Edge Computing for Smart Manufacturing Corporate Training
Deploy edge computing on your factory floor with OT-hardened skills and real production data.
Build the edge deployment skills your OT and IT teams need. Edstellar's Edge Computing for Smart Manufacturing corporate training program helps your engineers master edge architectures, OT connectivity, and edge AI through instructor-led hands-on labs built around real-world factory use cases. As the corporate training company enterprises trust for emerging-technology programs, we tailor every session to your plants, equipment, and digital roadmap.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build edge-ready manufacturing teams
THE EDSTELLAR EDGE COMPUTING CAPABILITY MODEL
Baseline edge readiness
Assess how your engineers rate edge concepts, OT connectivity, and the latency problems they already face.
Set one edge standard
One shared language for edge architectures, data pipelines, and deployment across OT and IT teams.
Build hands-on fluency
Guided labs deploy edge nodes, wire OPC UA and MQTT data flows, and run inference on real factory-style data.
Prove the edge lift
Before-and-after labs measure each engineer's ability to design, deploy, and secure an edge workload.
Scale across your plants
One edge program rolls out across sites and shifts as your smart manufacturing footprint grows.
Need more than one program?Get a group quote
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Program Overview: What is Edge Computing for Smart Manufacturing Corporate Training?
Edge Computing for Smart Manufacturing trains manufacturing and OT teams to deploy edge computing on the factory floor. It is built for plant engineers, automation specialists, and IT/OT leads modernising production sites. The program covers edge foundations for manufacturing, edge hardware and reference architectures, OT connectivity with OPC UA, MQTT and time-sensitive networking, edge data pipelines, edge AI, and security at scale.
Training runs over 16 hours in applied lab sessions. Teams configure edge reference architectures, connect OT protocols, build stream-processing pipelines, and deploy machine vision inference in guided labs. Instructors with factory-floor experience review every design, checking it against production realities like latency and downtime windows. Practice builds through connectivity and failure scenarios where teams keep edge systems running. The program closes with an integrated edge deployment exercise across a simulated production line.
Smart manufacturing pilots stall when edge projects stay in IT: unclear OT ownership, insecure devices, and data pipelines nobody maintains. The factory cannot afford experimental downtime. This program teaches teams to deploy edge computing the production way, with reference architectures, secure connectivity, and operations that scale.
The closing exercise is a full edge deployment for a simulated production line: teams deliver the hardware architecture, OT connectivity design, streaming pipelines, and a machine vision inference running at the edge, with a security and scaling plan. Your engineers leave with a reference deployment they can adapt to their own plants.
Across six modules, your engineers move from edge foundations to a live edge deployment plan. Sessions use real-world factory scenarios, OT data pipelines, and edge AI workloads, so every skill transfers directly to your plants.
Delivered as a hybrid instructor-led program, it fits around your shifts and plant schedules. Your cohort builds a tailored edge roadmap, with the same curriculum and lab outcomes in every delivery mode.
What's Included in this Workshop for Your Enterprise Teams
- 1
Edge foundations
Edge computing concepts mapped to factory workloads.
- 2
Hardware and architectures
Pick edge hardware and reference designs for the floor.
- 3
OT connectivity
Wire OPC UA, MQTT, and time-sensitive networking.
- 4
Data pipelines and edge AI
Stream OT data and run inference at the edge.
- 5
Security and capstone
Secure the deployment and plan your pilot.
- Training delivered at any of your offices globally
- 10+ languages
- Schedule around your calendar
- Group size set along with you
- Run as one cohort or split into batches
- Instructor-led (virtual/onsite/hybrid)
- Recurring and annual options
- Trainer sourcing, matching and logistics
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
- Plan from 2000+ Industry-ready Training Programs
- Hands-On Labs on Live Infrastructure, Led by Industry Experts
Edge Computing for Smart Manufacturing Course Topics and Program Outline
Six modules follow a clear learning path from edge foundations to a live deployment capstone. Each session builds on the last, with hands-on labs that turn edge concepts into factory-floor capability.
Built by Edstellar with edge computing and OT engineering practitioners
Built by engineers who deploy edge computing systems on factory floors and industrial plants in production, shaped around your stack and use cases.
Baseline each participant's edge computing readiness before module 01 begins
Build strong edge computing foundations in instructor-led sessions for your team
Reinforce skills through guided hands-on labs on edge gateways, OPC UA, and TinyML
Apply edge computing skills to real-world scenarios and a capstone deployment project
A short pre-training assessment sets each participant's entry level, so the program starts where your team actually is. The rest is weighted toward hands-on practice: guided edge gateway and stream-processing labs, TinyML inference exercises, and realistic scenarios drawn from your team's work, not slides.
Delivered as
Entry level set by the assessment. Depth and schedule customized to your team.
Assess your team's edge readiness and map the latency-sensitive workloads in your own plants.
learna)Why edge: latency, bandwidth, and autonomy on the factory floor
b)Edge vs cloud vs fog: where each workload belongs
c)Latency budgets for real-time control and monitoring
d)Factory workloads that win with edge computing
e)Edge readiness assessment for your plants
Compare edge gateway, server, and ruggedized designs and select the right hardware for a factory scenario.
learna)Edge hardware landscape: gateways, servers, accelerators
b)GPU and AI accelerators at the edge
c)Ruggedized and industrial-grade edge devices
d)Reference architectures for smart factories
e)Sizing compute, storage, and power for the floor
Configure an OPC UA server and MQTT broker, then route sensor data through a live pub-sub flow.
practicea)OPC UA fundamentals for industrial interoperability
b)MQTT topics, brokers, and message patterns
c)Time-sensitive networking for deterministic control
d)IT-OT network design and segmentation
e)Hands-on lab: connect a sensor stream to the edge
Build a streaming pipeline that cleans, aggregates, and routes OT telemetry in near real time.
practicea)Edge data lifecycle: ingest, process, store, forward
b)Stream processing engines for the edge
c)Manufacturing data architecture and OT DataOps
d)Historian integration and data contextualization
e)Hands-on lab: stream and transform live OT data
Deploy a machine vision model to an edge device and tune inference for latency and accuracy.
practicea)Running inference at the edge: frameworks and runtimes
b)TinyML: models on microcontrollers and sensors
c)Machine vision for quality inspection and monitoring
d)Model optimization: quantization and pruning
e)Hands-on lab: deploy vision inference to the edge
Design a secure, scalable edge deployment plan for a smart manufacturing pilot in your own plant.
applya)Edge security: zero trust, certificates, and patching
b)Fleet management and remote operations of edge nodes
c)IEC 62443 essentials for edge deployments
d)Capstone: your edge deployment plan for a pilot line
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Your engineers will leave able to design edge architectures, connect OT systems, and run edge AI on the factory floor. Each outcome is practiced in hands-on labs and shown in the capstone.
Design edge architectures
Place workloads at edge, fog, or cloud based on latency budgets and factory constraints.
Select edge hardware
Size gateways, servers, and accelerators for rugged factory environments and real workloads.
Connect OT systems
Wire OPC UA, MQTT, and time-sensitive networking between machines and edge nodes.
Build edge data pipelines
Stream, clean, and contextualize OT telemetry with near real-time processing.
Run edge AI inference
Deploy vision and TinyML models at the edge and tune them for latency and accuracy.
Secure edge deployments
Apply zero-trust principles, certificates, and IEC 62443-aligned practices to edge nodes.
Operate edge at scale
Manage edge fleets remotely and plan a pilot deployment for your own plants.
Teams that Benefit from this Edge Computing for Smart Manufacturing Group Training
This program is built for OT and IT teams deploying edge computing in manufacturing, from automation engineers to plant IT and reliability teams. Basic networking and plant systems familiarity helps; content adapts to each cohort, so every engineer practices the edge work their role actually owns.
Run edge where the machines are.
Automation engineers master edge architectures, OPC UA and MQTT connectivity, and edge AI, so factory systems respond in real time.
Workflow friction
- Latency from cloud round-trips slows control loops
- OT data stays locked in siloed controllers
- New edge hardware is hard to evaluate
How the program helps
- Cut control latency with edge placement
- Unlock OT data for real-time use
- Specify edge hardware with confidence
Practice use cases
- Edge node deployment
- OPC UA and MQTT integration
- Machine vision pilots
Own the edge infrastructure behind digital manufacturing.
Plant IT teams learn to design, secure, and operate edge infrastructure that keeps production data flowing and available.
Workflow friction
- IT and OT networks do not converge cleanly
- Edge fleets grow without management standards
- Security gaps at the edge go unnoticed
How the program helps
- Converge IT and OT networks safely
- Manage edge fleets with remote operations
- Secure edge nodes with zero trust
Practice use cases
- Network design
- Fleet management
- Security hardening
Turn machine data into predictive action.
Maintenance engineers learn to stream and process equipment data at the edge, so predictive models act on the floor, not in the cloud.
Workflow friction
- Equipment failures get spotted too late
- Cloud analytics are too slow for critical assets
- Sensor data never reaches the models
How the program helps
- Detect faults in near real time
- Run predictive models at the edge
- Route sensor data to the right models
Practice use cases
- Condition monitoring
- Predictive maintenance
- Anomaly detection
Each cohort works through role-relevant hands-on labs, then leaves with an edge deployment plan for day-to-day plant work.
Prerequisites: Participants benefit most with basic familiarity with industrial networks, plant automation, or IT infrastructure. No prior edge computing experience is required; foundations are covered from the ground up and the program adapts to mixed OT and IT backgrounds.
Automation Engineer to Smart Manufacturing Edge Sponsor
The program takes engineers from edge basics to production-ready deployments: foundation architectures and hardware, intermediate OT connectivity and data pipelines, then advanced edge AI, security, and a deployment capstone.
Engineers grow from understanding edge concepts to owning edge deployments in manufacturing as the modules progress.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Every mode is shaped around your plants and equipment before delivery. The curriculum, hands-on labs, and capstone stay the same in each format, so what your engineers can do after training never depends on how you run it.
Hybrid Training
Live instruction across office and remote sessions, with hands-on labs coached throughout. Your engineers deploy edge nodes, wire OT connectivity, and run edge AI with instructor guidance. Best for multi-site manufacturing teams.
- Live instruction across office and remote sessions
- Hands-on labs with instructor coaching
- Real factory scenarios and OT data flows
- Best for OT and IT teams across sites and shifts
Onsite Training
Your instructor delivers at your facility, with labs set up for your plants and equipment. Participants build edge data pipelines, deploy inference, and draft their capstone plan with direct coaching. Best for co-located plant teams.
- Instructor delivers at your facility
- Labs set up for your plants and equipment
- Direct coaching during lab work
- Best for teams wanting maximum hands-on time
Live Virtual Training
Live virtual sessions on Zoom or Microsoft Teams, with remote access to the edge lab environment and screen-shared guidance through every task. Your engineers collaborate on architectures and pipelines in real time. Best for distributed OT and IT teams.
- Live sessions on Zoom or Microsoft Teams
- Remote access to the edge lab environment
- Screen-shared guidance through every task
- Best for distributed engineering teams
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size, preferred dates, and delivery mode in the lead form. We reply with a tailored proposal covering scope, schedule, and pricing for your group.
Both. Choose live virtual sessions on Zoom or Teams, onsite delivery at your plant or office, or a hybrid mix across sites and shifts.
The standard program runs 16 hours of instructor-led sessions, typically over two days. We can reshape the schedule around your shifts and calendar.
We recommend 12 to 20 engineers per cohort for strong lab support. Larger plant teams can run as parallel batches.
Yes. We shape lab scenarios, equipment examples, and the capstone around your plants, machinery, and digital roadmap before delivery.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Edge computing sits between plant connectivity and AI on the shop floor. Your team connects machines with OPC UA and MQTT, processes that data close to the line, runs AI models at the edge, then uses the results for closed-loop and autonomous control.
Why Choose Edstellar as Your Edge Computing for Smart Manufacturing Enterprise Training Provider
If your OT and IT teams need to deploy edge computing on the factory floor, start here. Tell us about your plants, equipment, and preferred delivery mode, and we will shape a program around them.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Content shaped around your edge computing and smart manufacturing use cases, so every session maps to your real edge computing needs.
Proven Methodology
5+ years delivering corporate training to OT, automation, and plant IT teams across industries and regions.
Practice-Based Learning
6 hands-on labs across 6 modules. Your team builds edge deployments for factory systems with instructor guidance.
Expert Trainers
5,000+ certified trainers matched to your edge and OT stack, with a full trainer profile shared before your program is booked.
Global Scale
One edge computing program across your offices worldwide, in hybrid, onsite, or live virtual formats.
Measurable Outcomes
Baseline-to-capstone measurement and Skills Matrix reporting keep your edge computing capability lift visible.
Connect Factory Edge Systems Through Reliable OT Data and Governed Deployment
Edstellar develops manufacturing edge capability through hardware selection, OT connectivity, streaming data, and local AI inference. Mixed IT and OT teams build representative pipelines before planning secure operations at scale. The final deployment plan is reviewed for appropriate architecture, dependable telemetry, and latency-aware inference within the practical constraints of a manufacturing pilot.
- Step 01
Consult
We explore industrial-network and infrastructure experience to identify latency-sensitive workloads, connectivity gaps, telemetry-quality issues, edge hardware constraints, and deployment-security responsibilities.
- Step 02
Plan
We establish manufacturing edge foundations before hardware selection, OPC UA and MQTT connectivity, streaming pipelines, and local inference, then develop the secure pilot plan.
- Step 03
Align
We align industrial edge expertise with automation, plant IT, reliability, and OT teams, building a shared baseline across networking, infrastructure, and factory-process knowledge.
- Step 04
Customize
We tailor sample factory telemetry, gateway choices, and machine-vision workloads to representative production scenarios, keeping integration practice separate from live process control.
- Step 05
Execute
Teams configure OPC UA and MQTT flows, clean streaming telemetry, and tune edge inference, receiving feedback on connectivity, data handling, latency, and accuracy tradeoffs.
- Step 06
Evaluate
We assess the deployment proposal for justified hardware choices, coherent OT data flows, measured inference performance, and explicit security and operational responsibilities for scaling.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Edge Computing for Smart Manufacturing Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Edge Computing for Smart Manufacturing Training for Your Team
Share your team size, edge and digital manufacturing goals, preferred delivery mode, and timelines. We will respond with a tailored training plan covering scope, schedule, and pricing, and confirm trainer availability.