P66: Speed Up Inspection Readiness with Analytical Solutions
Business Title Manager, Software Development
1. A guided System for Inspection Readiness (IR) with a roadmap to become always inspection ready
2. A monitoring system to obtain fast actionable insights on IR health and IR solution performance health
3. ML, NLP to compare the accuracy in predicting possible inspection findings
Advance analytical and visualization techniques with ML and NLP was deployed to consume IR data and extract hidden insights while creating a guided indicator system of IR to become proactive in mitigating inspection issues beforehand. Surveys and GEMA was used to analyze efficiency.
1) Efficiency: No inspection findings (3 inspections). No additional man hours.
2) Highly replicable: Adopted by 6 operations (study build, SAS, analytics, etc.)
3) High visual preference & efficiency: F pattern1, Arrowhead Model2 and RAG based hybrid – 67% (N=88) preferred RAG2 and 78% preferred interactivity2.
4) Granular actionable insights: pending issues, quantity, and stakeholders. Proactive identification, and resolution of inspection findings.
5) High end-user satisfaction: 100%, (N=7)
6) Additional benefits (Gemba3): 15% time saving, manual error-free, uniformity, better documentation.
7) Predictive modeling4-9: Optimum output: Multi-Class Logistic Regression Model (TF-IDF4 vectorized inputs) - 76% vs. average 60%
Conclusion: This study was performed based on a pilot project. IR is a user-friendly concept that promotes better work-life balance and a culture of being always inspection-ready. This evolving model is ensuring zero reportable inspection findings. With the maturity of the project, further enhancements and analysis of efficiency will be performed using a larger volume of non-synthetic data.