New Year Offer End Date: 30th April 2024
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Program

ACCESS THIS PROGRAM UPCOMING WORKSHOPS
MODE
Mode(Online) TYPE
Mentor Based LEVEL
ModerateDates
17 Nov 2025 to 19 Nov 2025Program Length
1hr

Skills you will gain:

About Program:

A fast-paced, 3-day, 90% hands-on program where you’ll build a RoboDK robot cell, stand up an IoT/Digital Twin (OPC UA → MQTT → TSDB), and deploy edge ML for quality, anomaly, and basic RUL. You’ll go from offline programming to live KPIs (OEE, cycle time, energy/unit) with dashboards, alarms, and interlocks. Leave with a working bundle: RoboDK project, twin stack, edge ML services, SOPs, and alert topics—ready to adapt to real energy ops.

Aim: Equip participants to design, connect, and operationalize a full Industry 4.0 pipeline for energy operations—building a RoboDK robot cell, creating a live IoT/Digital Twin, and deploying edge ML for quality, anomaly, and maintenance—so they can go from offline programming to real-time KPIs and actionable decisions.

Program Objectives:

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  • Build & calibrate a collision-safe RoboDK cell; export vendor posts.

  • Execute changeovers (≥2 SKUs); save recipes, cycle reports, SOP.

  • Stand up OPC UA → MQTT with clear JSON topics/schemas.

  • Persist telemetry to a time-series DB; query cycle/energy metrics.

  • Create a live twin dashboard with KPIs, alarms, and recipe control.

  • Implement edge rules (debounce, interlocks, fault→ticket webhook).

  • Engineer features; train & deploy quality/anomaly/RUL models at the edge.

What you will learn?

📅 Day 1 – RoboDK Cells (Offline → Online)

  • Concept sprint: Robot cell basics for energy ops (pick-place, torqueing, inspection), safety envelopes, and tool frames
  • Build a RoboDK cell (robot + turntable + fixtures) for an energy asset task (e.g., valve assembly or inverter heat-sink placement)
  • Calibrate TCP & reference frames; import CAD (STEP) and create targets/paths with collision checks
  • Add sensors and IO stubs; map gripper open/close and torque gun signals
  • Generate offline programs (UR/KUKA/FANUC post); simulate cycle time & reach; export cycle report
  • Create a changeover: parametrize path for two SKUs; save recipe files and a quick SOP

📅 Day 2 – IoT Twins & Edge Connectivity

  • Concept sprint: What is an IoT/Digital Twin for a cell/line; OPC UA vs MQTT; time-series stores
  • Spin up an OPC UA server for the robot cell (simulated tags: pose, IO, cycle_ok) and browse with a client
  • Bridge OPC UA → MQTT; publish twin topics (cell/status, robot/pose, quality/ok) using JSON schema
  • Ingest to a time-series DB (InfluxDB/Timescale) and persist recipe/cycle/energy metrics
  • Build a lightweight digital twin dashboard (Node-RED/Streamlit): live KPIs (OEE, cycle time, energy per unit), alarm banner, and recipe selector
  • Implement edge rules: debounce a sensor, create an interlock (door_open ⇒ robot_hold), and test a “fault → maintenance ticket” webhook

📅 Day 3 – ML Analytics for Quality, Anomaly & Maintenance

  • Concept sprint: Framing anomaly vs quality classification vs RUL; labeling and drift
  • Build a feature table from Day-2 streams (cycle-level stats, torque traces, robot current, temperature)
  • Train a quality classifier (gradient boosting) for pass/fail based on torque/current signatures; interpret using SHAP
  • Train an anomaly detector (isolation forest/autoencoder) on robot/IO telemetry and set calibrated alert thresholds
  • Estimate Remaining Useful Life (RUL) using survival/Weibull fit for a consumable (gripper pad) with cycle counts and peak force
  • Deploy models at the edge (Docker container): subscribe to MQTT, score in real time, publish alerts and update twin dashboard with trends
  • Create a runbook: alarm triage, false-positive guardrails, rollback switch; export a one-page “ops playbook”

Mentor Profile

Fee Plan

INR 1999 /- OR USD 50
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Intended For :

Robotics & automation engineers (RoboDK/UR/KUKA/FANUC-curious)

OT/Controls engineers & IoT/Edge architects (OPC UA, MQTT)

Data/ML engineers & applied scientists in manufacturing/energy

Production/quality leaders exploring OEE, predictive maintenance

Final-year students & researchers in Robotics/IIoT/AI (project-focused)

Career Supporting Skills

Program Outcomes

  • Build & calibrate a collision-safe RoboDK cell and generate vendor posts.

  • Parameterize changeovers for ≥2 SKUs; export cycle reports, recipes, and an SOP.

  • Stand up OPC UA → MQTT with clear JSON topics/schemas and persist to a TSDB.

  • Build a live digital twin dashboard with KPIs (OEE, cycle time, energy/unit) and alarms.

  • Engineer features, train quality/anomaly/RUL models, and explain via SHAP.

  • Containerize & deploy models at the edge to score in real time and publish results.

  • Implement edge rules (debounce, interlocks, fault→ticket webhook).

  • Deliver a working bundle (cell project, twin stack, ML services, SOPs, alerts, KPIs).

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