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DSTC-DTWIN-2608 Open Online Post-Doctoral / Specialized 3 Days · Live + Recorded

Digital Twins: Predictive Modeling for Dynamic Industrial Processes

by - DSTC

Build data-driven digital twins to monitor, simulate and optimize industrial processes.

Starting from ₹1,999+GST

Register Now

Core Parameters

Level:
Post-Doctoral / Specialized
Duration / Workload:
3 Days · Live + Recorded (12 Hrs Total)
Venue Mode:
Online
Prerequisites:
PhD candidates, postdoctoral researchers, academic faculty, and industry R&D teams.

📅 Important Schedule Dates (Tentative)

Session Commencement (Tentative):
26 Aug 2026 · 5:30 PM IST
Session Conclusion (Tentative):
28 Aug 2026 · 5:30 PM IST
Enrollment Deadline (Tentative):
25 Aug 2026
Schedule Note: This schedule is tentative and subject to minor adjustments. Once the program registrations go live, all finalized dates and times will be sent to registered interest leads.

🎯 Program Aim

This workshop teaches the design of digital-twin models that fuse physics and machine learning to monitor, predict and optimize dynamic industrial processes.

📋 Workshop Objectives

Understand digital-twin architecture and data flows
Fuse physics-based and data-driven models
Implement predictive maintenance models
Simulate what-if scenarios
Connect twins to real-time sensor streams

👥 Who Should Enroll?

Process and manufacturing engineers
Industrial IoT and automation teams
PhD scholars in control and systems
Operations and reliability analysts

🚀 Key Learning Outcomes

A working digital-twin prototype
Predictive-maintenance model skills
Scenario-simulation capability
Verified e-Certificate of Industrial Competency

💎 What You'll Gain from this Program

🎥
Live & Recorded Sessions
Lifetime access to class recordings
🎓
e-Certificate upon Completion
Cryptographically verified credentials
💬
Post-Workshop Query Support
Direct chat access to mentors & council
💻
Hands-On Learning Experience
Step-by-step Jupyter notebooks & code

Curriculum Outline

Day 1 Architecture

Twin Foundations

Digital-twin concepts, data pipelines and sensor integration.

Day 2 Modeling

Hybrid Models

Physics + ML fusion, surrogate models and predictive maintenance.

Day 3 Optimization

Simulation & Control

What-if simulation, optimization loops and real-time deployment.

Build data-driven digital twins to monitor, simulate and optimize industrial processes.

This workshop teaches the design of digital-twin models that fuse physics and machine learning to monitor, predict and optimize dynamic industrial processes.

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Scholar Registration

For scholars whose department, college or employer pays the fee. We raise a proforma invoice to your institution; you attach the signed processing letter or bank slip.

The proforma invoice is emailed here as well as to you.
📄 Upload Sponsorship Slip / Letter

Signed letter on official letterhead, or the bank transfer slip. PDF/JPG/PNG, up to 5 MB.

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