Nitin Parekh, CEO, Via Automation

Paving the Way for Resilient Supply Chains

In today's semiconductor industrial landscape, downtime is more costly than ever. Unplanned machine downtime cost manufacturers more than $1.5 trillion globally per year. The cost of a single hour of downtime has surged by 50% in just two years.

Similarly, semiconductor manufacturing is inefficient due to complex chip designs and the need for nanoscale precision. Manufacturers, semiconductor fabs and energy providers are all looking for ways to maximize uptime, extend equipment life and reduce unexpected failures. Traditional solutions rely on dashboards and complex visualizations that don't solve the root problem.

Predictive maintenance powered by AI, automation and edge connectivity can change this. The use of artificial intelligence and generative AI chat are emerging as game-changers for enterprises looking to be more efficient and cost effective by implementing predictive maintenance at scale.

As the complexity of equipment and unexpected failures grows exponentially, the challenges of traditional maintenance are hard to ignore. Maintenance strategies for decades have been reactive—fix after failure—or preventive by relying on scheduled servicing. Both have unmistakable limitations that no longer work. Reactive maintenance leads to costly downtime and safety risks, while preventive maintenance often results in unnecessary part replacements and wasted labor.