Industrial Inspection Robotics, Global, 2024–2029

The Impact of the Top 3 Strategic Imperatives on the Industrial Inspection Robotics Industry

Disruptive Technologies

• WHY: The growing influence of Industry 4.0 and automation has led industrial customers to adopt advanced technologies.
• WHY: Artificial intelligence (AI) is revolutionizing robotics. AI enables robots to make real-time decisions with minimal human intervention.
• WHY: Navigation technologies and advanced sensor fusion pave the way for an autonomous and mobile future.
• FROST PERSPECTIVE: Automated inspections will see a steady increase over the next 5 years. Industries will gradually move away from manual inspections. The cost of health, safety, and environmental (HSE) compliance and liabilities associated with non-compliance will drive this change.
• FROST PERSPECTIVE: Asset management in critical applications across these industries will augment customer interest in AI-based data analysis and predictive maintenance.

Industry Convergence

• WHY: Process industries require periodic inspections to avoid costly disruptions. These inspections are characterized by complex structures, hazardous environments, and inaccessible locations.
• WHY: Maintenance of assets in these industries requires a thorough understanding of the process. Furthermore, regulatory compliance remains key to successful implementation.
• FROST PERSPECTIVE: Cross-industry partnerships will continue to grow over the next 3–5 years, and collaboration with universities will also continue.
• FROST PERSPECTIVE: Robotic companies partner with customers, technology companies, AI companies, and other robotic companies.
• FROST PERSPECTIVE: Industrial customers prefer solutions that are easy to use while also delivering actionable insights.

Innovative Business Models

• WHY: Subscription, rental, or lease models are preferred to avoid high initial investments. Growing interest in predictive maintenance will drive demand for data analytics-based services.
• FROST PERSPECTIVE: Robotics-as-a-service (RaaS) will continue to be a key model for reducing the burden on upfront costs.
• FROST PERSPECTIVE: Demand for data analytics-based services and scalability will continue to fuel interest in cloud-based remote inspections.
• FROST PERSPECTIVE: Vendors will offer AI-based data and integration services.

Growth Drivers

Ensuring workplace safety across industries:

Accessing hazardous/inaccessible environments and navigating confined spaces are typical of industrial inspections. Manual inspections in such locations pose a high risk for workers. Growing emphasis on safety is paving the way for robotic automation of inspection processes. Moreover, the emergence of quadcopters and tracked robots is expanding inspection possibilities in such locations.

Reactive to predictive maintenance driving robot adoption:

Aging and distributed infrastructure requires frequent inspections to evade unplanned and expensive disruptions. Predictive maintenance algorithms leverage data captured by robots using onboard sensors, enabling enhanced decision-making. A shortage of skilled inspectors and an emphasis on sustainability will augment interest in predictive maintenance.

Technology advancements fueling the adoption of robots in industrial inspections:

AI and machine learning (ML) are enhancing the capabilities of vision technologies—such as light detection and ranging (LiDAR) and thermal sensors—as well as navigation systems, including simultaneous localization and mapping (SLAM) and global positioning systems (GPS). Furthermore, the use of 5G networks across industries helps reduce latency-related issues.

Depleting volumes of quality inspectors shifting focus to robots:

As manual industrial inspections are subjective and prone to error, customers are inclined to adopt robots to ensure uniformity and standardized outcomes. In addition, robotic deployment allows for more frequent inspections and the potential to reduce both cost and time.

Growth Restraints

Resistance to change remaining a key issue to robotic automation: Employee perception that robots will replace their jobs continues to be a key damper to adoption. In addition, there is employee apprehension toward learning new technologies.

Integration of robotics with legacy systems and processes hindering adoption: Compatibility with existing systems for seamless deployment remains a concern for the adoption of robots in these industries. Moreover, changes from the status quo require employee training, adding to the overall complexity.

High upfront investment deterring the adoption of robots, especially for small- and medium-sized enterprises (SMEs): Implementing a robotic system with the necessary software and accessories for automating processes requires significant upfront investment, often stretching the financial capacity of budget-constrained SMEs. Although the long-term benefits outweigh these costs, the initial investment remains a barrier to adoption.