Maintenance, Repairs and Operations industry is undergoing a game changing transformation in the last few years after the introduction of IoT. Sensors and real-time monitoring have begun to replace the traditional time, usage or mileage based maintenance with the predictive maintenance.

Running through the yellow pages to locate the right service personnel or knowing whom to call when equipment breaks-down used to be the norm just few years ago. Thanks to predictive maintenance enabled by IoT, the right service personnel will now call you to schedule a tune-up before the equipment goes down. Industrial IoT (IIoT) has been the fastest growing IoT application by far and plenty of manufacturers have either developed or acquired such capabilities and others continue to do so.

Impact of IoT is beyond predictive. Especially in the domain of production operations, IoT is making the convergence of operations, communications and information technologies. End users of the likes of production facility managers, field service personnel etc. are increasingly habituated to this IoT driven convergence. On the other hand, IoT sensors continue to become smaller in size, easy to plug-in and more affordable. New communication networks are emerging and competing (LoRa, Sigfox, NB-IoT etc.) with each other to enable reliable, affordable and faster data transfer.

The pace of developments on the – IoT data generation, Bigdata analytics, machine-learning algorithms – has overtaken the pace at which the end users are integrating these efficient technologies into their workflow. Few scenarios have begun to emerge where the IoT data and business intelligence is in excess and is unused in the daily operations of the end user because that can’t easily integrate with end user’s workflow.

IBM with its IoT Equipment Advisor has gone one step further in addressing this – in combining predictive with cognitive. Cognitive capabilities and algorithms can operate on huge amounts of data and intelligence generated by IoT/Bigdata/Machine-learning and consolidate, classify and recommend specific resources to service personnel to help in executing a specific repair or maintenance procedure.

The lack of integration of IoT driven technologies into end user’s workflow becomes more visible when we look into the maintenance in the public domain. Maintenance of public assets like streetlights, traffic lights and so on, spreads over larger geographical areas and can impact public safety.

sensfix funded and accelerated by Rockstart Smart Energy Accelerator, is thinking beyond predictive and cognitive and developing a platform solution for the most critical of the applications – the public IoT. sensCloud platform developed by senfix offers smart workflow that completely automates different steps of maintenance and repair workflow. It combines the IoT data consolidation, classification, prioritization with various steps of the maintenance and repair workflow like – complaint management, planning of labor, materials and inventory, service management, service travel route optimization. sensCloud stores the general asset data, repair histories and provides a collaborative platform including audio-video links for all stakeholders – asset owner, asset manager and the common man in the public domain.

sensfix platform is finding applications beyond repairs and maintenance. Pollution monitoring and control, disaster recovery in collaboration with drone technology are few of them.

sensCloud continues to evolve as new customers start using it, enhancing its customizable peripheral modules while keeping its core modules intact. Automating the entire process workflow for an industry based on real-time data coming in from the assets is a challenging task. If you like to know more, contact info@senfix.com

The author is Balaji Renukumar, Founder & CEO of sensfix (Amsterdam, The Netherlands) set to disrupt the Repairs & Maintenance Industry