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Evaluate the Yield Rate of Multi-Process Products Using the Six Sigma DMAIC Method

EasyChair Preprint no. 14022

5 pagesDate: July 18, 2024

Abstract

With the rising consumer awareness, the emphasis on quality management and risk control has significantly increased. Without an effective quality assurance system, manufacturing costs can rise due to yield issues, and inconsistent quality may lead to market backlash. This study applies the Six Sigma DMAIC methodology to wheelchair accessory parts, focusing on the critical stages of Define, Measure, Analyze, Improve, and Control.

Initially, during the sampling stage, the production process is planned, incorporating inspection points into the key processes using a production flowchart. Failure Modes and Effects Analysis (FMEA) is used to identify potential failures, assess their severity, frequency, and detectability to implement preventive measures. Simultaneously, the control plan outlines quality characteristics from mechanical equipment and inspection methods to process parameters, evaluation methods, inspection ratios, frequencies, and analysis methods, and proposes improvement recommendations when anomalies are detected.

Finally, the process capability index is used to evaluate the quality stability of the product in continuous production, aiming to control defects within three standard deviations, reduce complaints, transportation, and technical maintenance carbon emissions, promote sustainable development, reduce production costs, and improve customer loyalty.

Keyphrases: analysis for processes with multiple characteristics, Control plan, failure modes and effects analysis fmea, FMEA, process capability index, Quality Function Deployment, Six Sigma

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:14022,
  author = {Sung-Chang Lin and Shui-Chuan Chen},
  title = {Evaluate the Yield Rate of Multi-Process Products Using the Six Sigma DMAIC Method},
  howpublished = {EasyChair Preprint no. 14022},

  year = {EasyChair, 2024}}
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