Produce more with
same resources or less
AI identifies hidden capacity in your existing operations - optimizing machine utilization, reducing changeover waste, balancing workloads, and eliminating bottlenecks - so you produce more with the people and equipment you already have.
From hidden losses to measurable gains
Most operations run at 60-70% of their theoretical capacity. The gap isn't caused by one big problem - it's the accumulation of small losses: changeover time that could be shorter, machines idling between jobs, unbalanced workloads where one line is overloaded while another waits, micro-stops that nobody tracks because they're "normal." These losses are invisible in monthly reports but add up to 20-30% of lost capacity.
KFactory makes these losses visible and actionable. Real-time OEE monitoring decomposes performance into availability, performance rate, and quality - showing exactly where capacity is leaking. Computer vision tracks throughput and counts output directly on the line, eliminating manual tallying errors and giving you accurate production data in real time. AI analyses patterns across shifts, products, and machines to identify the highest-impact improvement opportunities. The scheduling optimizer ensures machines are never idle when there's work to be done, changeovers are sequenced to minimize setup time, and workloads are balanced across available resources.
The result: more output from the same footprint. No new machines, no extra shifts, no additional headcount - just systematic elimination of the waste that's been hiding in plain sight.
Key insight: A single percentage point of OEE improvement in a typical manufacturing operation translates to thousands of additional units per year - from the same people, the same equipment, and the same floor space.
What you can expect
Unlock 15-25% additional capacity from existing resources without capital investment.
Based on OEE improvement benchmarks from the World Class OEE framework. Organisations moving from 60% to 75% OEE typically achieve 15-25% more output from the same assets (McKinsey, SEMI).The improvements compound over time. As each source of loss is addressed - downtime reduced, changeovers shortened, schedules optimised - the overall system operates closer to its theoretical maximum. Autonomous Optimisation agents continue running controlled experiments after the initial gains, ensuring performance keeps improving rather than plateauing.