Predictive maintenance reduces downtime

Unplanned downtime is recognised as a leading cause of loss of productivity in manufacturing, resulting in output delays and unsatisfied customers. According to a report by Deloitte, entitled ‘Predictive maintenance and the smart factory’, it is estimated that unplanned downtime costs industrial manufacturing companies an estimated $50-billion a year.

Reducing unplanned outages by ensuring continual maintenance can be achieved by partnering with organisations that offer field services teams and a robust support infrastructure, fed by experts across the world, that speeds problem-solving and lessens potential losses, asserts digital automation and energy management company Schneider Electric.

“An important differentiator of any field services offering, is the ability to offer end-to-end monitoring, maintenance and repair.  In the case of Schneider Electric’s Secure Power offerings, our field services teams focus on the entire ecosystem of products that include uninterruptible power supplies, power distribution, security/environmental monitoring, cooling and software,” comments Schneider Electric secure power expert consultant Reinard van Antwerpen.

The company highlights the use of predictive and prescriptive service maintenance and Internet of Things (IoT) sensors to constantly report on the condition and performance of assets, allowing for service to be provided based on the actual health of equipment, rather than on a fixed schedule.

“With this level of field service provision, we are constantly analysing data in parallel with artificial intelligence software and our team of experts.  For example, if a component shows early signs of failure, an engineer can be immediately dispatched to repair or replace it - before a shutdown even occurs,” explains Van Antwerpen.

Schneider Electric’s EcoStruxure augmented operator adviser technology gives support teams access to digital field service manuals, schematics and blueprints.

The custom application helps improves operational efficiency with the use of augmented reality, which allows operators to superimpose data and virtual objects onto a cabinet, a machine or a plant.