Factory Data Analysis & Intelligent Solution Implementation:
Analyze specific production processes (e.g., OEE, quality control, energy consumption) to identify business pain points. Use tools like SQL and Python for data extraction, cleaning, and analysis.
Design and develop data visualization dashboards (e.g., using Spotfire,Power BI) to translate data insights into actionable information for onsite management.
Research and apply advanced algorithmic models (e.g., time-series forecasting, anomaly detection) to real production data. Evaluate their business value and support the pilot implementation of "smart data" solutions.
AI Integration and Adoption:
Research the latest trends in AI applications within manufacturing (e.g., quality inspection, process optimization, predictive maintenance).
Under the guidance of a mentor, contribute to specific AI adoption projects, such as:
Participate in the daily operation of the test data flow, analyze historical and real-time data from operation
Applying natural language processing to analyze equipment maintenance logs for root cause analysis.
Utilizing machine learning algorithms for intelligent classification and root cause analysis of test results.
Assist in evaluating the feasibility, cost, and ROI of different AI solutions and contribute to technical reports.