The oil and gas industry continues to be a hotbed of innovation, with activity driven by the need for more efficient production, improved safety and long-term sustainability. Digital technologies are playing a transformative role in meeting these objectives and this is characterised by the growing importance of technologies such as artificial intelligence (AI), cloud computing, internet of things, and robotics. 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 Robotics in Oil & Gas: Predictive maintenance systems.

However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.

Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have. 

150+ innovations will shape the oil & gas industry

According to GlobalData’s Technology Foresights, which plots the S-curve for the oil & gas industry using innovation intensity models built on over 256,000 patents, there are 40+ innovation areas that will shape the future of the industry.

Within the emerging innovation stage, robotic drilling machines is a disruptive technology that is in the early stages of application and should be tracked closely. Automated drilling tools, predictive maintenance systems, and force feedback robots are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas is jig conveyors, which is now well established in the industry.

Innovation S-curve for robotics in the oil & gas industry

Predictive maintenance systems is a key innovation area in robotics

Predictive maintenance is an important part of asset management strategies that are employed in every industry to help maximise the operational life of equipment and infrastructure. It uses an innovative data-driven approach to assess the state of the field equipment or infrastructure and provides a detailed picture of its expected operating life. This enables decision-makers to schedule maintenance activities without affecting normal functioning. These insights can also be utilised to determine whether any machinery or infrastructure requires a substantial overhaul.

Robotics technology has further improved the effectiveness of predictive maintenance systems by offering superior mobility during data collection. Robotic crawlers, both autonomous as well as remote-operated, can be used to detect faults even in constrained areas that may be otherwise inaccessible to humans. These devices can survey almost every corner of enclosed spaces, such as storage tanks to identify early signs of corrosion, cracks, and other defects.

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 10+ 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’.

Patent volumes related to predictive maintenance systems

Company Total patents (2010 - 2021) Premium intelligence on the world's largest companies
Fanuc 394 Unlock company profile
Siemens 104 Unlock company profile
Kawasaki Heavy Industries 83 Unlock company profile
ABB 35 Unlock company profile
Rockwell Automation 32 Unlock company profile
General Electric 14 Unlock company profile
Okuma 11 Unlock company profile
Lincoln Electric Holdings 10 Unlock company profile
JANOME SEWING MACHINE 9 Unlock company profile
Fuji 8 Unlock company profile
Klingelnberg 8 Unlock company profile
Nidec 6 Unlock company profile
DMG Mori Seiki 6 Unlock company profile
Bobst Group 6 Unlock company profile
Makino Milling Machine 5 Unlock company profile
Sumitomo Electric Industries 5 Unlock company profile

Source: GlobalData Patent Analytics

Leading robotics providers in predictive maintenance systems include ABB, General Electric, and Siemens. They offer a wide range of critical equipment including automated robotic systems to improve efficiency and operational safety at industrial facilities. These robots are integrated with predictive maintenance systems to ensure reliable performance and timely repairs. This integrated product offering ensures longer operational life and reduced downtimes to customers.

ABB supplies robotic equipment to improve performance of routine oil and gas operations. It also offers predictive maintenance service for its robotic fleet deployed with the respective industrial users.

Siemens offers retrofit and modernisation services to improve plant lifecycle as well as to reduce maintenance costs. Retrofitting older equipment with robotic elements helps eliminate the need for manual data collection for predictive maintenance systems and other use cases.

To further understand how robotics is disrupting the oil & gas industry, access GlobalData’s latest thematic research report on Robotics in Oil & Gas (2021).

GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.