Purposeful function

Transforming raw data into visually compelling and understandable formats. Crucial role in ensuring the highest standards of product quality through the application of data-driven insights and analytics.

Function scope and responsibility

1. Data Analysis and Model Development

Analyze large datasets related to production quality, such as quality inspection data, machine sensor data, and production processes.
Develop Machine Learning and AI models to predict errors or quality issues in advance (Predictive Modeling).
Create and analyze key performance indicators (KPIs), such as Defect Rate, Overall Equipment Effectiveness (OEE), and Process Capability Index (CPK).

2. Algorithm Design and Quality Monitoring

Design and develop real-time anomaly detection algorithms to ensure production quality control.
Integrate data from IoT Sensors and MES to monitor deviations from quality standards.
Collaborate with engineering and QC teams to analyze root causes and identify preventive measures.

3. Data Visualization and Reporting

Develop dashboards and data analysis reports using tools such as Power BI, Tableau, and Python Dash for clear and easy understanding.
Prepare daily, weekly, and monthly reports, communicating analysis results to management and operational teams.
Present insights to identify problems, trends, and actionable recommendations to improve quality control processes.

4. Process Improvement and Automation

Use insights to improve production efficiency and quality control processes.
Identify opportunities for automation to reduce errors and production losses.
Work with the Production Engineering team to plan process improvements aligned with data analysis.

5. AI Implementation and Team Development

Evaluate and refine Machine Learning models for greater accuracy using updated production data.
Provide guidance on implementing new AI technologies in production processes.
Conduct training sessions and foster understanding of data analysis tools among team members.