Availability-based predictive maintenance scheduling for vibrating-grate biomass boilers

Abstract

This paper proposes an availability-based maintenance scheduling for a vibrating-grate biomass boiler. The main objective is to minimise the maintenance programme cost while maintaining the system availability at a targeted level. A modified failure density function was employed to deliberate the effect of maintenance on the reliability of the components. The constant failure rate of the components which yields constant hazard functions were converted to time-dependent hazard functions by means of Weibull regression analysis. The updated failure parameters were examined by Kolmogorov Smirnov tests and the results showed a good agreement with the primary data. A critical factor named maintenance impact plays an important role in optimised scheduling and determines which components have a higher influence on system availability. Fault tree analysis method was engaged to estimate system availability. The results showed 32% reduction in the number of maintenance requirements with the help of modified predictive maintenance management.

Keywords:

• Biomass boiler availability
• fault tree analysis
• maintenance plan
• Weibull regression analysis
• maintenance impact

Acknowledgments

The authors thank Brais Malouin and Associates (BMA) corporation for financial and technical information support.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was funded by an Engage grant from Natural Science and Engineering Council of Canada (NSERC) & Brais Malouin and Associates (BMA) corporation [Grant Number: RGPIN-2016-06727].

Notes on contributors

Mohammad Hosseini Rahdar

Mohammad Hosseini Rahdar is a third-year PhD student at Concordia University. His doctoral research focuses on analysis of grate-type biomass boiler performance under uncertainty's conditions. He holds a master's degree in Energy Engineering and a bachelor's degree in Mechanical Engineering. He specializes in CFD modeling, maintenance and reliability analysis, energy system analysis, and biofuels.

Fuzhan Nasiri

Fuzhan Nasiri, PhD, is an associate professor at Concordia University. He is a systems engineer with deep interest in investigating the emerging challenges in design and operation of complex (physical) systems (such as facilities, infrastructure, and buildings) and their interactions with and impact on the environment and society from sustainability, resilience, and reliability perspectives. He has adopted an interdisciplinary approach in research that stems from his background in systems modeling and analysis and his research activities in various domains involving industry and public sector.

Bruno Lee

Bruno Lee, PhD, is an assistant professor at Concordia University. He specializes in building energy performance simulation. His current research is interdisciplinary in nature covering areas in building envelopes, HVAC systems, renewable energy systems, and lighting as they are applied to building as a whole. His work focuses on investigating how to better employ different computational simulation techniques to study the performance of the built environment in an integrated manner.