About
Teknor Apex
Teknor Apex is a global leader in specialty polymer compounds, including plasticizers, with $1B in annual revenue and 20 production sites worldwide. Each factory runs 5 to 10 lines with complex changeover constraints, raw-material shelf-life sensitivity, and high SKU variability.
Before Oplit, scheduling relied on a legacy solution rigid, opaque, and entirely dependent on individual expertise.
Teknor is:
20 factories
$1B turnover
5–10 lines per site
Impact
The story
Plasticizer manufacturing runs on tight sequences, stock constraints, and constant demand volatility. At that scale and complexity, reactive scheduling is the default with suboptimal tradeoffs made under pressure and schedules rebuilt by hand multiple times per day.
Oplit changed the operating model. Before each production run, demand is predicted and batch sizes are optimized, eliminating future changeovers before they appear on the schedule. When conditions shift, the schedule updates in real time without manual intervention. Factories stopped absorbing volatility now they control it to maximise production efficiency.
The challenge
Scheduling at Teknor Apex was built on a legacy solution. Constraints were hardcoded, decisions were mostly manual, with thousands of rules in people's heads. With 20 factories and hundreds of SKUs, the system created as much complexity as it managed.
Oplit's approach
Demand-driven production batching
Before each production run, Oplit's prediction model estimates the probability of similar orders arriving in the next weeks. When relevant, it recommends increasing run quantities to avoid redundant future changeovers turning scheduling into a proactive capacity lever rather than a reactive queue.
Scheduling on autopilot
With Oplit Copilot, decisions are automated by default. The system generates and updates the schedule in real time, without manual intervention. Planners shift from building plans to steering them validating exceptions.
A knowledge model planners actually own
Instead of a blackbox with hardcoded rules, Oplit's knowledge model lets planners define, adjust, and evolve hundreds of production constraints themselves. Each site builds its own scheduling logic without writing a single line of code.
Predict demand. Run less. Produce more.
Before every production run, Oplit models the probability of similar orders arriving in the coming weeks. When relevant, it recommends increasing run quantities to avoid redundant future changeovers. Sequence optimization happens upstream, not as damage control. Less switching, higher yield, and a schedule that actively works to protect production capacity rather than just reflect it.
Decisions happen automatically. Exceptions surface instantly.
Oplit Copilot generates and updates the schedule in real time, across every site. Planners don't build plans, they review decisions the system has already made. When something changes on the floor, the schedule adapts without waiting for a human to catch it. The result: planners gain a lot of productivity, throughput went up, and response time to disruptions dropped from hours to minutes.
Constraints are owned by the factory, not locked in code.
Oplit replaces the blackbox with a knowledge model planners control directly. Every constraint changeover sequences, skills, tooling, raw material shelf life is defined, adjusted, and evolved by the teams who understand the floor. As the factory changes, the scheduling logic changes with it. No IT ticket. No delay. Scheduling intelligence becomes a living asset, continuously refined by the people closest to production.
