Augmented Reality (AR) and the Industrial Internet of Things (IIoT) have proven to be critical in managing modern-day industrial assets and equipment.
Although there are countless IIoT and AR use cases, the use cases leveraged for managing equipment are arguably the most valuable to asset-intensive companies, such as manufacturing. For these industrial companies, the operational status of heavy machinery is fundamental to daily production KPIs, such as overall throughput or overall equipment effectiveness.
Visualize and interact with product design data in an immersive environment
Use cases: Product design, Construction design
Manufacturers are always making efforts to improve their product quality and performance metrics. They’re also trying to expedite new product development and time-to-market. Some new outcome-based business models, such as Product-as-a-Service, add another layer of complexity and importance to the product design process.
IIoT data from smart connected products can close the feedback loop for product designers and engineers. Real-world IIoT performance and usage data fuels product designers with important data-based insights for future iterations and decisions. The same data can be used as an input for simulation modules or generative design software to gain greater design understanding or create entirely different designs.
Augmented reality’s visualize capabilities are leveraged in design use cases like Augmented Design Review. In Augmented Design Review, design changes are superimposed on top of physical prototypes, real-world equipment, or within physical environments. With IIoT added to this product design scenario, we’re now allowed to visually overlay real-world performance data impacting the product in a physical environment, as well as simulate various ‘what-if’ digital twin scenarios.
Empowering product designers with IIoT-enabled performance and usage data allows them to make data-based decisions, while AR contextualizes these parameters in 3D.
Diagnose equipment problems faster with advanced monitoring
Use cases: Asset quality assurance, Operations monitoring, Equipment monitoring and diagnostics, Quality control, and Production line optimization
Heavy-industrial companies focus on asset resiliency and production efficiencies. Overall equipment effectiveness and throughput are major manufacturing metrics that are intertwined with the downtime of assets.
IIoT has unlocked the lucrative data residing in these assets with popular use cases – including asset monitoring, predictive maintenance, and more. Adding AR for equipment monitoring and diagnostics enables the operator to view this real-time IIoT performance data within the 3D environment. Workers can visualize the condition of the entire factory line with x-ray vision into assets and their operational status.
This visibility also applies to monitoring operations and equipment outside of discrete manufacturing. Overlaying live IIoT data through AR into the worker’s field-of-view can further ensure that the equipment on the line is working properly improving yield rates.
Use digital and equipment information to take action in the physical world
Use cases: Assembly work instruction, Asset installation, Maintenance instruction and guidance, Operator instruction (for precision processes and large industrial equipment)
Virtual work instructions are an extremely popular AR use case – due to the fact overlaying step-by-step instructions can help with assembly, maintenance, operating, and service tasks.
Adding IIoT into this use case can further inform the worker on their task or action. Operating equipment’s live IIoT data can update maintenance instructions in the worker’s field-of-view based on priority. For example: ‘go fix this machine instead of the one you are fixing now’.
It could also update instructions on the physical equipment, where looking underneath the equipment’s physical shell to identify which part is malfunctioning and inform repair instructions on the worker’s AR device.
Paper-based manuals and instructions have been a major productivity bottleneck for industrial companies. Replacing them with updateable AR work instructions alleviates these work constraints. Also, overlaying dynamic IIoT data can even further improve efficiencies.
Conclusion
An hour of downtime can cost businesses thousands, which is a main reason why industrial companies will go to great lengths in preventing it. Managing assets and equipment across industrial operations in factories or in-the-field is a crucial factor to this downtime. While driving exponential value for reducing asset downtime on their own, when IIoT and AR are integrated together, these equipment problems can be remediated at record rates and drive unprecedented efficiencies.
