How to Reduce Forced Outages
Forced outages – Cost implications
Most industries follow best practices in Operations and Maintenance. Various RCM techniques are adopted to maintain high reliability of critical equipment. Despite adopting these, many industries experience failure of expensive equipment, often resulting in significant losses.
Typical cost of failure/year
Cost of Forced Outages
Cost of Replacement of Parts
Failure of critical components may have a cascading effect on upstream or downstream systems · Cost due to loss of Generation / Production
Cost due to any associated penalties
Cost due to increase in insurance premiums
Typical cost of insurance is around 1-1.5% of insured value and could usually be of the order of $200-300k USD/year
Cost due to delay in restart (depends on the availability of spares)
Delivery lead time for big equipment like GT, Generator and Transformers, etc.,. is ~12 months. For boilers it is higher.
Safety Concerns
Failure of high energy equipment => Accidents Cost of failure of any critical equipment in power or process industries usually runs into millions of dollars
Some reasons for failures
- Available RCM programs in the market do not look at live data on a continuous basis
- ‘Condition monitoring’ is often limited to rotating equipment
- Original Equipment Manufacturers often limit data analysis to their own equipment
- Setup of dedicated “Reliability and Performance Analysis” centers is too expensive for individual plant owners
- DCS (Distributed Control Systems) are not equipped to understand complex correlations that exist between process variables
- Some industries lack historians that can store and retrieve data for analysis
Anomaly Detection
Our software and solutions have the capability to detect anomalies at their onset and prevent catastrophic failures. We employ hybrid modelling techniques that are comprised of artificial intelligence, statistical methods and thermodynamics analysis for anomaly detection. Types of anomalies that can be detected by our software include:
- Equipment Anomalies
- Process Anomalies
- Sensor Anomalies
- Data Anomalies
