Northrop Grumman’s B-21 charges point to a familiar problem: late process changes to reach rate create cost and schedule risk.
How to find, analyze, and design bottlenecks to optimize flow, cost and performance.
A head-to-head look at top-down vs. bottom-up cost estimation methods, and how LineLab combines the best of both.
Flow details can switng throughput by 50% - learn about the impact of rework loops, feeders, batching, yield, variability, reentry, and staffing.
The structural production decisions made before scale determine rate, cost, and capital efficiency, yet they are rarely treated as a formal design problem.
Extending published mRNA techno-economic models with system-level behavior, uncertainty, and scale-up insights.
Spreadsheets, simulations, and custom toolchains form the foundation of production modeling in advanced industries. This article examines the state of practice before LineLab.
An overview of discrete‐event simulation, queueing theory, and analytical approaches—including LineLab’s innovative solver.
Join industry leaders at the Solving for Scale Summit at MIT to tackle the challenges of scaling manufacturing and driving industrial innovation.
Process time variation is often the most important factor if a factory underperforms. Debunking myths, we uncover profound implications it has in factory operations, and show how to model the "hidden factory".
