Data Analytics

1. Data Integration and System Management

i) Clean, validate, and input daily operations data (manual entries, equipment data capture, supply chain data, etc.) into the Kingdee system, ensuring data integrity and accuracy.

ii) Maintain data interfaces between Kingdee and equipment systems (e.g., PLC, MES); build a unified data platform to enable multi-source data fusion.

2. Algorithm Development and Model Building

i) Cost analysis modeling : leverage data from production scheduling, work time, and material consumption (reference for 2-shift / 3-shift cost algorithms) to quantify cost differences across production modes.

ii) Quality fluctuation attribution : use sensor data from equipment (e.g., motor torque, speed) and manual quality inspection records to construct SPC (Statistical Process Control) models and identify root causes of quality anomalies.

iii) Resource allocation optimization : based on historical work orders, Overall Equipment Effectiveness (OEE), and manpower scheduling data, develop dynamic resource scheduling algorithms to improve capacity utilization.

3. Visualization and Decision Support

i) Design Power BI / Tableau dashboards to monitor costs and quality KPIs in real time (e.g., cost per unit, defect rate), issue deviation alerts, and generate root-cause analysis reports.

ii) Regularly deliver an Operations Decision Brief, including but not limited to :

• Production shift adjustment recommendations (3-shift vs 2-shift economic simulations)
• Quality improvement priorities (Top 3 defect types and related processes)
• Supply chain inventory optimization plans (dynamic safety stock calculations)

4. Cross-Department Collaboration and Process Optimization

i) Work with Finance, Production, and Quality teams to standardize data collection processes and promote standardized cost accounting.

ii) Train frontline team leaders to use data tools and promote data-driven culture.

Requirement :

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