AI for Manufacturing is a course in using AI for factory and production work, from writing SOPs and work instructions to analysing output and downtime, root-cause analysis with 5-Why, maintenance and safety records and production planning. It suits production engineers and supervisors, QC/QA staff, maintenance and safety teams and plant managers.
Factories and manufacturing work are full of documents, data and routine tasks: creating and improving SOPs and work instructions, recording and analyzing production data, finding the causes of defects and downtime, preparing shift and monthly reports, maintenance and safety work, and production and inventory planning. These tasks are time-consuming, demand high accuracy and are often spread across many systems and spreadsheets. Generative AI greatly reduces the time spent on document and analysis work so factory teams work faster, to one standard, and have more time to focus on real process improvement. This course is designed to help factory and manufacturing teams use AI
in real work confidently and safely, covering the whole process, from documents and SOPs, analyzing production and quality data, maintenance and safety work, production and supply chain planning, setting up shop-floor assistants and a factory knowledge base, to automation with n8n, plus practices for accuracy, data security and protecting trade secrets and data under PDPA. All content is taught through workshops on real factory tasks, finishing with a capstone project where learners set up an end-to-end AI toolkit for their own work. (2 days, 6 hours per day, 12 hours in total, Beginner to Intermediate level, no AI or programming background required.)
Course Details
A 2-day course, 6 hours per day (12 hours in total), delivered as a hands-on workshop with a capstone project. Beginner to Intermediate level, no AI background required. Learners take home a factory prompt library, a shop-floor assistant (Custom GPT/Gem), SOP templates, PM checklists and sample production reports, and a data security and PDPA checklist.
Section 1: AI in Factory and Manufacturing Work
Section 2: Effective Prompts for Factory Work
Section 3: SOPs and Work Instructions with AI
Section 4: Analyzing Production Data with AI
Section 5: Quality and Defect Analysis
Section 6: Maintenance and Safety Work
Section 7: Production and Supply Chain Planning
Section 8: Shop-floor Assistants and Factory Knowledge Base
Section 9: Factory Automation with n8n
Section 10: Accuracy, Data Security and PDPA
Section 11: Capstone Project and Real-world Adoption
No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770
Describe the shop-floor process to the AI as it really happens, by typing, transcribing a voice recording or attaching existing documents, and include the machines, materials, quality checkpoints and safety precautions. Ask the AI to arrange it into an SOP using your organisation's template, with short, actionable steps and a supporting checklist. Finally have the supervisor and the operators who do the job review it before it is issued.
5-Why means asking why repeatedly, starting from the visible problem, until you reach a root cause that stops the problem recurring when fixed. For example, parts are scratched because the die is worn, because it was not replaced on schedule, because there is no clear PM plan. AI can take defect data and shop-floor notes, suggest possible causes at each level and questions to check next, but the team must confirm each cause with real evidence.
OEE, overall equipment effectiveness, measures how productive a machine really is. It is calculated as availability multiplied by performance multiplied by quality. Availability is actual running time against planned time, performance is actual speed against standard speed, and quality is good parts against total parts produced. Looking at the three separately shows whether to focus on downtime, speed losses or defects.
It suits production and planning engineers and supervisors, QC and QA staff, maintenance and safety teams, plant managers who want to set up AI use for their teams, and manufacturing SME owners. You need general computer skills, basic Excel or Google Sheets use and an understanding of your own production process. No AI or programming knowledge is required.
You will be able to use AI to write and improve SOPs and work instructions, analyse output, defect and downtime data with checked figures, find root causes with 5-Why, prepare maintenance records, PM plans and safety documents, support production planning, set up shop-floor assistants with Custom GPTs or Gems and automate alerts with n8n while protecting trade secrets. Participants who complete the training receive a Certificate of Completion with its own number, which can be verified online.
Yes. It can be run in-house for your plant team, with examples adapted to your own work, such as your real SOPs, production reports and maintenance records, along with agreed safeguards for confidential information. You can request a quotation from this page, or contact us on LINE @itgenius or by phone on 02-570-8449.
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