In Hydropower generation company, the focus was on making use of the reliability-centred maintenance (RCM) principles in relation to expert systems in order to optimize maintenance of power generation assets at HPGC station. The researchers realised that in order for CBM to come out clearly, it is critical to do the RCM first. Naturally, the ageing equipment demands a paradigm shift in maintenance strategies in order to guarantee continuity of supply and meet the ever-growing stakeholder requirements. Increase in customer demand has worsened the situation. There is need to improve the overall equipment effectiveness (OEE) from the current 60% to the world class 85%, using the same old equipment in order to retain customer satisfaction.
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Power generation business depends heavily on machinery of high monetary value. Very little study has been done on Reliability Centred Maintenance in the context of developing electricity industry. As a result of this research deficiency, the power generation industry has suffered due to the shortcomings of the traditional maintenance practices of fixed overhauls and breakdown maintenance. This book is going to make use of the Reliability Centred Maintenance (RCM) principles in relation to Expert Systems in order to optimize maintenance of power generation assets at HPGC station. The researchers realised that in order for CBM to come out clearly, it is critical to do the RCM first. Naturally, the ageing equipment demands a paradigm shift in maintenance strategies in order to guarantee continuity of supply and meet the ever growing stakeholder requirements. Increase in customer demand has worsened the situation. There is need to improve the Overall Equipment Effectiveness (OEE) from the current 60% to the world class 85%, using the same old equipment in order to retain customer satisfaction.
Of late, numerous breakdowns together with extended Mean Down Times (MDT) have negatively impacted the company’s competitive performance objectives (CPOs) and the Zimbabwean economy at large. The failure rate stands at about 30% against a world class of 10% while mean down time goes to 2 months a year per machine which can be reduced by half with improved maintenance systems. As such, system failure has caused massive loss of revenue amounting to at least $1m a year as well as catastrophic loss of capital equipment worth over $100 000 a year, posing danger to safety, health and the environment. Constant machine overhauls have not improved equipment reliability significantly. The massive exodus of Engineers has added onto the problems leaving the organisation exposed due to lack of experts and hence the need to adopt a streamlined Artificial Intelligence based reliability maintenance system. The aim of this study is to develop a Reliability Centred Maintenance system based on Expert Systems. This is so as to adopt a maintenance approach which would optimise power generation processes at HDPC. The project objectives are:
- 1.
To apply the concept of Maintenance Free Operating Period (MFOP) reliability metric to determine maintenance intervals as opposed to Mean Time Between Failure (MTBF).
- 2.
To determine and analyse the failure mode and effects of equipment and component failure.
- 3.
To design an online condition monitoring scheme for critical equipment.
- 4.
To design a predictive maintenance system as a component of reliability based maintenance.
The book focuses on the maintenance of power generation assets at HDPC which includes the hydro-turbines, generators and switchgear. One out of six units only is going to be examined and the concepts can be easily duplicated to the other units. Unit 1 is going to be used for the purpose. The current maintenance practices shall be studied and the Expert Reliability Centred Maintenance system shall be applied as an improvement to the current maintenance systems. The project excludes the transmission and distribution network.
Figure 1. Flow diagram of a power plant