Quality improvement of DB-CDP with integration of CRISP-DM and six sigma method

Ahmad Alfiandi, Triwulandari S.D, Rina Fitriana

Abstract


The DB-Customer Display Product (CDP) is a product that has a high level of defects with the type of attribute that the display light is off. The quality improvement is carried out using the integration of the Cross-Industry Standard Process Data mining (CRISP-DM) method with Six Sigma. The technique using classification technique with the CART algorithm to identify the leading causes of defects in the CDP and association processes using the Frequent Pattern-Growth Algorithm to make association rules between the combination of production support data sets. The results of both algorithms known attributes that cause high rejects are poor solder and solder Short. Implementation of proposed improvements made at the deployment stage, there are work instructions for re-soldering, tip checking forms, and Standard Operating Procedures for solder tip replacement. The result from implementation, was decrease in the value of Defects per unit to 0.0541, where previously it was worth 0.0628, and the value of Defects per million Opportunities decreased from 32.636 to 27.020, and converted into sigma level and obtained sigma value 3.80, before the implementation was at 3.74 sigma. The three indicators of DPU, DPMO, and Sigma level indicate that the proposed quality improvement is successful.

Keywords


CART Algorithm; CRISP-DM; FP-Growth Algorithm; Six Sigma

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References


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