Maintenance Modeling and Control of Multi-unit Systems Subject to Condition Monitoring

受状态监测影响的多单元系统的维护建模和控制

• 批准号: RGPIN-2018-04447
• 负责人: Makis, Viliam
• 金额: $ 4.52万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=658549
• 关键词: Maintenance; Modeling; Control; Multi; unit

The proposed research will focus on the development of maintenance models and optimal maintenance policies for multi-unit systems with the special interest in widely appearing structures of real systems such as series systems and the systems consisting of N independently operating units. Examples of series systems include complex equipment and machinery. Examples of N-unit systems include energy systems such as wind or solar panel farms at different locations, oil drilling platforms in a particular geographical area, production systems consisting of several machines or production lines, and fleets of vehicles such as trucks, buses, trains or airplane fleets. In many situations the units themselves can be considered as series systems. Previous research has focused mainly on the development of maintenance models and optimal policies for single unit systems. The published research results for two-unit and multi-unit systems are very limited. Due to the high maintenance setup cost for systems considered in the proposed research which may include also the travel cost and the system downtime cost, there is an economic inter-dependence among the units, and the newly developed maintenance policies which will utilize opportunistic maintenance should bring substantial benefits. Other challenges in this research include the additional constraints associated with these systems such as energy or production demand satisfaction, scheduling of planned, periodic maintenance combined with the developed CBM policies for groups of the units to meet the transportation requirements, selection of the proper size of the fleets and the number of vehicles with different propulsion systems, and the subsequent replacement decisions. The proposed research provides several excellent challenging topics for Ph.D. and M.A.Sc. students and top journal publications are expected. The theories and methodologies which will be applied include CBM modeling and control using hidden Markov and semi-Markov modeling, Bayesian dynamic programming, semi-Markov decision process theory, optimal stopping, renewal and Markov renewal theory, theory of regenerative and semi-regenerative processes, proportional hazards modeling, EM algorithm and its extensions, phase-type modeling, group and opportunistic maintenance modeling, recently developed approximate stochastic dynamic programming methods and index policies, vector time series modeling and data dimensionality reduction methods, vibration data de-noising methods, and simulation. The results will be published in the front line journals and presented at major international conferences, they will contribute significantly to the further development of the discipline, will bring high economic benefits, and will be highly applicable and desirable in many industries.

建议的研究将集中在多部件系统的维修模型和最优维修策略的发展，特别是在广泛出现的结构的真实的系统，如串联系统和系统组成的N个独立运行的单元。串联系统的例子包括复杂的设备和机械。N单元系统的示例包括能源系统，例如位于不同位置的风力或太阳能电池板农场，特定地理区域中的石油钻井平台，由几台机器或生产线组成的生产系统，以及诸如卡车、公共汽车、火车或飞机队的车队。在许多情况下，单元本身可以被认为是串联系统。以往的研究主要集中在单部件系统的维修模型和最优策略的发展。对于两单元和多单元系统，已发表的研究成果非常有限。 由于在拟议的研究，其中可能还包括旅行成本和系统停机成本的系统考虑的高维护设置成本，有一个经济的相互依赖的单位之间，新开发的维护政策，将利用机会性维护应带来实质性的好处。在这项研究中的其他挑战包括与这些系统，如能源或生产需求的满足，调度计划，定期维护与开发的煤层气政策相结合的单位组，以满足运输要求，选择适当的规模的车队和车辆的数量与不同的推进系统，以及随后的更换决定。拟议的研究为博士生提供了几个极具挑战性的课题。和硕士学生和顶级期刊出版物的预期。将应用的理论和方法包括使用隐马尔可夫和半马尔可夫建模的CBM建模和控制，贝叶斯动态规划，半马尔可夫决策过程理论，最优停止，更新和马尔可夫更新理论，再生和半再生过程理论，比例风险建模，EM算法及其扩展，相类型建模，组和机会维护建模，最近发展的近似随机动态规划方法和指数策略，向量时间序列建模和数据降维方法，振动数据去噪方法，和仿真。研究结果将发表在前沿期刊上，并在主要国际会议上发表，它们将为该学科的进一步发展做出重大贡献，将带来很高的经济效益，并将在许多行业中具有高度的适用性和可取性。