AI in Industrial Automation
By Raju Karibandi
A six-day, six-hour course for learners with basic AI awareness and limited manufacturing experience. A single fictional biscuit factory connects process understanding, automation, analytics and practical AI use — no coding, live equipment or paid AI account required.
Course Overview
A six-day course — 6 days × 60 minutes = 6 hours — for learners with basic AI awareness and limited manufacturing experience. A single fictional biscuit factory runs through every session, from released ingredients staged for production through inspection, packing and recorded quality disposition, including maintenance, cleaning, utilities and shift work.
6 hours total
6 daily sessions of 60 minutes each
No coding required
No live equipment or paid AI account needed
Guided materials
56-slide deck, instructor guide and workbook
Six-Day Curriculum
Each session blends teaching, practice and review within 60 minutes. Every day ends with a worksheet and exit ticket, and the final project builds on each day's work.
Factory processes and digital transformation
Map the biscuit production process, distinguish automation, digital transformation and AI, and identify a theoretical bottleneck on the line.
Learner output
Process map and bottleneck explanation
Automation and AI-assisted workflows
Explain measurement, control and interlocks, then design an accountable automation sequence alongside an AI-assisted response.
Learner output
Automation and assistant workflow
Analytics and reporting from existing data
Validate records, calculate shift measures, and draft a factual review with traceable evidence and missing-data questions.
Learner output
Calculated shift review
AI for quality and production planning
Evaluate quality-model errors and compare feasible production sequences under changeover and maintenance constraints.
Learner output
Quality evaluation and production schedule
Process optimization and quality improvement
Investigate a loss, design a controlled trial, and distinguish observed improvement from proof of a sustained effect.
Learner output
Trial evaluation and repeat-test plan
Unified platform and practical project
Connect production, quality and maintenance records, then propose a limited pilot with ownership, evaluation and fallback.
Learner output
One-page integrated improvement proposal
Assessment
This is an introductory internal course assessment, not a professional certification. Each criterion is scored 0 (absent), 1 (partly specified) or 2 (clear and workable), with a suggested pass of 7/10 — and no zero allowed for ownership or evaluation and fallback.
Process understanding — clear process, boundary and operational problem
Data and measurement — named records, valid counts, units and comparison
Technical choice — justified rules, analytics, AI or integration
Workflow ownership — named reviewer, decision-maker and action owner
Evaluation and fallback — pilot, acceptance criteria, constraints and fallback
Watch & Learn
To learn more about this session, which was an introduction/orientation conducted during our weekly webinar, watch the video below.
Prefer a quick overview first? Start with the course introduction, then explore the orientation recording and a real-world example of AI in industrial automation.
Course Introduction
A quick walkthrough of what the course covers and how the six days fit together.
Watch on YouTube
Orientation Session
The introduction/orientation conducted during our weekly webinar.
Watch on YouTube
AI in Industrial Automation — Example
A real-world example showing how AI is applied on the shop floor.
Watch on YouTubePricing & Enrollment
Enroll in the AI in Industrial Automation program.
