Production Workflow Optimization

Replacing manual assignment of orders, staff, and test cells with an optimizer that reschedules as conditions change.

The Challenge

At an engine manufacturing plant in South Carolina, incoming orders, employees, and test cells were assigned manually. As demand, staff availability, and test cell availability change, manual scheduling makes it difficult to balance capacity, resources, and order deadlines efficiently.

The manufacturer needed a way to automate these decisions and make better use of its existing test cells and workforce, particularly when multiple orders compete for the same resources.

Our Approach

Fraunhofer USA CMA developed a data-driven scheduling and optimization solution that pulls incoming orders, test cell availability, and employee availability directly from the plant's database.

An optimization algorithm assigns orders to available resources with the goal of minimizing total completion time while respecting operational constraints. As new orders arrive or resource availability changes, the schedule can be recomputed to adapt to the current production situation.

The Impact

The optimization-based approach consistently outperformed conventional scheduling strategies, with particularly strong performance under resource contention, while balancing workload across available test cells.

By automating scheduling decisions and continuously adapting to changing production conditions, the solution provides a foundation for higher throughput, shorter turnaround times, and more efficient use of existing test cells and employees.