By industry
Manufacturing
From MPS through shop floor execution. Autonomous agents handle BOM explosion, capacity constraints, quality disposition, and maintenance scheduling.
All six decision domains apply here, portfolio, demand-shaping, supply, production, transport, warehouse — unified on a single world model and surfaced through one Decision Stream.
The Manufacturing Challenge
Mid-market manufacturers face a planning paradox: too complex for spreadsheets, too small for the SAP IBP / Kinaxis implementations that Fortune 500 companies can afford. The result is a patchwork of ERP transactions, Excel workarounds, and tribal knowledge.
"The factory of the future will be orchestrated by AI agents that continuously optimize production schedules, material flows, and quality decisions in real time. Manufacturers who adopt autonomous planning will see 20 to 50 percent improvements in overall equipment effectiveness."
How Autonomy Helps
Master Production Scheduling
Strategic production planning with rough-cut capacity checks. The system ingests demand signals, customer orders, channel forecasts, promotional plans, and market trends, and balances those requirements against available capacity, material constraints, and changeover costs. Planning runs continuously, not just on Monday, so production stays aligned with what the market actually needs.
Multi-Level BOM Explosion
Recursive component requirements with scrap rates and yield adjustments. Support for phantom assemblies, optional components, and configurable lot sizing rules (LFL, FOQ, POQ, EOQ, MIN/MAX).
"Multi-level BOM explosion with real-time yield and scrap adjustments is the single highest-value automation target in discrete manufacturing. Companies that automate MRP netting see planning cycle times drop from days to minutes."
Manufacturing Execution
The MO Execution agent manages manufacturing order release, sequencing, expediting, and deferral - deciding in <10ms whether to release, split, or defer based on capacity, material availability, and downstream demand urgency.
Make-vs-Buy Decisions
The Subcontracting agent evaluates internal vs external manufacturing routing based on capacity utilization, cost differentials, lead time impact, and quality considerations.
Quality Management
The Quality Disposition agent evaluates holds and determines accept, reject, rework, scrap, or use-as-is - factoring in downstream demand urgency, rework cost, and quality history.
"Quality disposition is where AI delivers outsized returns in manufacturing. Automated accept/reject/rework decisions based on historical quality data and downstream demand reduce scrap costs by 15 to 25 percent while maintaining compliance."
Continuous Learning from the Shop Floor
Every production decision generates outcome data that feeds back into agent training. Yield patterns, changeover durations, quality rejection rates - agents learn your specific manufacturing reality and improve their decisions continuously. And because agents never sleep, never take holidays, and don't break for lunch, your production planning operates around the clock. The night shift quality hold gets evaluated immediately, not when a planner arrives the next morning.
OEE improvement with AI-orchestrated production planning
McKinsey Global Institute
MO release decision time including capacity and material checks
Autonomy Platform Benchmark
of mid-market manufacturers still rely on spreadsheets for production planning
Gartner Supply Chain Survey, 2024
scrap cost reduction with AI-driven quality disposition
Gartner Manufacturing Strategy
Typical Results
- 20-35% reduction in total supply chain cost
- Exception worklist reduced from 800+ to under 20 items daily
- Planning cycle compressed from weekly to continuous
- Institutional knowledge captured and self-reinforcing
- 24/7 autonomous operation, agents handle the repetitive so planners focus on what matters
Agents handle the routine. Your team focuses on what matters.
See Autonomy for manufacturing
Walk through a production planning scenario with your data.