Manufacturing Changeover Optimization

The Problem Today

Production planners manually sequence 200–500 changeovers per line per year, balancing customer OTIF requirements, inventory targets, and changeover minimization. Changeovers are the largest single source of OEE loss (15–30%). Changeover time varies 30–50% for the same SKU pair depending on crew, time of day, and equipment condition. The planning cycle runs 1–5 days from demand forecast to production schedule.

How It Works

Every changeover solution is powered by a Decision Value Loop – a continuous cycle of five stages:

1. Sense: Real-time data from ERP (customer orders, demand forecasts), MES (line status, production rates), changeover history, and quality systems.
2. Analyze: Predict changeover duration by SKU pair, crew, and equipment state. Optimize production sequence to minimize total changeover time while meeting delivery commitments.
3. Decide: Recommend production schedule with changeover timing. Provide alternatives when disruptions occur (equipment failure, rush orders).
4. Act: Push optimized schedule to MES. Alert production supervisors to sequence changes.
5. Learn: Every changeover refines duration models and sequencing rules. Identify crew-specific best practices.

Why Not Off-the-Shelf AI?

Production scheduling requires understanding the specific physics of each production line – which SKU transitions require cleaning, which can run back-to-back, how equipment age affects changeover time. Company-specific rules and constraints (customer priority, regulatory lot tracking, equipment quirks) make generic solutions fail.

The metricsIQ Advantage

Industrial data platform experience at 47Lining gives us proven expertise in the enterprise integration challenge at the heart of changeover optimization. ERP/MES/CMMS bridging is a classic IT/OT convergence challenge – and one our team has solved before at scale.