The oil and gas industry, along with the automotive and aerospace sectors, was one of the earliest adopters of predictive maintenance routines. Challenged by various safety issues the sector has always been in search of highly efficient solutions to improve performance.
Today, the use of sensors and data gathering routines are widely spread throughout the sector in drilling, production and rig maintenance. And even though the oil and gas industry is reaping the benefits of predictive maintenance, there is still a high demand for processing and analytics tools, since a huge amount of the collected data is not used and not involved in important decision-making.
Today’s economic landscape offers a good moment for the industry to look towards applications enabled by the Industrial Internet of Things (IIoT) and automation in order to limit downtime and minimise safety and environmental risks. It might seem inexpedient to invest and experiment in times like this, but doing so can secure the feature.
Predictive analytics are nothing new to the oil and gas sector. But what is rather challenging is the adoption of a next-gen and versatile computerised maintenance management software (CMMS) that can guide a company through the laborious transition from reactive to proactive and to predictive maintenance. Data collection retains a critical role in the predictive maintenance process but data processing is the step that really empowers professionals to act and keep equipment running safely and reliably for as long as possible.
Another big challenge is to make this data immediately available to several departments at the same time to speed up critical field decisions. An industry 4.0 CMMS should enable the data to “free-flow” internally and ensure that all the company’s key players are properly involved. Engineers and data scientists should be able to communicate via a solution that can gather and process their valuable knowledge.
Smart maintenance implies connected maintenance revealing real-time equipment health and performance insights on critical offshore assets and ensuring that all machines are operating as expected. Only predictive maintenance can provide data based on continuous performance monitoring and establish advanced pattern recognition to anticipate failures for highly complex and critical assets.
The shift to predictive maintenance helps organisations improve, in particular, drilling operations by optimising asset reliability and availability and thus this maximises economic return.
Data capture
Automating maintenance can undoubtedly improve production efficiency. Geolocation tools, equipment tagging, sensors data, news feed and real -time information exchange are some of the essential steps enabling equipment condition monitoring. However, collecting data is not the problem. The challenge comes when companies decide to shift this data to where operational and business decisions are made.
A successful automated support requires a quality data input captured by automated hardware sensors and engineers and a next-gen CMMS to store, manage and analyse this information and issue predictive algorithms, which should be read by professionals and applied on a production level. The good news is that some of the current computerised maintenance management systems are extremely user friendly and don’t require additional training in order to make managers and staff collaborate and work with the latest applications.
Besides the obvious impact of automation and predictive maintenance on an asset’s economic life, revenues and equipment reliability, there is one more crucial improvement that is worth mentioning. Internal communication can benefit enormously from automation and this is essential for the nature of the oil and gas industry, including continuous and complicated communication between clients, technicians, providers and managers that are often far away from each other.
Automated maintenance communication allows employees to assign and monitor tasks, which significantly reduces the emails exchanged on follow-ups and speeds up and streamlines the entire process. The best thing is that this information is available to anyone at any time of the day on any type of smart device. Loss of information, confusion and errors are eliminated and targets are clear.
Automation optimises production efficiency by maximising asset integrity through streamlined maintenance cycles and predictive algorithms to finally improve oil throughput.
Next-gen CMMS
Not every CMMS in the market can support the latest digital trends. Many available solutions are difficult to deploy, require additional training and need a lot of time to be properly adopted by staff which makes workers very reluctant to work on them.
A modern CMMS is there to firstly ease and improve daily routines by facilitating team communication and saving time. User-friendliness is a key feature. This is a solution that is very versatile and can easily adapt to the growing and changing needs of an organisation.
A next-generation CMMS is an industry 4.0 induced product that can speed up critical decision-making (of crucial importance for the oil and gas sector) through properly stored, processed and managed real-time and historical sensor data.
A quality product should be able to analyse sensors data in the context of other maintenance data gathered from industrial equipment, such as for oil rigs. And one of the most important features for the oil and gas industry is the ability of a CMMS to perform remote equipment monitoring and send alerts and warnings to the team.
A next-gen CMMS can provide oil and gas companies with predictive analytics in real time based on large amounts of equipment monitoring data. One of the biggest obstacles for the oil and gas industry, for example, is old pipelines, which are difficult and expensive to run and maintain. But modern maintenance approaches can help the sector to improve and secure performance by shifting to smarter and safer pipeline maintenance.
The bottom line is the deployment of an industry 4.0 CMMS in the context of predictive maintenance captures massive amounts of data in a cost-effective way; centralises and analyses all variable inputs; generates automatic alerts; eliminates equipment defects and, crucially, minimises health, safety and environmental incidents.
Companies that have turned towards automation and started implementing big data, sensors and analytics in their maintenance process will be able to overcome industry’s challenges.
Oil and gas companies can easily unlock the value of automation and improve efficiency. Most of the organisations have already chosen the right path. The only thing that remains is to find and adopt the right solution to leverage data in order to mitigate risks. Smarter equipment creating tonnes of data is useful only when employees know and fully understand when to act in order to prevent a possible failure.
