Companies Merge the Digital and Physical to Transform Service


Jet-TurbineFor sellers of manufactured goods, the Internet of Things enables performance and customization at a never-before-possible level. Seeing how clients use your items through IoT connectivity also means that makers are now ‘advisers’ on how best to get the most from their goods. 

At GE Aviation, for instance, an hour is not just 60 minutes. It’s more complicated.

That same hour has to be measured along with heat, humidity, dust, altitude and other factors. Airplane engines use a “time-on-wing” unit to measure how many flight hours are logged for maintenance purposes. And these days, GE Aviation is accounting for all sorts of user variables while also proposing ways to save the end users time and money. They share the end goal – more time in profitable operation.

Data is key to that relationship and manufacturers succeed by helping figure out how to make an asset more productive – even if they don’t own the asset.

In aviation, that meant understanding conditions like ways that a hot, dusty hour of flight in Dubai affected jet engines differently than an hour elsewhere.  GE suggested operational improvements to help its airline customers. One solution was a water-wash of engines in Dubai to remove fine-grain dust and prevent damage.

Knowing each client’s need for service, product and preventive care is critical. That puts many companies on the road to an “Outcome-based service.” For instance, Trane’s Kevin Bollom told LiveWorx 2016 that its customer focus is part of the company DNA. Trane has been using IoT to help clients remotely dashboard their power usage, heat and cool facilities and limit service calls.

“For almost a decade we’ve been using IoT to bring data to deliver the best solution possible in how they operate their building,” Bollom told the LiveWorx audience. “It still comes down to a person talking to another person, technology can help you do that in a new way.”

An emerging best practice requires creating a ‘digital twin’ of your business – a forecast or model of the products and services. That prediction gets compared to actual operation, often in real-time. During a LiveWorx panel, Daniel Kingham explained how modeled behavior of repairs at Elekta AB, helped managers understand a complex issue set.

From its headquarters in Sweden, Elekta builds machines that deliver critical cancer therapy in 6,000 locations across 150 countries. When executives saw repair rates were rising, they examined records and purchasing trends and learned that because of the distance technicians had to travel, some were ordering and stockpiling parts ahead of schedule, costing significant amounts. 

Elekta saw its field workforce differently by using a remote IoT solution and boosted uptime by 20%, while increasing throughput. Performance data collected from equipment can also be used for future engineering design and improvements.

Changing habits among the field service workers required a philosophy shift and sharing knowledge to smooth out inventory management. “It’s not sales, new venture or something sexy – that’s part of the challenge,” he said. “Any downtime has an impact on patients.”

But the model helps manage the business, and compares predictive analytics to the actual results in the field to deliver crucial support for the diagnosis and treatment machines that 140,000 patients rely on. That delivers benefits for front line workers and data that supports back office analytics.

A U.S. Department of Energy study forecasts a 25 percent reduction in asset maintenance costs and 35 percent reduction in downtime as proactive IoT systems replace the old ‘fix it when you see it’s broken’ reactive model, according to PTC.

Being pro-active matters. GE Aviation contacted airline clients such as Alitalia with recommendations for flight paths that would minimize fuel consumption, using data gathered remotely from engines.

Services, consulting, and contract maintenance are revenue drivers for companies – not just one-time sales.  Data is powering models that check design assumptions during planning stages and compare them to repairs, once goods are in customer use.

A ‘cradle to grave’ model tracks design, assembly, sales, usage and performance, comparing each to initial forecasts.

These new models do more than deliver reliability, experts agree. The IoT helps ensure outcomes – on-time flights, less downtime and data that powers the enterprise.