Critical equipment plays an essential role in industry because of its lack of redundancy. Failure of critical equipment results in a major economic burden that will affect the profit of the enterprise. Lack of redundancy for critical equipment occurs because of the high cost of the equipment usually combined with its high reliability.
When we are analyzing the reliability of such equipment, as a result, there are few opportunities to crash a few pieces of equipment to actually verify component life.
Reliability is the probability that an item can perform its intended function for a specified interval of time under stated conditions and achieve low long-term cost of ownership for the system considering cost alternatives. From the economical standpoint, the overriding reliability issue is cost, particularly the cost of unreliability of existing equipment caused by failures.
Classical questions about reliability are:
· How long will the equipment function before failure occurs?
· What are the chances that a failure will occur in a specified interval for turnaround?
· What is the best turnaround interval?
· What is the inherent reliability of the equipment?
· What are the risks of delaying repair/replacements?
· What is the cost of unreliability?
· …
We will try to answer these questions for a critical reciprocating compressor, which has been in service for only 4 years and has undergone only few failures.
Professionals in all industries are faced with the problems of performing maintenance actions and optimizing maintenance planning for their repairable systems. Constructing stochastic models of their repairable systems and using these models to optimize maintenance strategies require a basic understanding of several key reliability and maintainability concepts and a mathematical modeling approach.
Therefore, our objective is to present fundamental concepts and modeling approaches in the case of a critical reciprocating compressor. We developed a stochastic model not to simulate a reciprocating compressor with a complete set of components but mainly to optimize the overhaul period taking into account the main failure modes only.
How to lower the cost? How to reduce or remove maintenance actions that are not strictly necessary? How to improve the long-term profitability of ageing plants with the strict respect of Health-Safety-Environment HSE requirements?
A reciprocating compressor is a complex machine that cannot be described with a single reliability function. A compressor has several failure modes. Each failure mode is assumed to have its own Weibull cumulative distribution function. The compressor is then a system with several Weibull laws in series. We will extend the usual procedure for minimizing the expected total cost to a group of components. Different components may have different preventive maintenance “needs”, but optimizing preventive maintenance at the component level may be sub-optimal at the system level.
We will study also the reliability importance indices that are valuable in establishing direction and prioritization of actions related to a reliability improvement plan, i.e. which component should be improved to increase the overall lifetime and thus reduce the system costs.
When considering a large system with many items that are maintained or replaced preventively, it is advantageous to schedule the preventive maintenance in a block such that the system downtime is kept as small as possible. This requires that the resources are available so that the maintenance of components can be performed simultaneously or according to a well-defined sequence.
The result of the stochastic model optimization came as a surprise. We thought to find a new mean-time-between-failure MTBF, larger than the actual overhaul period. Actually, the model showed that there is no economical interest to schedule a systematic preventive maintenance for this reciprocating compressor. Nevertheless, we cannot wait for a failure (and the associated corrective maintenance) because the loss-of-production cost is too high and this compressor has no spare. Preventive maintenance is not the optimum strategy, but predictive maintenance is.
But what means predictive maintenance? It is a maintenance policy to regularly inspect equipment to detect incipient changes or deterioration in its mechanical or electrical condition and performance. The idea behind this is to perform corrective maintenance only when needed, before the occurrence of failure. We need to find how to detect performance deterioration of the compressor with a couple of weeks or days notice before failure. So it is possible to schedule a right maintenance activity at the optimum moment.
To summarize, the main findings of this thesis are
· a new method to estimate the shape factor of a Weibull distribution function,
· a stochastic model demonstrating that we have to move from systematic preventive maintenance to predictive maintenance,
· a low cost system based on thermodynamic approach to monitor a reciprocating compressor,
· an automatic detection of performance deterioration.
| Identifer | oai:union.ndltd.org:BICfB/oai:ulb.ac.be:ETDULB:ULBetd-12142006-215740 |
| Date | 21 December 2006 |
| Creators | Vansnick, Michel P D G |
| Contributors | Mme Mercier, Sophie, Mr. Dehombreux, Pierre, Mr. D'ans, Gérard, Mr. Labeau, Pierre-Etienne, Mr Leduc, B |
| Publisher | Universite Libre de Bruxelles |
| Source Sets | Bibliothèque interuniversitaire de la Communauté française de Belgique |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://theses.ulb.ac.be/ETD-db/collection/available/ULBetd-12142006-215740/ |
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