Analisis Pengendalian Kualitas Statistik dan Perencanaan Desain Smart Garden Furniture Berbasis Python Data Library

Abstract

Synchronizing consumer preferences with manufacturing process reliability serves as a crucial pillar in assembling smart outdoor furniture. This study is directed toward combining the Quality Function Deployment (QFD) strategy via the House of Quality (HOQ) matrix alongside Statistical Quality Control (SQC), facilitated by Python Data Library computational algorithms. This quantitative analysis relies on questionnaire feedback from 50 participants and technical assessments of 40 representative prototype units. Instrument evaluation proves compliance with data validity and reliability requirements (Cronbach's Alpha = 0.724). The planning matrix computation positions the mechanical aspects of the main supporting pillars (TR5) as the highest manufacturing engineering focus, with a 22.08% contribution toward foundational stability. Conversely, statistical evaluation on the shop floor maps electrical outlet defects as the most dominant failure, reaching 55%, supported by p-chart control graph findings capturing an operational deviation in Batch 6 (p = 0.350 > UCL = 0.2895) with sub-optimal process capability index performance (Cpk = 0.86). The implementation of this programming-based closed-loop quality assurance scheme successfully eliminates informational barriers between departments through real-time and direct engineering specification updates and automated tolerance design alterations.