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. So with Cognitive Predictive Maintenance (CPdM) in Oil and Gas Industrial, it can help optimize production, operators might consider adopting advanced analytics, which combines engineering, data science, and computing power to enable businesses to forecast yields or maximize industry assets. Below is the reason why Cognitive Predictive Maintenance (CPdM) is good to apply in Oil and Gas Industrial.
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.
Oil and gas operators 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.
Health and Performance Optimization
Predictive asset analytics software solutions can improve performance by providing early warning notification of equipment issues and potential failures. The software learns an asset’s unique operating profile during all loading, ambient and operational conditions through the advanced modelling process. Predictive analytics also can enable personnel to address subtle variations in equipment behaviour before they become problems that significantly impact operations.
Please feel free to contact E-SPIN for your inquiry and requirement, so we can assist you on the exact requirement in the packaged solutions that you may require for your operation or project needs.