A cost-based failure prioritization approach for selecting maintenance strategies for thermal power plants: a case study context of developing countries

Abstract

The Failure Mode and Effect Analysis (FMEA) employing the Risk Priority Numbers (RPN) have been used extensively for identifying and prioritizing failure modes with a view of mitigating their impact on equipment failure. However, in its traditional form, the prioritization approach through the RPN lacks the objectivity required for robust risk assessment, more so, where maintenance data is available, which could enhance such objectivity. This paper extends a quantitative approach for prioritizing failure modes and component failures in facilities, and more specifically, leverages on maintenance data often recorded in such facilities. To enhance the objectivity of the risk prioritization process, the proposed approach integrates three objective measuresthe cost of failure, failure occurrence rate and percentage downtime effects of equipment failure. The integrated measures are demonstrated as more robust for prioritizing risks as opposed to ordinal indices as the case in the conventional FMEA approach. Using historical maintenance records, a three-step ranking approach is proposed for prioritizing critical failure modes in a thermal power plant where a case study is discussed. Moreover, the study compares the results derived from the prioritization approach with that derived utilizing the conventional RPN method. The comparative study demonstrates the added value of a more objective and quantitative prioritization approach for maintenance decision support. Ultimately, the critical failure modes are evaluated using a decision scheme to allocate appropriate maintenance strategies as the final step of risk assessment (i.e. risk treatment). The proposed approach is viewed as generalizable, intuitive and offering insights to the maintenance practitioners.

A comparative analysis of maintenance strategies and data application in asset performance management for both developed and developing countries

“…Event or failure data are collected and recorded following several downtime-related events like equipment failure, repairs, spare management and other incidental stoppages to the plant (Tambe and Kulkarni, 2016; Wakiru et al , 2019). At higher system abstractions, event data on maintenance planning and spare parts management are collected and stored using maintenance information systems.…”

A framework for now-casting and forecasting in augmented asset management

“…Fault -A fault is defined as a state of an item or system characterized by its inability to perform a required function, excluding the inability during preventive maintenance or other planned actions, or due to lack of external resources (CEN 2010). To improve the functioning of the system, fault diagnosis is performed to monitor the location, and identify the faults within the system (Wakiru et al 2019). The goal for the early fault diagnosis is to get sufficient time for counter measures which include planning of maintenance actions, such as repair, replace, postponing of operations, etc.…”