Implementing AI solutions for manufacturing operations

As an industrial player, your goal is to harness AI technology to boost productivity, improve yield or asset utilization, make predictions based on data insights, and leverage this increased performance to gain a competitive edge against the other players in your sector. 

But most manufacturing organizations lack the skill sets, scientists, data, and infrastructure readiness to pursue unique differentiating processes or solutions. A recent global study involving organizations across 16 industries found that 80-85% of companies are stuck in the proof of concept stage when it comes to their AI projects.

• Are you just getting started with AI and don’t yet know how to leverage AI in your business?
• Are you already farther along than that, with an in-house data science team that has algorithms in development or production?
• Perhaps you have invested heavily in AI upfront and are disillusioned with the meager return on investment you’re seeing. Or you want to continue pursuing AI initiatives and deploy them at scale, but you need to justify their cost with concrete results before you can get stakeholder approval and finance more proof-of-concept initiatives.

Regardless of where you are in your AI journey, once you’ve developed and built your AI, the challenge is to get it out of the proof-of-concept stage and into practical use within production quickly, convince your teams to adopt and accept it, and deploy it at scale.

Don’t miss this webinar if as a plant director or operations manager you want to keep up with technological advances, to capture and consolidate knowledge detained by your experts, to comply with quality regulations and standards, to perform real time quality control and adjust machine parameters automatically, on the long haul.  

Join us in a practical webinar to learn what data science brings to manufacturing operations and the importance of AI lifecycle services through operational use cases.