The industry is reeling under the explosion of data generated by smart sensors, motors, actuators, machines, and other “things”. With the pace at which production is happening currently, the last straw would be an asset breakdown. Statistics show that the automotive industry deals with an alarming 800 hours of downtime every month. The cost of such downtime is a staggering US$22,000 per minute, or US$12.6 million a month.
Additionally, data shows that 20% of these breakdowns are common or predictable and that a majority – a shocking 80% – of them are seemingly random instances and cannot be predicted.
According to McKinsey, the Industrial IoT (IIoT) market is worth $11 trillion, and predictive maintenance solutions can help companies save $630 billion over the next 15 years. So, how can manufacturers tap these savings and benefits?
Join us in our webinar featuring Vishwas Shankar, Research Manager, Frost and Sullivan and Sundeep Sanghavi, CoFounder and CEO, DataRPM to learn how automotive manufacturer and automotive suppliers can experience the power of Cognitive Predictive Maintenance (CPdM) to avoid unplanned downtimes and drive greater efficiencies.
Date- August 2, 2017
Time- 9:30am- 10:30 am PST
By attending this webinar, you will
2. Monetize the trillion-dollar opportunity of the IIoT by applying machine learning to get valuable insights to identify failure triggers from operational sensor data
3. Cognitive Predictive Maintenance (CPdM) significantly helps augment your bottom line with a 50% reduction in maintenance over time, 20% reduction in production downtime and 20% enhancement in labor productivity
4. Live demonstration of uses-case to highlight how IIoT can be made scalable, efficient and ROI-generating