By IndustryIntermediate

AI in Manufacturing

A 70-minute playbook for plant managers and VPs of manufacturing — six shop-floor plays that ship, three pitches that disappoint, and a 12-month roadmap with OEE and quality KPIs (not AI metrics).

70 min·8 chapters·Executive · Director · Manager · Technical practitioner·Free

Last updated: 2026-05-20

What you'll learn

By the end of this course you'll be able to:

The manufacturing-AI fit map — six plays that ship, three pitches that disappoint, the OT/IT bridge filter
Predictive maintenance — sensor coverage decisions + the narrative layer + three project killers
Quality vision AI — three messy-real-world challenges + operator labelling loop + false-confidence discipline
Process optimisation — three AI signals + operator-led experiments + three overfitting guards
Plant-floor supply chain integration — three signal flows + re-planning cadences + three failure modes
Safety AI — three use cases + three safety-specific failures + the line nobody crosses
Digital twin — three targeted twins that ship in 4–6 months + three megaproject traps to refuse
Your 12-month plant AI roadmap — two plays Q1 + ranging in Q2–Q4 + OEE and quality KPIs

Who this is for

Plant managers, VPs of manufacturing, operations directors, plant engineering leaders, and the OT engineers who run the production floor. Especially useful for mid-sized manufacturers in India and GCC industrialising rapidly — and for any plant evaluating AI investment beyond pilot stage.

Curriculum

8 chapters · 2 hands-on exercises · capstone challenge

Each chapter ends with the learning objectives ticked off. Quizzes are auto-graded with feedback; exercises are open-ended and produce artifacts you can take to your team.

1. The manufacturing-AI fit map

9 min

Name the six plays that ship + the three pitches that disappoint on the shop floor
Apply the OT/IT bridge filter (data accessible, data quality usable, culture supports AI)

2. Predictive maintenance for plants

10 minQUIZ

Make three sensor coverage decisions and build the narrative layer for the maintenance engineer
Anticipate and prevent the three project killers most plants hit during deployment

3. Quality vision AI

10 minEXERCISE

Design around the three messy-real-world challenges (lighting, drift, novel defects)
Run the three-stage operator labelling loop and hold the false-confidence discipline

4. Process optimisation with AI

9 minQUIZ

Surface the three signals that produce non-obvious improvements (interactions, drift, best-shift)
Run operator-led experiments with statistical rigor and avoid the overfitting trap

5. Plant-floor supply chain integration

9 min

Wire three signal flows into production scheduling (demand, material/supplier, equipment)
Run the three re-planning cadences and prevent the three integration failure modes

6. Safety AI — augmenting human attention

9 min

Deploy three safety AI use cases (PPE, near-miss, ergonomic) with the support-not-surveillance framing
Hold the line — AI never has final say on safety actions — via written safety AI charter

7. Digital twin — pragmatic, not megaproject

9 minEXERCISE

Build three targeted twins that ship in 4–6 months (critical equipment, bottleneck, operator training)
Refuse the three megaproject traps via three discipline rules

Capstone: Capstone — Your 12-month plant AI roadmap

8 min

Sequence PdM + quality vision in Q1; range process optimisation, supply chain, safety AI across Q2–Q4
Track OEE, unplanned downtime, defect escape rate, team engagement — not AI metrics

Capstone deliverable: Every learner who completes this course produces «Your 12-Month Plant AI Roadmap» — a tangible artifact you take back to your organization.

Interactive Course · Free

Full web-rendered experience available now.

All 8 chapters live with interactive slides, audio narration, mock-exam practice, and cross-device progress tracking. The first two chapters are accessible without an account.

Take the interactive course

References & sources