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PROGRAM 22 · TEAM TRAINING

AI & Data for Manufacturing Professionals

Less downtime, cleaner reports, and a factory that runs on data.

8 sessions3 modules4 hands-on projects3 days · 9 am–5 pmCertificate on completion
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Who this course is for

  • Plant, production and operations managers
  • Quality, maintenance and engineering teams
  • Planning, inventory and supply chain staff
  • Teams in cement, steel, plastics, food processing, packaging and electronics plants

What your team will be able to do

  • Turn daily production logs into clear reports and KPIs
  • Run root-cause analysis and draft CAPA with AI support
  • Analyse downtime, maintenance and quality data in Excel
  • Deploy four working automations on your own plant floor
How it runs

3 days at your office, 8 sessions

Three sessions a day plus a hands-on build lab every afternoon. Day 3 ends with capstone presentations.

Day 1

9:00 am – 5:00 pm

AI chatbots for manufacturing work

9:00–10:30S1Prompt engineering for manufacturing
10:30Tea break
10:45–12:15S2Production reporting & root cause
12:15Lunch & prayer
1:00–2:30S3SOPs, safety & shop-floor training
2:45–4:30LABBuild lab: prompt library on your own files
4:30–5:00Q&A and day recap

Day 2

9:00 am – 5:00 pm

Plant data, then the first two builds

9:00–10:30S4Formulas & factory data cleaning
10:30Tea break
10:45–12:15S5Manufacturing analytics & plant KPIs
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant & alerts
2:45–4:30LABBuild lab: KPI dashboard, assistant and alerts on your data
4:30–5:00Q&A and day recap

Day 3

9:00 am – 5:00 pm

Last two builds and the capstone

9:00–10:30S7Project 03: Maintenance workflow
10:30Tea break
10:45–12:15S8Project 04: Supplier document extraction
12:15Lunch & prayer
1:00–3:00LABCapstone build clinic
3:15–4:30LABCapstone presentations
4:30–5:00Certificates and next steps
Group: 10–40 people from one organisationSame content and projects in both formatsBangla delivery with English technical termsEvery session ends with a deliverable
Curriculum

8 sessions, one build in each

3 modules · 8 sessions · 4 hands-on projects

PART 1AI Chatbots for Manufacturing WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for manufacturing work (SOP drafting, root-cause analysis, shift report summaries, formula help)
  • Free vs paid tiers; a workflow that needs no international payment card
  • Bangla vs English output quality; when to draft in English and translate
  • Which tool for a long document, which for a formula, which for a polished letter

Prompt Engineering Fundamentals

  • What a prompt is; why the same question gives different answers
  • The four-part structure: role, context, task, output format
  • Role prompting: act as a plant manager, quality engineer, maintenance planner or production supervisor
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own manufacturing work
  • Step-by-step reasoning for multi-part tasks such as working through a 5 Whys analysis or comparing machine downtime across lines
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a quality investigation (defect data → fishbone → root cause → CAPA → verification plan) into a sequence of smaller steps

Iteration & Prompt Library Building

  • Why the second prompt matters more than the first; refining instead of restarting
  • Diagnosing a bad output: vague instruction, missing context or wrong tool
  • Building reusable prompt templates for repeated manufacturing tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: product formulations and process parameters, customer drawings and specs, costing sheets, supplier prices, worker personal data
  • Anonymising data before prompting; safe vs unsafe manufacturing use cases
  • Hallucination awareness; verifying every figure, date, name and legal reference
  • The verification rule: AI drafts, a person checks before anything leaves the building
DELIVERABLEa personal prompt library of 10 templates for your repeated manufacturing tasks.
PART 2Manufacturing Data Analysis in Excel & Google SheetsSessions 4–5
PART 3Applied Projects: AI Assistants & AutomationSessions 6–8
Applied projects

Four automations, running in your organisation

01Session 6

SOP & Machine Manual Assistant

Supervisors, operators and maintenance technicians get answers from your SOPs, work instructions and machine manuals, with the section cited.

  1. INSOPs & machine manuals
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

Plant Compliance & Maintenance Alerts

Factory and fire licences, boiler inspections, calibration, BSTI and audit dates checked daily, with alerts 30, 15 and 7 days ahead.

  1. INLicence & maintenance tracker
  2. RUNDaily Make scenario
  3. OUTAlert to the right owner
Built with Make · Sheets · Gmail
03Session 7

Maintenance Request & Breakdown Workflow

Breakdowns logged by form and assigned by machine area and priority, with downtime calculated and repeat breakdowns flagged.

  1. INBreakdown request form
  2. RULESAssignment & priority script
  3. OUTClosed job with downtime logged
Built with Apps Script · Forms
04Session 8

Supplier Document Extraction Pipeline

Supplier invoices, challans and test certificates become clean rows, matched against the purchase order, with off-spec values flagged.

  1. INSupplier invoices & certificates
  2. AIGemini structured extraction
  3. OUTMatched rows in your sheet
Built with Gemini API · Drive

Capstone presentation

Each person presents one automation built for their own workplace.

Day 3 afternoon
Applied across every session

Responsible & Ethical AI in Manufacturing

Fairness & Non-Discrimination

  • Where bias enters manufacturing decisions: data, wording, criteria and past patterns
  • Proxy discrimination: address, age, gender or background inferred indirectly

Privacy & Data Protection

  • Data minimisation: collect only what the decision requires
  • Retention and deletion of worker, supplier and customer data

Worker Safety & Fair Treatment

  • Worker safety comes before output targets in every automated alert
  • Productivity data used to fix processes, not to punish individual workers

Accountability & Human Oversight

  • Human-in-the-loop by design: AI recommends, a named person decides
  • Who owns an AI-assisted decision when it is challenged

Workforce Impact & Your AI Use Policy

  • Talking to manufacturing teams about AI without triggering job-loss fear
  • Reskilling and role redesign as AI absorbs routine work
Outcomes

By the end, your team can

  • Choose the right AI tool and write prompts that work first time
  • Maintain a prompt library covering your repeated manufacturing tasks
  • Turn shift logs into production reports and run root-cause analysis
  • Write SOPs, safety checklists and Bangla training material
  • Calculate OEE and build a plant KPI dashboard
  • Build and deploy automations with Make, Apps Script and the Gemini API
  • Apply fairness, transparency and privacy to every AI-assisted decision

And leaves with

A production report template, fishbone and CAPA draft
An SOP, safety checklist and short training video
A plant KPI dashboard with OEE, quality and downtime
A grounded sop & machine manual assistant your colleagues can use
A plant compliance & maintenance alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own plant or factory

Tools your team will use

Chatbots
ChatGPTGeminiClaudeCopilotDeepSeek
Content
CanvaGammaCapCutGoogle Slides
Data
Microsoft ExcelGoogle SheetsPower Query
Workspace
GmailCalendarMeetFormsDrive
Automation & AI builds
MakeGoogle AI StudioApps ScriptGemini API
Manufacturing tools
Looker StudioCapCutCanvaPower BI basics

What participants need

  • A laptop with Excel and a Google account
  • Basic Excel comfort and a month of production, downtime or quality data from your plant
  • One real work file to practise on from Session 2
  • No coding background required; free tiers only

How your team will learn

  • build-along classes (you work while the trainer works)
  • practise on your own workplace file, not dummy data
  • every session ends with a deliverable
  • Bangla delivery with English technical terms
  • recordings, prompt library and setup guides
  • certificate after capstone submission
Request a proposal

Bring this program to your plant team

Tell us about your team. We reply within one working day with a plan built around your own documents and workflows.

  1. 1 · A short discovery call with your plant lead
  2. 2 · We tailor examples to your masked files
  3. 3 · Offline at your office, or online live classes
Chat on WhatsApp
Request a proposal