{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Automate Now","title":"Chapter 12: Production Analytics and Continuous Improvement","html":"","width":"100%","height":180,"duration":792,"description":"Deploying automation is the beginning, not the finish line. The manufacturers who get the most out of their systems are the ones who treat data as a core operational capability — not a nice-to-have dashboard. In this episode, Formic Product Manager Molly Garrison walks through how production analytics transforms automation from static machinery into an adaptive, continuously improving system, and why visibility into what's actually happening on your line is the key to unlocking its full potential.The episode covers the key performance indicators every manufacturer should track — OEE, cycle time, downtime, throughput, first pass yield, MTBF, MTTR, and energy consumption — and explains how to turn that data into action through visualization tools, automated alerts, root cause analysis, and structured continuous improvement programs. A real-world case study shows how one manufacturer's palletizing line went from chronic missed targets and overtime to accurate scheduling and proactive problem-solving once they deployed Formic Production Intelligence (FPI). The shift from reactive to predictive isn't reserved for advanced operations — it starts with simply replacing paper logs and guesswork with reliable, real-time data.Key Takeaways:Data transforms automation from a static machine into a learning system — without it, you're managing by assumption and fighting fires instead of preventing themKey KPIs to track: OEE, cycle time, planned and unplanned downtime, throughput, first pass yield (FPY), MTBF, MTTR, and energy consumptionFormic Production Intelligence (FPI) gives teams real-time CPM benchmarks per SKU with visual status indicators — green, yellow, and red — so problems are caught in the moment, not after the shiftOne manufacturer went from chronic overtime and missed targets to reliable scheduling and proactive problem-solving simply by making performance data visible and actionableThe path from reactive to predictive analytics starts simple: eliminate paper...","thumbnail_url":"https://img.transistorcdn.com/lgirYQYIxA7pl6I1kn2EHj-2uC9hT0oBgYXlmFJpPLo/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lOGM2/YjlhYWRhZmQ4YTQx/NTg1OTA3YTU4MGE2/ZGJjZS5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}