Enlarge Image AI and predictive maintenance in industry
A talk on applying AI to manufacturing and machine maintenance, connecting data, sensors and team preparation before a project begins.
FROM CHALLENGE TO DELIVERY
Consulting and designing AI/IoT system
We help define your requirements, assess readiness and design AI / IoT systems or custom hardware before investment, with prototype planning, concept testing and knowledge transfer through talks, workshops or coaching so your team can continue the work.
Suitable for: Organizations with specialized requirements that are unsure which cameras, sensors or software to use, need prototypes before full investment, or need system designs and specifications for procurement or budget requests.
Embedded systems (ATmega/ESP32/K210)PCB designPrepare hardware for testing within the project scopePythonOpenCV
CONSULTING · DESIGN · KNOWLEDGE TRANSFER
A clear system plan, with your team ready to move forward
We help management and on-site teams align on the challenge, from data assessment and system and prototype design to workshops and knowledge transfer, giving your team a trial plan and decision criteria before investment.
- 01
Assess requirements and readiness
Discuss with management and technical teams to identify problems, available data, constraints and opportunities to prioritize.
Clear requirements and priorities suited to your organization - 02
Design the system and trial plan
Agree on the architecture, prototype scope, feasibility and test criteria together.
A system design and pilot plan within the agreed scope - 03
Transfer knowledge to your team
Choose talks, workshops or coaching suited to executives, engineers and system users.
Exercises, documentation and a plan for further action
From industry events to working with your team
Our experience in speaking, training and knowledge exchange helps us tailor communication to management, technical teams and system users.
Enlarge Image 
Enlarge Image Developing AI skills for personnel
Explain concepts so learners can see how to apply them at work, then extend them into workshops tailored to each team's role.
See more training photos
Enlarge Image 
Enlarge Image 
Enlarge Image Explore the details before designing the work together
Sample materials from talks and knowledge transfer. Select an image to view details and discuss relevant topics with our team.
Enlarge Image AI for manufacturing
An example linking machine temperature, sound, vibration and image data to a processing system to explain AI system design approaches.
Speaker: Piyorot Khongchuay
View enlarged document image
Enlarge Image Machine data and maintenance
Select data and measurement points relevant to machine symptoms, and discuss model evaluation and team preparation before a real trial.
Speaker: Piyorot Khongchuay
View enlarged document image
Enlarge Image Hand over systems to users and technical teams
Explain role-based operations alongside system structure and data flows so the receiving team understands both usage and maintenance.
Speakers in the materials: Watcharapol Duangjit and Noppadon Khongchuay
View enlarged document image
Enlarge Image Design interfaces and prototypes with Figma
Learn UX/UI and Atomic Design fundamentals, practice wireframes, Auto Layout and components, then assemble interfaces and prototypes.
Instructor in the document: Chanthana Suwannakhet
View enlarged document imageThese materials show examples from previous work. We tailor the topics, data and practical exercises to your project.
Choose a topic and tailor it to your team
Proposed course and workshop frameworks. Duration, content and deliverables are adapted to participants' backgrounds, the data used and the jointly agreed scope.
01AI for executives and organizational transformationEXECUTIVE AI & INDUSTRIAL TRANSFORMATION
Builds on experience presenting industrial AI
- Suitable for
- CEO, Plant Director, COO, Digital Transformation Office, HRD
- Objective
- Help executives understand AI's impact on quality, cost, decision speed and organizational readiness.
- Learning topics
- Overview of AI/ML/GenAI relevant to business and industry
- Map AI opportunities across production, procurement, maintenance, quality and management
- A use-case selection framework based on business impact, data readiness and feasibility
- AI governance, human oversight, data confidentiality and investment prioritization
- Build a 30/60/90-day roadmap and pilot success criteria
- Proposed activity
- Gather departmental challenges and prioritize them in an opportunity matrix
- Proposed deliverables
- Executive use-case map, quick-win roadmap and project kickoff questions
- Recommended duration
- Executive briefing of 2–3 hours or 1 day
02AI for everyday work and responsible useAI FOR WORKPLACE PRODUCTIVITY & RESPONSIBLE USE
Newly proposed course for generative AI work
- Suitable for
- HRD/L&D, supervisors, sales teams, project officers, office staff
- Objective
- Improve AI literacy and design workflows that increase productivity while controlling data risks.
- Learning topics
- AI/generative AI fundamentals and business use cases
- How to define tasks and write structured prompts
- Use AI for documents, meeting summaries, organizing data and communication
- Verify accuracy, reduce hallucination risks and protect customer data
- Design workflows before and after AI adoption, with ways to measure results
- Proposed activity
- Practice 2 real work cases for each department and present the before/after comparison
- Proposed deliverables
- Sample workflows, a team prompt library and a personal action plan
- Recommended duration
- 1 day for fundamentals or 2 days in small groups
03Machine health analytics and maintenance planningPREDICTIVE MAINTENANCE & MACHINE HEALTH ANALYTICS
Builds on predictive maintenance presentation materials
- Suitable for
- Maintenance Manager, Reliability Engineer, Production Engineer, Automation Team
- Objective
- Develop a data-driven approach to anticipate anomalies, reduce downtime and connect findings to maintenance plans.
- Learning topics
- Maintenance strategy, failure modes and downtime costs
- Data sources: vibration, current, temperature, alarm logs and production data
- Data cleaning, feature engineering and health indicators
- Anomaly detection, classification, forecasting and threshold setting
- Model evaluation, false alarms, deployment, monitoring and retraining
- Proposed activity
- Analyze simulated machine data or data properly prepared by the customer
- Proposed deliverables
- Data readiness checklist, health KPI sheet and predictive maintenance pilot canvas
- Recommended duration
- 2 days, with optional additional data assessment activities
04Computer vision for quality control and automationCOMPUTER VISION FOR QUALITY CONTROL & AUTOMATION
Course proposed from system development experience
- Suitable for
- QA/QC, Quality Engineer, Production/Process Engineer, R&D, Automation Engineer
- Objective
- Understand how to build automated visual inspection systems suited to quality requirements and production timing.
- Learning topics
- Camera, lighting, lens, trigger and reference image fundamentals
- Image preprocessing, segmentation, features and dataset preparation
- Inspection use cases: surface defects, color, counting, OCR/OCV and dimensions
- Precision, recall, false rejects, false accepts and sampling
- Concept architecture: camera–edge–PLC/MES and on-site testing
- Proposed activity
- Design a QC vision pilot at 1 point, with failure scenarios and acceptance criteria
- Proposed deliverables
- Vision requirements sheet, image collection checklist and PoC plan
- Recommended duration
- 2 days + demo/pilot within the agreed scope
05Smart factories, industrial IoT and production dataSMART FACTORY, INDUSTRIAL IoT & PRODUCTION DATA
Course proposed from factory expertise
- Suitable for
- Plant Manager, IE, IT/OT, Production, Continuous Improvement
- Objective
- Assess factory readiness and design a step-by-step approach to using data to improve productivity.
- Learning topics
- Industry 4.0/smart factories and business challenges
- Sensors/edge/PLC/SCADA, data collection and networking
- OEE, availability, performance, quality and visualization
- Data integration and secure OT/IT connectivity
- Opportunity roadmap, success metrics and pilot prioritization
- Proposed activity
- Build a plant data map and select the most worthwhile pilot use case
- Proposed deliverables
- Smart factory assessment canvas, data point register and roadmap
- Recommended duration
- 1–2 days or pre-assessment + workshop
06Practical machine learning and data analyticsPRACTICAL MACHINE LEARNING & DATA ANALYTICS
Course proposed from machine learning materials and exercises
- Suitable for
- Data Analyst, Engineering, Business Analyst, Developer, IT Team
- Objective
- Enable teams to build basic data models and interpret evaluation results correctly.
- Learning topics
- Define the business problem and data inventory
- Exploratory data analysis, missing values, duplicates and outliers
- Feature engineering, classification, regression and clustering
- Train/validation/test splitting, cross-validation and data leakage
- Model metrics: precision, recall, F1, ROC-AUC, MAE/MSE
- Proposed activity
- Build a notebook from data cleaning → modeling → model evaluation
- Proposed deliverables
- Sample notebook, evaluation sheet and guidelines for preparing real data
- Recommended duration
- 2–3 days of hands-on practice
07UX/UI and design systems with Figma 101UX/UI DESIGN SYSTEM WITH FIGMA 101
Backed by Figma experience and a course outline
- Suitable for
- UX/UI Designer, Product Owner, Developer, Business Analyst, software teams
- Objective
- Improve interface and component system design skills to help reduce inconsistencies in system development.
- Learning topics
- User journeys, user flows, wireframes and UX fundamentals
- Figma frames, grids, typography, colors, assets and alignment
- Atomic Design, components, styles and Auto Layout
- Responsive design, variants, interaction and prototyping
- Design system governance, feedback and developer handoff
- Proposed activity
- Design 1 process flow and build a component library and prototype
- Proposed deliverables
- Figma project file, design system starter and handoff checklist
- Recommended duration
- 1–2 days
08System user training and handover to support teamsDIGITAL PLATFORM TRAINING & SYSTEM HANDOVER
System knowledge transfer materials available for users and technical teams
- Suitable for
- End Users, System Admin, Project Owner, Operations Staff, IT Support
- Objective
- Build understanding of the system, from permission-based use to the structure needed for maintenance and further development.
- Learning topics
- Overview of business processes, user roles and workflows
- Use each module with scenarios relevant to actual work
- Network, system, data flow and database diagrams
- Frontend/backend/API/open data and external integrations
- Incident reporting, FAQ, UAT and knowledge transfer to the receiving team
- Proposed activity
- Role-based exercises for 3–5 user roles and an admin team workshop
- Proposed deliverables
- User guide, admin handover, known-issue log and training attendance template
- Recommended duration
- 1 day for users + 1 day for technical teams
09Medical device risk management fundamentalsMEDICAL DEVICE RISK MANAGEMENT AWARENESS
Delivered with standards specialists within the agreed scope
- Suitable for
- QA/RA teams, R&D, Product Engineers, Medical Device departments
- Objective
- Understand risk management frameworks and the documents used for cross-functional communication on product safety.
- Learning topics
- Risk management definitions and principles in the medical device context
- Hazards, hazardous situations, harm and risk estimation
- Risk evaluation and analysis of risk control options
- Residual risk, review, traceability and monitoring
- Sample risk files, risk worksheets and evidence-related precautions
- Proposed activity
- Practice identifying hazards in a hypothetical product and planning risk controls
- Proposed deliverables
- Sample risk worksheet and training takeaways
- Recommended duration
- Half a day to 1 day, with a standards specialist instructor
10Project management and digital process improvementPROJECT MANAGEMENT & DIGITAL PROCESS IMPROVEMENT
Course proposed from project management expertise
- Suitable for
- Project Manager, BA, System Analyst, Operations Excellence, Digitalization teams
- Objective
- Clarify project scope, manage change and enable effective knowledge handover.
- Learning topics
- Problem statements, stakeholder mapping, scope and requirements
- BPMN, process mapping, system analysis and UAT
- Work breakdown, milestones, risk register and communications
- Procurement, cost, quality and change control
- Implementation planning, handover and continuous improvement
- Proposed activity
- Create a project charter + BPMN for 1 process + a risk register
- Proposed deliverables
- Project starter kit, scope checklist, UAT plan and action tracker
- Recommended duration
- 1–2 days
Start with a talk, workshop or consulting project
Choose a format suited to your organization's decisions and team readiness, then agree on the scope before starting.
45–180 minutes
Executive overview talk and discussion
AI applications and industry examples, with Q&A and slides tailored to your work.
1–2 days
In-house training
Assess learners' backgrounds, set objectives, practice and summarize learning for the selected topics.
2–3 days
Technical workshop
Use simulated data or data appropriately prepared by your organization for exercises, readiness assessment and pilot planning.
Estimated according to project scope
Consulting and pilot planning
Start with requirements, assess feasibility, design the system and test criteria, and provide coaching so your team can continue.
Tell us your goals, stakeholders and available data. We help shape a system design approach or course outline suited to your organization.
Discuss your needs and request a scope of workWork Illustration
Why start with a system diagram before detailed design?
A system diagram aligns users, technical teams and management on the scope, from receiving parts and processing to screens and reports. We designed 1 MVDeep prototype machine that reports Cpk (process capability index) to help select cameras, lenses and lighting, under a Thai government prototype machinery development project in 2019–2020. The project targeted at least 100 reports per 8 hours, and its final report records that testing met this target. Setting numerical targets from the outset makes acceptance criteria clear. Your design work therefore starts with a system diagram and jointly agreed test criteria.
What to prepare for an assessment
- Roles and backgrounds of the team working on the project or attending the workshop, participant count and suitable times
- Data or sample parts for trials, with data usage or confidentiality conditions
- The problem to solve and project goals
- Current workflows, constraints and budget if available
Scope, schedule and pricing
Estimated from complexity, design scope and the need for prototypes
Before work starts, our proposal sets out the schedule, inclusions, exclusions and costs. Additional work requires a joint scope assessment.
View deliverables ↓
Technical capabilities we have developed
- Design custom machine vision systems for inspecting, sorting, counting and measuring parts by type, model, color and pattern.
- Design and develop hardware, and assess standards testing within the agreed scope.
- Design mechanisms and control cabinets for specialized inspection systems.
- Consulting on transition planning toward Industry 4.0
What you receive
- Project proposal with technical specifications
- Custom system, circuit or mechanism designs within the agreed scope
- A prototype for concept testing, when included in the scope
- Study, design or test reports
- Trial plans and criteria for assessing data or system readiness within the agreed scope
- Course outline, exercises and an application plan when training or workshops are included in the scope
Suitable for: Organizations with specialized requirements that are unsure which cameras, sensors or software to use, need prototypes before full investment, or need system designs and specifications for procurement or budget requests.
Our process
1
Understand your requirements
Listen to the problem, on-site constraints and budget, then jointly define requirements and measurable goals.
2
Design
Select an approach and design the system, circuits or mechanisms with technical specifications.
3
Prototype development and testing
Build a prototype and test it with real parts or data to reduce risk before full investment.
4
Handover
Deliver designs, documentation and test reports, and explain the results to management and the teams that will use the system.
Frequently Asked Questions
Can consulting and team training be included in the same project?
Yes. We assess requirements, design the system approach and plan workshops or coaching suited to your team. Participants, data, deliverables and test criteria are agreed before work starts. Course durations are recommendations; pilot work is estimated separately according to complexity.
Can we consult you if our requirements are still unclear?
Yes. We first listen to the actual problems and constraints on site, then help clarify requirements before proposing a design approach. Some problems only need sensors or predefined rules; AI is not always necessary.
What custom systems has Inspektion designed?
We designed and developed 2 DSIS can seam inspection machines for a Thai metal can manufacturer in 2016–2017 under a government-supported project. We also developed a prototype digital electrical appliance waste registry for 6 stakeholder groups for a government agency in 2021, and designed the IDB9 isolation board, which a gauge and measurement system manufacturer reordered in multiple batches during 2018–2022. DSIS users requested 4 rounds of changes after installation, so your project plan should include post-installation revision rounds from the outset.
How long does custom design work take?
It depends on the complexity of the mechanisms and system. For example, the MVDeep prototype project began in fiscal year 2019 and was presented for final acceptance in July 2020. We estimate your timeline after reviewing the requirements.
What documents are delivered at project completion?
Documents depend on the scope, such as proposals, system designs, test reports and user manuals. We agree on the list before work starts. Our past government prototype projects included work plans, progress reports and final reports.
When is consulting and design not the right service?
This service is not suited to projects that already have specifications and selected equipment and only need installation. Our system installation service is a better fit for those cases. Prototypes from this service are for testing concepts, not machines immediately ready for production lines.
