustrate the proposed approach and to show the impact of various parameters on the control policies thus obtained.     

Energy efficiency analysis of machine tools with periodic maintenance

Machine tools consume a large amount of energy in the production process. Effective reduction of energy consumption of the machine tool will lead to significant savings. Although substantial efforts have been devoted to reducing energy consumption of the machine tool through upgrading the equipment or improving the manufacturing process, the study of energy efficiency improvement through effective maintenance operations scheduling has received significantly less attention. Power consumption usually increases as the machine tool deteriorates in most mechanical manufacturing environments. In this paper, we develop a discrete-time, discrete-state homogeneous Markov chain of the deteriorating machine tool based on energy efficiency. To evaluate the energy performance and productivity performance of the machine tool with periodic maintenance, analytical models of average energy efficiency and average productivity are developed based on renewal reward theorem. The effects of some parameters on the average energy efficiency are analysed through a numerical example, and the trade-off between energy efficiency and productivity is discussed.     

Environmental issue in an integrated production and maintenance control of unreliable manufacturing/remanufacturing systems

This paper addresses a joint production and maintenance problem under environmental constraints and reliability issues in a manufacturing/remanufacturing context. The manufacturing system is composed of one machine producing one type of product. The remanufacturing system, also composed of one machine, retrieves returned products from the market in order to refurbish them. The manufacturing and remanufacturing systems aim to satisfy random demands under a given service level. Moreover, the entire system generates harmful emissions. Exceeding carbon emission limits defined by authorities may risk sanctions. We aim to propose a compromise between ecologic and economic production and maintenance plan by calling on green subcontracting in order to satisfy the demand and avoid emission excess. Three models are proposed in this paper. These models tackle mainly the basic production problems and propose alternative equivalent solution schemas for future extensions. The robustness and usefulness of the proposals are illustrated with various examples and sensitivity analyses.