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Simulating Technology Improvements for Maintenance Excellence (TIME)

Simulating Technology Improvements for Maintenance Excellence (TIME). Researchers: Dr. Manuel D. Rossetti Stephen Farris Josh McGee Brad Hobbs. Objective. To research mechanisms for: The evaluation of automatic data collection system’s benefits and costs within a logistics environment

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Simulating Technology Improvements for Maintenance Excellence (TIME)

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  1. Simulating Technology Improvements for Maintenance Excellence (TIME) Researchers: Dr. Manuel D. Rossetti Stephen Farris Josh McGee Brad Hobbs

  2. Objective • To research mechanisms for: • The evaluation of automatic data collection system’s benefits and costs within a logistics environment • Automatic data collection systems are information systems which utilize computerized data collectors to capture and record data associated with events at or near the spatial occurrence of the event and at or near the actual time of the event. • To provide decision support technologies for the integration of the automatic data collection system with simulation planning mechanisms

  3. Approach • Develop object-oriented simulation framework and primitives that support the modeling of ADC’s within a simulation model of the system • Explore requirements for substitutability • The ability to substitute a simulation of the system for the real system for planning and control purposes. • Investigate (in a logistics context) the simulation of example ADC’s within the framework

  4. Phase I • Enhance the JSL • The Java Simulation Framework • Contains Java classes that are used in the development of simulations including modeling and experimentation • Model Element, Model, Random Variable, Statistic, Control Variable, Response Variable, Event, Queue, etc. • Provide process oriented modeling capabilities for thread-based interaction. This is especially relevant when modeling the “processing” life of an ADC • Documentation

  5. Phase II • Enhance the Object Oriented Spare Parts Supply Chain Simulation Framework to model • Maintenance flight line operations • Conceptualize the ADC example and establish the requirements for testing example • Framework analysis using object-oriented design and analysis techniques (UML, etc) • Documentation Adapted from Faas (2003)

  6. System Operation System Structure Spare parts Indenture 1 Pump To higher echelon Facility Indenture 2 Valve Piston Ware House Repair Indenture 3 Stem Ring Rod MI Hierarchy Depot Echelon 1 Base Base Echelon 2 ME Hierarchy Object Oriented Spare Parts Supply Chain Simulation Framework

  7. Detailed Base/Depot Repair Modeling • Order Receiving Agent • receives order for a facility • Order Sending Agent • creates and sends order for a facility • Shipment Receiving Agent • receives shipment for a facility • Shipment Sending Agent • creates and sends shipment for a facility • End Item Scheduling Agent • Schedules operational cycle for end items

  8. Phase III • Develop testing plan • Development and implementation of ADC object concepts within Java • Conceptualizing, designing, developing, and documenting Java implementation • Testing of simulation code • Report writing and documentation

  9. Project Status • JSL enhancement completed • Literature Review of ADC, Sensor Networks, Java-based simulation, supply chain modeling is currently ongoing • Currently, in the process of determining the best way to model the sensor network especially the spatial/temporal aspects of the ADC

  10. Literature Review • Sensor Networks • Park et al (2001) describes a simulation involving sensor nodes, target nodes, and user nodes as a possible sensor network scenario • Java-based Supply Chain Simulation • Rossetti and Chan (2003) give a framework for an object-oriented supply chain simulation • Health and Usage Monitoring Systems • Larder (2003) describes the benefits monitoring a helicopter’s engine for defects and using the information for maintenance • Autonomic Logistics System • Faas (2003) explores the advantages of using a system that automatically places orders for parts once used, which allows workers to continue on jobs such as repair and maintenance

  11. Sensor Network Model • Using nested zones and allowing them to represent physical space • Giving each of these zones a physical dimension and location • Creating links to allow for passage between zones • Represented by location, orientation, and width • Using sensors with own location, range, and distributions governing type I and type II error • Allowing entities to have tags in order to be tracked through zones

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