Forbes estimates the cost of downtime alone is over $50 billion each year for industrial manufacturers. This is more than substantial and can often be the difference between a company making or losing money. The article points toward predictive maintenance gaining prominence to significantly reduce downtime, to learn faster and predict failures long before stoppages can ever happen.
A common misconception when it comes to Digital Transformation and Industry 4.0 is that with the rapid adoption of the technology gamut associated with them, the manufacturing operation would, as a step change, transform into a fully automated endeavor, orchestrated almost entirely by autonomous AI applications, self-optimizing and self-driven.
Digital Transformation has increasingly become the top priority for leaders the world over. It has become a main pillar of operations strategy and has gained momentum ever since the COVID pandemic hit in 2020. What is less evident though is the fact that digital transformation is far more than just the adoption of automation and new technology. It is really about people and their improved/enhanced/augmented interaction with data: the ability to gather more data faster; manipulate and utilize that data from all incoming and available data streams in the right context with a connected workforce; and allow this digitally-transformed workforce to use this data through the right platforms to perform better, to generate better business and operational results.
Digitizing tasks and activities for frontline workers, while providing real-time operational visibility and driving process optimization and improvement, across all areas of business operations.
