Manufacturing testing often fails not because data is missing, but because testing is done without a clear decision structure. Many teams increase sample size thinking it will improve accuracy, but this often leads to higher cost without improving clarity. Design of experiments changes this approach by linking sample size directly to decision value instead of…

Modern manufacturing lines produce constant streams of numbers. Machines log values, sensors track performance, and systems store everything from cycle time to defect counts. On paper, it looks complete and well structured, yet the real situation on the shop floor often tells a different story, where decisions still feel unclear and reactive instead of planned….