Extend connectivity, extend machine lifetime
September 16, 2016
While interest in the Industrial Internet of Things (IIoT) continues to rise, the concept remains very difficult for many to get their arms around. Th...
While interest in the Industrial Internet of Things (IIoT) continues to rise, the concept remains very difficult for many to get their arms around. The source of confusion is the various definitions, business processes, value chain, and evolving business models. Manufacturing, however, holds some of the most exciting developments in the Internet of Things (IoT) and most economic benefit in terms of cost savings, new revenue streams, and efficiencies. The near-term focus should be broader visibility of critical machine health through connectivity and reporting.
Bruce Sinclair conducted a great interview with Tanja Rueckert of SAP in episode 64 of The IoT Inc Business Show podcast, “IIoT Manufacturing From the Shop Floor to the Top Floor,” which emphasized just that. Rueckert explained that an IoT enabled solution in connected manufacturing includes connectivity, intelligence, pattern analysis, and predictability. Predictive maintenance should be seen as predictive algorithms that extend the life of the machine, akin to a doctor-patient relationship and lifetime extension. In assessing a patient, a doctor has to maintain a holistic view of health just as one would with IIoT. The true value will lie in an integrated end-to-end organization and each connected component is important and has an incremental IoT value.
IIoT, or connected manufacturing, is literally connecting Operational Technology (OT) and Informational Technology (IT), meaning production and core business processes have end-to-end connectivity, or what is known as “visibility” throughout. To have a truly integrated value chain, Rueckert also emphasized the importance of implementing machine learning algorithms and mapping back to core ERP. Mass customization or individualized products with speed of production and delivery through automation and the integrated manufacturing system is another opportunity for differentiation.
The discussion verified my observations and the business discussions I’ve been having. The focus in IIoT has been primarily on the first aspect – that is, connecting OT with IT – and analyzing the business processes in between. Predictive maintenance, condition monitoring, and reliability are not new, but what is new is using connectivity to disseminate information to a broader audience. The goal is to look for costly bad actors and systemic problems, then employ IIoT to improve efficiencies. The connectivity or, as Rueckert calls it, “from shop floor to top floor,” hits the nail on the head, expanding visibility from the operator to maintenance professionals who use analyzed usage patterns and trends to head off issues before they become costly problems or to extend the life of the machine.
For example, a sensor measuring pump vibration is taking thousands of readings per second, the sophisticated analysis of which can now be exported and shared with the right people. Having the operator shut off the machine in response to potential errors, costing so many dollars per hour of downtime, is not necessarily the right protocol as the operator is not a maintenance technician. The issue is compounded when the maintenance technician adds issues in a time-stamped queue instead of ranking things in a scale of importance. With “shop floor to top floor” visibility, the costs of downtime and diagnosing can be reduced or avoided.
IIoT has the power to sift through this big data and identify trends for even more effective reliability than ever before. It is very encouraging and exciting to hear about the developments in the “Fourth Industrial Revolution”.