Optimizing the Yield of Multi-process Wheelchair Components Using the Six Sigma Define, Measure, Analyze, Improve, Control Approach

Amid growing consumer awareness, quality management and risk control have become paramount in manufacturing.Inadequate quality assurance systems can escalate production costs through yield deficiencies and provoke adverse market responses due to inconsistent product quality.In this study, we employed the Six Sigma Define, Measure, Analyze, Improve, Control (DMAIC) methodology to enhance quality in wheelchair accessory parts manufacturing.In the Define phase, the production process for the sampling stage is mapped using a flowchart, incorporating inspection checkpoints at critical junctures.The Measure and Analyze phases utilize Failure Mode and Effects Analysis (FMEA) to identify potential failures, evaluating their severity, occurrence, and detectability to devise preventive strategies.Concurrently, a Control Plan is established, specifying quality attributes encompassing equipment, inspection protocols, process parameters, evaluation techniques, sampling ratios, frequencies, and analytical methods, along with corrective actions for anomalies.In the Improve and Control phases, process capability indices are applied to assess product quality stability during ongoing production, targeting defect containment within three standard deviations.This approach minimizes customer complaints, reduces carbon emissions from defect-related transportation and maintenance, fosters environmental sustainability, lowers manufacturing costs, and bolsters customer loyalty.The findings provide a replicable framework for quality optimization in precision manufacturing sectors.