This post originally appeared on ARC Advisory Group's Industrial IoT/Industrie 4.0 Viewpoints blog.
More than 2,700 people descended upon San Francisco in November for GE Minds + Machines (GEMM). As always, GEMM provides a great opportunity each year to see how “digital” the company looks. Since the early 2000s, the company has moved to converge many IT business concepts with its OT and big iron solutions in anticipation of evolving into a digital business. You can revisit Twitter conversation about the event by visiting #GEMM16 or digging into highlights.
Living “in-between” the transition from physical and digital
The always interesting GE Vice Chair Beth Comstock delivered one of the event’s more memorable perspectives on digital transformation. By citing some simple data points around mobile phones, movies, and walking she disabused the audience that digital transformation is optional or can be kicked down the road. She pointed to disruption that has occurred in music, shopping, and media, the latter she lived through. It’s her belief that a connected world will have an even greater impact on industrial businesses.
She pointed out that omnipresent drivers of change—human behavior and geopolitics—are now being accelerated by components of a digital world—connectivity, ubiquitous access to information at speed, and compute power.
It’s created an “in-between” world that is transitioning away from physical objects toward a digital environment. This emerging world is the genesis of concepts such as the digital twin. Ms. Comstock stated that though this transition isn’t fully realized, businesses need to deal with its implications now. Or, as she nicely summed it up:
“Get used to living in the in-between. The old is going away, and the new has not yet fully emerged. It’s uncomfortable and it’s chaotic, but it’s happening in pretty much every industry right now.”
Proactive asset performance management
Ms. Comstock’s words provide context for the thinking behind many of the solutions at GE Minds + Machines. A multitude of demos pushed to extend beyond the physical value provided by assets by emphasizing digital elements coupled to them, mainly in the form of digital twin concepts and Predix-enabled analytics. A few asset performance management (APM) examples included:
- Drone-based inspection on linear assets for utilities. Using an embedded Predix system, the drone collected edge data, which was fed back to the cloud for predictive analysis and maintenance.
- As part of their APM suite, OEM-agnostic renewable energy analytics for wind farms. This included the use of machine learning to detect anomalies. Like many other vendors in the OT space, GE sees the necessity of supporting a diverse ecosystem of suppliers and providers
- Predictive corrosion management for oil and gas. This application relied on sensors to provide continuous digital inspection of an asset. Data can then be fed to the cloud for predictive analysis.
Perspective on acquisitions
It seems nearly impossible these days to get through an event involving GE Digital without some type of acquisition news by the company. GEMM 2016 was no different, as the company announced a number of acquisitions.
- ServiceMax enables GE to add analytics and insights into the company’s logistics, workforce optimization and deployment models.
- Meridium broadens the predictive maintenance solutions that GE can offer. The marriage takes aim at expanding the company’s APM portfolio by combining analytics with reliability-centered maintenance.
- BitStew and Wise.io build out machine learning and predictive analytics capabilities for industrial applications. Bit Stew delivers expertise in data ingestion of both structured and unstructured varieties. As well, the company had made significant inroads in developing tools and sandbox environments for use by both data scientists and subject matter experts.
Deeper integration of knowledge is key
A crucial advancement for harnessing the value of digital transformation is further underpinning predictive solutions with knowledge and automating the delivery of it, when appropriate. GE should continue to push forward on this front.
Solutions that predict a problem and then deliver the knowledge necessary to solve it (or automate that process), are prescriptive. This step is especially crucial for optimizing APM. It moves prediction beyond alerts, notifications, or basic integration into work order system. Instead, it enables companies to be as proactive as possible, implementing optimized, highly-efficient decision making across planning and management of assets and operational processes.