The oil and gas industry continues to be a hotbed of innovation, with activity driven by the need for improved productivity and reduced downtime, enhanced safety and long-term sustainability. Digital technologies are playing a transformative role in meeting these objectives. This is characterised by the growing importance of technologies such as artificial intelligence (AI), cloud computing, internet of things, and robotics, within the industry. In the last three years alone, there have been over 534,000 patents filed and granted in the oil & gas industry, according to GlobalData’s report on Artificial Intelligence in Oil & Gas: Predictive maintenance systems.
According to GlobalData’s Technology Foresights, which uses over 256,000 patents to analyse innovation intensity for the oil & gas industry, there are 40+ innovation areas that will shape the future.
Predictive maintenance systems is a key innovation area in artificial intelligence
Predictive maintenance is an approach that relies on data-driven insights to determine the condition of equipment and anticipate its maintenance requirements. AI-based predictive maintenance solutions provide fast and accurate insights on equipment condition. Hence, it is being increasingly adopted in new-build as well as legacy oil and gas infrastructure for early detection of potential faults.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 20+ companies, spanning technology vendors, established oil & gas companies, and up-and-coming start-ups engaged in the development and application of predictive maintenance systems.
Key players in predictive maintenance systems – a disruptive innovation in the oil & gas industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Leaders in the predictive maintenance systems include Siemens , General Electric , ABB , and Honeywell . These leaders supply critical equipment to the oil and gas industry with the equipment vendors including predictive maintenance services together with products to ensure their reliability and operational longevity.
Siemens offers predictive maintenance services for industrial equipment and helps in optimising spare parts inventory. In addition to offering condition monitoring systems for predictive maintenance, Siemens ’ analytics solutions provide informative reports on the status of the spare parts stock, ranges, and inventory supply limits amongst other things.
General Electric offers predictive maintenance technologies that may be application-specific solutions or even embedded in an umbrella solution, such as digital twin technology. Its SmartSignal predictive maintenance software solution helps companies to predict, diagnose, forecast, and prevent equipment failures. Also, its digital twin solution for asset performance management has helped its customers in reducing operational and maintenance costs.
ABB ’s Ability Genix Industrial Analytics and AI Suite helps industrial companies harness AI to minimise operational cost and risks. It also offers predictive maintenance service for its equipment sold to industry players.
Honeywell offers AI-based asset monitoring and predictive analytics products to improve asset management and equipment maintenance. The platform reduces unplanned maintenance requirements and renders refineries safer and more reliable.
To further understand how artificial intelligence is disrupting the oil & gas industry, access GlobalData’s latest thematic research report on AI in Oil & Gas.