Manufacturing Platforms Underpinning Digital Twin Introductions

One of world’s largest metal valve and pipe fitting manufacturing companies implemented IIoT-enabled valves, using an Industrial IoT platform with AR to sense and transmit data about the matter that passes through them as well as their environmental conditions. The platform also tracks various environmental conditions such a temperature, pressure, vibration, humidity, and acoustics. Now, using a combination of machine learning, AR, edge computing, and the cloud, the connected Industrial IoT valves provide their customers with accurate and cost-effective measurement and monitoring capabilities for real-time alerting and predictive maintenance.

These kinds of advances fundamentally change the order of business for companies that employ the technologies. This insight highlights a sample of use cases that leverage a combination of solutions to deliver value greater than the sum of their parts.

Patti Engineering, a CSIA certified control systems integrator offering expert engineering and software development, uses Siemens digital twin solution integrating MindSphere with Tecnomatix Plant Simulation to optimize a machining line at an US car manufacturer. The solution allowed Patti to virtually remodel the existing production line, collect and integrate production data, and derive, as well as verify a new process set-up avoiding production blocks. This increased throughput resulted in about US$1 million annual incremental revenues for the auto maker.

Konecranes, a leader in the lifting business, improves the designs of its cranes by feeding field data via IoT back into its engineering and simulation models. Moving from hypothesis-driven to data-driven design practices allows the engineers to design equipment to real operating requirements and prevents over- or under-engineering. By using an integrated digital twin, they see major potential in speeding up the product development process, reducing prototypes, increasing traceability, and thus improving quality and reducing development cost.

Navantia, a military and civil ship building company, uses MindSphere and Simcenter to combine IoT and operational information along with simulation model of the vessel to deliver multi-fidelity digital twins for optimal systems performance. Various environmental and operational conditions are accounted for during simulation to ensure that the vessel performs efficiently and optimally.

Most manufacturers fall somewhere in the middle of ABI Research’s five-step digital maturity curve, but the general posture toward IIoT projects is starting to mature. Many projects still get started at the plant level and especially if the project is part of a larger change management or modernization initiative (where a company would start with one location (land) then roll out to others (expand)). The difference today is that for larger organizations with a distributed footprint, the opportunities to standardize are becoming an executive decision/mandate, rather than something tactical.

One example is standardizing on parts of the technology stack that are commoditized, like machine connectivity/protocol translation. If technology gaps persist, those gaps would be filled on an ad hoc basis. If the same project were initiated, ideated, and executed on a plant-by-plant basis, there would be a number of unintended consequences, including a messy ecosystem stymied by unwanted vendor lock-in.

Areas such as machine connectivity/protocol translation were a clear competitive advantage for companies like PTC (Kepware), Litmus Automation, and Telit (deviceWISE) several years ago. Today, these companies have expanded their suite of capabilities to encompass metrics like OEE in addition to dealing with a broader constituency of stakeholders. At the same time, industrial automation giants including ABB, Emerson, Rockwell Automation, and Siemens have made considerable strides jockeying for position in areas that help stand up more complete digital threads. For ABB and Emerson, it’s additional functionality for Ability and Plantweb in terms of robotics and AR; for Rockwell Automation, it’s a partnership with PTC, as well as innovation at the edge; and for Siemens it’s bringing simulation and cloud to the IIoT arena for more thorough linkages throughout the manufacturing process, from design through manufacturing and after sales service and support. For more on these developments, market growth, and what’s next, see ABI Research’s research on digital twins (AN-5478) and forthcoming IIoT platforms competitive ranking.