Big Data Analytics for Production Management

Introduction to Big Data in Production Management

• Definition of big data and its relevance to production management
• Key components of big data: Volume, Variety, Velocity, and Veracity
• Benefits of big data analytics in production optimization
• Challenges in adopting big data in production environments

Data Collection and Tools for Production Management

• Sources of data in production environments (e.g., machines, sensors, workers)
• Tools for data collection: IoT devices, sensors, and data management platforms
• Real-time data monitoring and integration with production systems
• Data storage solutions: Cloud, on-premises, hybrid approaches

Data Analysis Techniques for Production Optimization

• Descriptive, diagnostic, predictive, and prescriptive analytics
• Key performance indicators (KPIs) in production management
• Use of machine learning and AI for data analysis
• Visualizing data insights through dashboards and reports

Implementing Big Data Analytics in Decision Making

• Using big data to identify inefficiencies and optimize production processes
• Real-time decision-making based on data insights
• Predictive maintenance and demand forecasting using big data
• Best practices for integrating big data analytics into production management strategies

1ST BATCH: Tuesday, February 3, 2026 — Friday, February 6, 2026.

2ND BATCH: Tuesday, May 26, 2026 — Friday, May 29, 2026.

3RD BATCH: Tuesday, September 22, 2026 — Friday, September 25, 2026.

The training methodology integrates lectures, interactive discussions, collaborative group exercises, and
illustrative examples. Participants will acquire a blend of theoretical insights and hands-on practical
experience, emphasizing the application of learned techniques. This approach ensures that attendees return
to their professional environments equipped with both the competence and self-assurance to effectively
implement the acquired skills in their responsibilities.