Bright Future for the Early Adopters of Industry 4.0 Maintenance Trends
The oil and gas sector is a complex industry with challenging demands. Along with the fact that professionals and installations are operating in remote and hostile environments, it is becoming more and more expensive and difficult to extract energy. Business owners have been forced to look for opportunities to maximize investments, lower costs and mitigate risk.
The latest digital trends in industrial equipment maintenance allow manufacturers to streamline maintenance. Thanks to condition monitoring data and predictive analytics, failures can be anticipated and maintenance scheduled only when it is needed. Without having a choice to make mistakes related to employees’ safety and environmental accidents, the oil and gas industry (together with power generation and aerospace) was one of the earliest adopters of predictive maintenance. The payback is reduced unscheduled downtime and increased equipment effectiveness, along with automated high-cost and dangerous tasks.
The Industry Challenges or Why Predictive Maintenance Can Really Pay Of in the Oil and Gas sector?
The oil and gas industry is characterized by many challenges but the main ones can be summarized as follow:
Equipment Reliability and Operator’s Safety
A failure or an unplanned downtime of a critical piece of equipment leading for example to spills and leaks can have dramatic impact on the operator and the environment. Thus inspections are often needed on a daily basis which requires more additional equipment and high cost.
An oil and gas project encompasses a huge network of equipment, installations and technical professionals. Very often important events as turnarounds or shutdowns require months of preparations and should be properly organized and communicated among all involved participants.
In order to achieve production-efficiency improvements, most companies turn towards automation. Monitoring the condition of every single piece of equipment to predict shutdowns to prevent catastrophic events have meanwhile become a basic requirement in the oil and gas sector.
An oil and gas operation can produce a huge amount of readings. Turning them into valuable data and creating algorithms might be extremely challenging without the right tools and professionals. A milestone in this process is the deployment of a next-gen CMMS, supporting predictive analytics. This implies the storing, processing and evaluating of real-time and historical sensor data alongside maintenance data generated from industrial equipment. A computerized maintenance management platform as Mobility Work also enables entirely new insights into machine and process operations efficiency.
Advanced predictive maintenance strategies are nothing new to the oil and gas industry. Their establishment has already brought to the sector endless benefits, varying from higher investments to increased production revenue.
A Reliable Predictive Maintenance Approach Is Impossible Without a Next-Gen CMMS
Mobility Work is a productivity enhancing CMMS, combining traditional software features with industry 4.0 induced functionalities. A condition monitoring data on itself cannot really serve a lot if not analyzed in the context of all daily interventions, historical data, spare parts information, past and future inspections and many more. A next-gen CMMS can be directly linked to all equipment sensors to gather the relevant performance parameters. Rotating equipment, centrifugal pumps, gas compressors and other specific equipment require as well a particular way of monitoring including multiple sources and advanced analytic modeling techniques.
Consult Mobility Work Articles on CMMS and Predictive Maintenance:
There are three known predictive maintenance solutions – empirical, physics-based and experience-based. They all function in a similar way by establishing a norm of metrics. If an asset exceeds these metrics, it indicates a possible deterioration. Each of the mentioned predictive maintenance solutions offers a different way how this “model of normality” is built. The empirical approach is based on the assets’ historical data; the experience-based one uses data that has been collected from similar assets and the physics-based solution leans on engineering principles.
Given the fact that each of these solutions has advantages and disadvantages, the best approach will be to combine the three of them in order to maximize the high diagnostic accuracy. Mobility Work can be linked to any of these approaches.
This Is Good but It Can Get Even Better
According to latest researches, only a very small amount of the data gathered by sensors on offshore oil rigs is finally used in important decision-making. The conclusion is that technology to gather and deliver data has successfully spread throughout the industry, but there is still a high demand for tools to process this data and deliver valuable analytics.
A modern CMMS, combined with predictive maintenance routines can definitely improve the current situation and make the sector benefit even more from all sensor data. Mobility Work is easy to use and thus its adoption throughout an organization – fast and efficient. Furthermore, tagging of equipment and a reliable geolocation tool can track machines and tools and support predictive maintenance operations.
The oil and gas industry has been one of the first sectors to deploy predictive maintenance software leading to significant reduction in downtime and elimination of breakdowns. Companies took the great opportunity to adopt predictive maintenance and benefit today from increased efficiency and reduced operational costs. This makes the challenging time for the industry easier to cope with and mitigate financial risk.
As a modern, industry 4.0 inspired maintenance management platform Mobility Work can support any oil and gas company to establish and maintain a valuable predictive maintenance program. The solution is very flexible and can be easily tailored to the specific needs of the sector. A high-quality, next-gen CMMS is at the core of a successful predictive maintenance strategy, ensuring safety and best performance outcome.