The Experts below are selected from a list of 41256 Experts worldwide ranked by ideXlab platform

Yuanjian Yang - One of the best experts on this subject based on the ideXlab platform.

  • condition based Maintenance with scheduling threshold and Maintenance threshold
    IEEE Transactions on Reliability, 2016
    Co-Authors: Haikun Wang, Hongzhong Huang, Yanfeng Li, Yuanjian Yang
    Abstract:

    In order to arrange Maintenance resources according to system condition, the lead time needs to be considered within the context of condition-based Maintenance (CBM). Therefore, a scheduling threshold is introduced to replace the time to schedule, which is used as a decision variable in combination with a Maintenance threshold and a failure threshold. The long-run expected cost rate for Maintenance considers the Maintenance cost, the cost of the waiting time of suppliers and customers. In this way, suppliers can schedule Maintenance services in advance when the system condition reaches the scheduling threshold, and Perform Maintenance when the system condition exceeds the Maintenance threshold. Furthermore, the optimal Maintenance plan is updated dynamically in the framework of Prognostics and Health Management (PHM). Finally, a numerical example is provided to demonstrate the effectiveness and the dynamic nature of the proposed method.

Haikun Wang - One of the best experts on this subject based on the ideXlab platform.

  • condition based Maintenance with scheduling threshold and Maintenance threshold
    IEEE Transactions on Reliability, 2016
    Co-Authors: Haikun Wang, Hongzhong Huang, Yanfeng Li, Yuanjian Yang
    Abstract:

    In order to arrange Maintenance resources according to system condition, the lead time needs to be considered within the context of condition-based Maintenance (CBM). Therefore, a scheduling threshold is introduced to replace the time to schedule, which is used as a decision variable in combination with a Maintenance threshold and a failure threshold. The long-run expected cost rate for Maintenance considers the Maintenance cost, the cost of the waiting time of suppliers and customers. In this way, suppliers can schedule Maintenance services in advance when the system condition reaches the scheduling threshold, and Perform Maintenance when the system condition exceeds the Maintenance threshold. Furthermore, the optimal Maintenance plan is updated dynamically in the framework of Prognostics and Health Management (PHM). Finally, a numerical example is provided to demonstrate the effectiveness and the dynamic nature of the proposed method.

Vidar Skaar - One of the best experts on this subject based on the ideXlab platform.

  • Optimization of routing and scheduling of vessels to Perform Maintenance at offshore wind farms
    Energy Procedia, 2015
    Co-Authors: Magnus Stålhane, Lars Magnus Hvattum, Vidar Skaar
    Abstract:

    Abstract This paper studies the problem of finding the optimal routes and schedules for a fleet of vessels that are to Perform Maintenance tasks at an offshore wind farm. To solve the problem two alternative models are presented: an arc-flow and a path-flow formulation. Both models are tested on instances of varying numbers of vessels and Maintenance tasks. The arc-flow model is solved with commercial software using branch-and-bound. The path-flow model is solved heuristically by generating a subset of the possible routes and schedules, but produces close to optimal solutions using a lot less computing time than the exact arc-flow model.

Joachim Meyer - One of the best experts on this subject based on the ideXlab platform.

  • AAAI - Personalized alert agent for optimal user Performance
    2016
    Co-Authors: Avraham Shvartzon, Amos Azaria, Sarit Kraus, Claudia V. Goldman, Joachim Meyer, Omer Tsimhoni
    Abstract:

    Preventive Maintenance is essential for the smooth operation of any equipment. Still, people occasionally do not maintain their equipment adequately. Maintenance alert systems attempt to remind people to Perform Maintenance. However, most of these systems do not provide alerts at the optimal timing, and nor do they take into account the time required for Maintenance or compute the optimal timing for a specific user. We model the problem of Maintenance Performance, assuming Maintenance is time consuming. We solve the optimal policy for the user, i.e., the optimal timing for a user to Perform Maintenance. This optimal strategy depends on the value of user's time, and thus it may vary from user to user and may change over time. Based on the solved optimal strategy we present a personalized Maintenance agent, which, depending on the value of user's time, provides alerts to the user when she should Perform Maintenance. In an experiment using a spaceship computer game, we show that receiving alerts from the personalized alert agent significantly improves user Performance.

  • AAMAS - A Game for Studying Maintenance Alerts' Effectiveness
    2015
    Co-Authors: Avraham Shvartzon, Amos Azaria, Sarit Kraus, Claudia V. Goldman, Omer Tsimhoni, Joachim Meyer
    Abstract:

    In this paper we present a space-ship game which allows us to evaluate human behavior with respect to Maintenance and repairing malfunctions. We ran an experiment in which subjects played the space-ship game twice. In one of the games, they were simply told that they should Perform Maintenance every 20 seconds, and in the other game they received alerts from an agent for Performing Maintenance every 20 seconds. We show that when receiving alerts, people tented to Perform more Maintenance, and Perform slightly better (not statistically significant). We suggest that in order to further improve the Performance of the players in the space-ship game, one should also consider when to provide these alerts.

  • A Game for Studying Maintenance Alerts' Effectiveness (Extended Abstract)
    2015
    Co-Authors: Avraham Shvartzon, Amos Azaria, Sarit Kraus, Claudia V. Goldman, Omer Tsimhoni, Joachim Meyer
    Abstract:

    In this paper we present a space-ship game which allows us to evaluate human behavior with respect to Maintenance and repairing malfunctions. We ran an experiment in which subjects played the space-ship game twice. In one of the games, they were simply told that they should Perform Maintenance every 20 seconds, and in the other game they received alerts from an agent for Performing Maintenance every20 seconds. We show that when receiving alerts, people tented to Perform more Maintenance, and Perform slightly better (not statistically significant). We suggest that in order to further improve the Performance of the players in the space-ship game, one should also consider when to provide these alerts.

Rafael Bidarra - One of the best experts on this subject based on the ideXlab platform.

  • GALA - MainTrain : A Serious Game on the Complexities of Rail Maintenance
    Lecture Notes in Computer Science, 2019
    Co-Authors: David Alderliesten, Kotryna Valečkaitė, Nestor Z. Salamon, J. Timothy Balint, Rafael Bidarra
    Abstract:

    Commuters who travel by train often feel annoyed due to misunderstanding the causes of delays in train traffic. They oftentimes are unaware of the necessity of Performing Maintenance to stations, tracks, and trains. MainTrain is a serious game developed to teach commuters about rail-Maintenance while simulating the difficulty of keeping passengers happy. It is a fast-paced strategy game with a top-down view in which a player can Perform Maintenance actions on stations, tracks, and trains. By using commuter happiness as a base metric, MainTrain attempts to elicit empathy from players dissatisfied with scheduled Maintenance so that they gain a better appreciation of the need for scheduled Maintenance. This is coupled with the need to schedule Maintenance for several components of a rail network, encumbering a player while teaching them about different aspects of rail Maintenance. To examine the effectiveness of the game, the results of a user study are presented.