Client: Global Specialty Materials Manufacturer
Project Type: Process Improvement & Cost Reduction
Methodology: Lean Six Sigma – D.M.A.I.C.
Challenge (Define)
A key production line a plastic manufacturing facility was experiencing excessive downtime and inconsistent product yield, resulting in significant operational costs and delayed customer deliveries. Leadership sought a data-driven solution to identify root causes and implement sustainable process improvements.
Approach (Measure & Analyze)
As a lead process improvement consultant, I initiated a Six Sigma DMAIC project:
- Measured baseline performance: downtime of 15% per week and yield variation of ±8%.
- Conducted process mapping and engaged with cross-functional teams (engineering, operations, maintenance).
- Performed root cause analysis using tools like Fishbone Diagrams and FMEA.
- Uncovered that equipment calibration issues and operator variability were the top contributors to yield loss.
Solution (Improve)
- Implemented standardized work instructions and retrained operators to reduce process variation.
- Upgraded calibration protocols and introduced real-time performance dashboards for machine monitoring.
- Partnered with maintenance to develop a predictive maintenance model using historical failure data.
Outcome (Control)
- Achieved a 25% reduction in downtime and 7% increase in yield consistency within 90 days.
- Developed control plans with KPIs and implemented visual management tools to sustain gains.
- Resulted in annualized cost savings and improved on-time delivery metrics by 18%.
Impact
This project not only demonstrated measurable ROI, but also showcased how data, engineering principles, and human-centered change management can drive operational excellence. It remains a benchmark project referenced internally for future process improvement initiatives.
