Reliability and Availability Analysis of Port Equipment

PROJECT PI

Dr. Yisha Xiang, Assistant Professor, Department of Industrial Engineering

SHORT DESCRIPTION

In this project funded by Center for Advances in Port Management at Lamar University, innovative preventive maintenance models are developed to address the challenges caused by port equipment unavailability due to busy operational schedules.

FULL DESCRIPTION

Port equipment operation and maintenance are seen by the World Bank and the United  Nations as one of the primary issues facing in port management. Conventional preventive maintenance models often assume that equipment is always available for maintenance activities. However, port equipment may not be available for scheduled maintenance due to busy operational schedules. Forced maintenance shut-down might incur extra costs which cannot be offset by the benefits from preventively maintaining the equipment. In this project, we develop innovative preventive maintenance models to address the challenges caused by equipment unavailability. Maintenance models with possible rescheduling are developed for both time-based and condition-based maintenance policies, and the objective is minimizing the long-run cost rate of all maintenance activities which include maintenance rescheduling, forced shut-down, and preventive and corrective maintenance.  To assess potential benefits from the proposed maintenance models, the optimal policies with consideration of equipment unavailability are compared with the policies that ignore such unavailability. 

FUNDING

This project was funded by the Center for Advances in Port Management (CAPM) at Lamar University

PUBLICATIONS

  • Alaswad, S., and Xiang, Y. (2017), A review on condition-based maintenance optimization models for stochastically deteriorating system. Reliability Engineering & System Safety, 157, 54-63.
  • Xiang, Y., Coit, D. W., and Zhu, Z. (2016), A Multi-objective Joint Burn-in and Imperfect CBM Model for Degradation-based Heterogeneous Populations, Quality and Reliability Engineering International, 32(8), 2739-2750.