Midstream oil and gas companies can’t afford unplanned downtime. Studies have shown unplanned downtime can costs tens of millions of dollars per year in lost productivity and repairs, on top of the physical risks involved when equipment fails. Fortunately, the rise of the Industrial Internet of Things, or IIoT, allows operators to increase their ability to monitor performance, temperature, flow, and other metrics via low cost sensors, and make better maintenance decisions based on collected data.
Predictive Maintenance and its Benefits?
Predictive maintenance uses data, like temperature, vibration, and throughput, collected by sensors, then analyzed for any red flags or abnormal results. This data is then used to forecast when maintenance should be completed to avoid decreased efficiency or equipment failure.
For midstream oil and gas companies, cost control is always a factor. Companies that can better manage operational costs during a downturn are more agile and better prepared to deal with margin pressures. Predictive maintenance can help save on costs, requiring fewer equipment inspections and fewer unnecessary updates.
A proper predictive maintenance program will allow for better decision making with maintenance budgets. Operators can further control costs by allowing cost of efficiency lost in comparison with cost of maintenance to determine maintenance schedules. Due to the remoteness of assets, maintenance costs for particular sites increase or decrease based on logistics. Having a definitive view of drive train efficiency decreases will create an environment for truly informed decision making with regards to maintenance planning.
Roadmap to Predictive Maintenance
There are several steps organizations should take to get started developing a predictive maintenance plan:
- Benchmark your current capabilities-what are you spending on maintenance now and how much downtime are you experiencing?
- Identify opportunities-where can you add sensors to collect actionable data? Are there bottlenecks or hot spots causing issues? Create pilot programs with well-defined metrics to test whether predictive maintenance is improving results.
- Invest in an automated predictive maintenance solution that is scalable, designed from the edge, and is based on a platform that is downtime proof.
Predictive Maintenance Solutions in Oil and Gas
Predictive Maintenance is best run from the Edge – in the process areas beside the pump, compressor, or terminal - not in a far off location, in a control room or cloud where there could be problems with transmission, bandwidth, latency and data integrity.
Stratus Technologies offers an industrial grade platform with built-in redundancy, that is designed especially for the edge. It is a perfect fit for any predictive maintenance solution in the oil and gas industry that requires reliable data collection in mission critical environments.
Summary
For midstream oil and gas companies, predictive maintenance has many advantages over reactive or planned maintenance, including increased equipment life, optimized equipment operations, less equipment downtime, and less staff time wasted. For more insights into how Stratus Edge Computing can help midstream oil and gas companies, visit this link or consult with a Stratus edge computing expert.
