Using AI and Digital Twins to Enhance Manufacturing Workflow Efficiency: Andrew Scheuermann - CEO and Co-Founder , Arch Systems
While the promise of AI is immense, many manufacturers find themselves stuck in pilot projects, unable to unlock its full potential. The key lies in addressing foundational challenges and adopting a clear, phased strategy to transform operations. Fundamentally, AI offers manufacturers a pathway to achieving operational excellence by moving through the four stages of analytics maturity: 1️⃣ Descriptive Analytics – Understanding what happened. 2️⃣ Diagnostic Analytics – Pinpointing root causes. 3️⃣ Predictive Analytics – Forecasting potential equipment failures or quality issues. 4️⃣ Prescriptive Analytics – Recommending the best actions to address challenges. Despite its promise, many manufacturers struggle with significant obstacles, which include data fragmentation. I recently had a sit down with Andrew Scheuermann the CEO and Co-Founder of Arch Systems to discuss why building a comprehensive Digital Twin is the key to overcoming these barriers and how manufacturers can use AI to enhance manufacturing workflow efficiency.