In the age of digital transformation, industrial organizations are tasked with moving faster than ever to better serve their customers. Yet, in many cases, it’s easier said than done.
Digital transformation requires a fundamental shift in how companies do business – and many organizations have entrenched systems and processes that are challenging to rework and reimagine.
Howden, a 150-year-old business that provides global engineering solutions for industrial air and gas handling, is one company that has embraced change and is using digital technologies to achieve customer-centricity.
Howden faced two common challenges in the industrial sphere – a reliance on paper-based documentation and an increasingly complex product and service model. Think about this: 78% of manufacturers leverage outdated and ineffective paper documents, diminishing standardization and quality.
But first, organizationally, Howden committed to a culture change with its Data-Driven Advantage (DDA) program, which revolves around its customers’ lifecycle with its products. The digital backbone of this program begins with digitizing its paper-based documentation. Though this data unification process and development of a digital thread internally, Howden is creating customer-facing digital twins to deliver the right information at the right time through augmented reality.
“DDA includes monitoring deployed machines and creating augmented reality experiences to improve customer service, deliver effective training, and reduce downtime. As Howden continues their transformation journey, PTC looks forward to maintaining this close relationship,” says Matt Sheridan, Senior Director of Field Execution at PTC, whose team has worked closely with Howden to execute on their DDA strategy.
With PTC as its partner, Howden is using emerging technologies, including industrial IoT and augmented reality, to demonstrate the potential in immersive experiences. Howden’s goal is to use digital twin technology to reduce business risk for their customers by improving uptime of deployed products. Why? Unplanned downtime in mission critical applications costs companies millions.
Check out this demonstration:
This demonstration, which was initially unveiled at Hannover Messe 2019, features one of Howden’s diaphragm compressors. It was logistically challenging to transport the 10-foot machines for an event – and far less immersive than an augmented reality experience. The AR demo seamlessly lays out the different functions and use cases relevant to a worker interacting with the machine in the real world.
Customer-facing digital twins are a key element to Howden’s connected field maintenance program, Uptime. This service offering uses digital twins with underlying technologies (ThingWorx, Vuforia, etc.) to provide real-time performance data of deployed assets.
Predicting equipment performance and resolving failures in this scenario has been traditionally challenging and are a casualty of ‘break-fix’ maintenance models. To truly implement a ‘product-as-a-service’ business model, improve customer satisfaction, and solve product complexity issues, Howden is equipping its technicians with augmented reality solutions. Field engineers are now able to access step-by-step service instructions on a specific asset almost immediately. The results have been a drastic improvement in first-time-fix-rates and mean-time-to-repair.
Howden is also resolving issues for its customers faster through remote service. With IIoT built-in to their globally dispersed products, technicians or engineers are able to remotely troubleshoot, patch, or update software without physically visiting the site. This IIoT data can also feed into predictive and simulation models to further forecast failures for service organizations.
-Maria Wilson, Global Leader of Data Driven Advantage
The two key intertwined components of a digital twin are its digital definition data and physical experience. Definition data could include CAD, PLM, and other data that includes the unique asset characteristics and configurations, while physical experience usually is IIoT and real-world telemetry data captured through increasingly widespread sensors. Both sides need to be top of mind to create a full-fledged digital twin implementation that drives maximum business value to the organization.
Howden recognized the importance of definition data but hit a snag: They had many legacy assets in operation where the CAD didn’t exist or was inaccessible/in paper-form.
To subjugate this data bottleneck, Howden created a ‘theoretical data set’ as a performance baseline of its deployed assets, which included 150 years of product design data. The OEM can use this optimal state asset health baseline to measure against real-world IoT data to more accurately predict failures.
Similarly, on the physical experience side, there were some sensor inputs inaccessible yet critical to predictive maintenance models. Howden formed ‘virtual sensors’ -- essentially aggregated sensor inputs with engineering calculations – to provide real-time telemetry data for further predicting failures. For real-time simulation modules, including structural and thermal analysis, this data input is critical to inform predictions.
This comprehensive digital twin provides the framework to build on innovative use cases (predictive service) and adoption of cutting edge-technologies (artificial intelligence). This could include using deep learning in computer vision on AR to recognize Howden deployed equipment without serial numbers or predictive maintenance models using machine learning to precisely predict when a machine will fail.
Howden and similar forward-thinking industrial companies will increasingly look to build out digital twin strategies to drive near-term outcomes, quickly adapt to changing and new markets, and create a foundation to drive transformative change internally and optimize the value delivered to customers.