Case Study: Model Validation

The Challenge

A large manufacturer needed a way to create a digital twin of their production system to rapidly develop and test strategies for improving production flow. Multiple products were run on the same production line and each product had unique and expensive tooling. The goal was to create an accurate model for predicting the production flow behavior of the production system.

Our Solution

We built a production system model in LineLab. Inputs consisted of machine and part carrier counts and cycle time averages and standard deviations for the different processes. In this particular factory, the part carriers were large molds that would travel along with the part through the entire production process. Therefore, the number of part carriers was limiting the maximum amount of work-in-progress inventory in the system.

LineLab automatically includes the mathematicals for part routing and queueing, equipment utilization, and for lean practices in the real facility. This drastically speeds the modeling process, getting answers sooner. The model predicts the average production rate of the system by maximizing throughput taking into account the process variability, machine and tool utilization, and optimal inventory allocation.

Total Error


Our models predicted a production rate of 21.86. Comparing the model result to the actual observed production rate of 22.00 yields an error of only 0.64%. LineLab’s comprehensive sensitivity analysis gave the team a clear path forward for continuous improvement efforts after exhausting state-of-the-art resources for lean production.