Case Study
Reducing manufacturing defects through Lean Six Sigma
overview
Applying Lean Six Sigma to identify and eliminate the root causes of recurring defects in a critical appliance component, improving manufacturing quality, assembly efficiency and production costs.
15% → 1.8%
Defect rate reduction
$350K
Annual cost savings
+18%
Assembly cycle time improvement
Project Objectives
A home appliances manufacturer was experiencing a persistent 15% defect rate in a critical component manufactured in-house from short-glass-fiber-filled polypropylene.
The defects were not detectable during standard in-line quality checks and only became apparent after the component was assembled into the finished product, resulting in significant quality-related costs.
Despite previous investigations by the company’s R&D team and external Lean consultants, the underlying causes remained unidentified and earlier improvement initiatives had failed to resolve the issue.
The objective was to identify the root causes of the defects, implement effective corrective measures and reduce the defect rate to the lowest achievable level without compromising production efficiency.
Key Challenges
Defects detected too late in production: The component passed existing quality checks, with defects becoming visible only after final assembly. This increased the cost of defective parts and complicated the identification of their underlying causes.
Unresolved technical issues: Previous investigations had failed to establish why the defects occurred. The problem required a systematic examination of component design, manufacturing technology and assembly processes.
Multiple contributing factors: The defects were linked to more than one stage of production, including injection molding and automated assembly. Identifying how these factors interacted required detailed measurements and structured analysis.
Gaps in quality control: Existing inspection procedures were insufficient to detect defects before the components entered subsequent production stages, allowing problems to continue through the manufacturing process.
The Approach
The project began with a one-week on-site assessment involving detailed measurements, production observations and data collection across the component manufacturing and assembly processes.
A structured Lean Six Sigma investigation was conducted to identify the underlying causes of the high defect rate. The analysis examined injection mold design, material behavior, automated assembly technology and existing quality control procedures.
The investigation identified two major technical issues. The injection mold design contributed to rapid shrinkage of freshly molded components, while programming inconsistencies in the robotic assembly cell occasionally caused microscopic damage during assembly.
Following the initial assessment, several months of remote analysis and implementation support focused on refining the findings, developing corrective measures and introducing targeted process changes.
The resulting improvements addressed the identified causes of component defects and strengthened the manufacturing and assembly processes.
The results
The Lean Six Sigma initiative delivered measurable improvements in product quality, production efficiency and manufacturing costs:
Defect rate reduced from 15% to 1.8%, addressing a persistent quality issue that previous improvement efforts had failed to resolve.
18% improvement in assembly cycle time, increasing the efficiency of the production process.
$350,000 in annual cost savings achieved through reduced defects and improved manufacturing performance.
Root causes identified and addressed across injection molding and automated assembly operations.
Improved process reliability, reducing the likelihood of recurring defects associated with the identified technical issues.
The project resolved a longstanding manufacturing problem through targeted technical changes rather than additional broad improvement initiatives.
Lessons learned
Defects can originate long before they become visible: Quality problems detected during final assembly may be caused by earlier manufacturing stages. Effective root cause analysis must examine the entire production process rather than focusing only on where defects are discovered.
Multiple technical issues can produce the same quality problem: In this case, injection mold design and robotic assembly programming both contributed to the defect rate. Addressing only one would not have resolved the complete problem.
Data-driven analysis is essential when conventional improvements fail: Structured measurement and statistical analysis can reveal relationships between process variables that remain difficult to identify through observation or isolated corrective actions.
Automation does not eliminate process-related defects: Robotic assembly systems can introduce quality problems when equipment programming and component characteristics are not properly aligned.
Key takeaways
A persistent 15% defect rate had remained unresolved despite previous investigations and improvement efforts. The underlying causes were eventually traced to specific technical problems in injection molding and automated assembly.
A structured Lean Six Sigma investigation, followed by targeted corrective measures, reduced the defect rate to 1.8%, improved assembly cycle time by 18% and generated $350,000 in annual savings.
The results highlight the importance of examining manufacturing processes as an interconnected system, particularly when quality problems cannot be explained by conventional inspection or isolated process improvements.
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