Even though defect reduction is often viewed as the overarching goal of a Six Sigma project, optimization is just as important. In this case study, we follow the efforts of your Six Sigma team as you work to both optimize an existing manufacturing process and reduce the number of defects it produces.
Your company is Components Inc., a manufacturer of aluminum components used in high-end audio equipment. The surfaces of these components are anodized and then dyed to produce a visually smooth, rich, black surface.
Unfortunately, Components Inc. currently has a significant problem with discoloration of their black components. Lot yields in manufacturing are extremely low, causing rework and compromising on-time delivery. Failure to fix this problem could cost Components Inc. its major customer and more than a million dollars in losses.
Management assembles a Six Sigma project team, and you are the black belt. You and the team are charged with improving the yield of the anodizing process. This case study follows you as you and the team go through all of the steps of the Visual Six Sigma Data Analysis Process.
You make extensive use of dynamic visualization in achieving your goal. You identify four Ys and five Hot Xs that relate to yield. Measurement System Analysis (MSA) studies are conducted and the results are explored using variability charts. Specification limits for the four Ys are determined using Exploratory Data Analysis (EDA) ...