Course
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Data collection and connectivity
The next module becomes its own course: how data leaves the machine, which protocol to use, and what to do with older equipment that says nothing.
Introductory course · featured
From the sensor to the indicator, no shortcuts.
The starting point for anyone who runs, plans, or manages production and wants to understand what Industry 4.0 changes in plant results. Five short lessons, two of them a conversation with the Ubivis CEO, and a workbook that closes the module.
Introduction to Industry 4.0
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Start with a course
The first lesson asks for nothing.
In the works
What Ub-Academy is recording and writing right now.
Technical note
Coming soon
In production
Measuring machine downtime without installing new sensors
Technical material with a named author, for teams that need the downtime number before they have a budget for instrumentation.
Audio
Coming soon
In production
The videocast with the CEO, full episode
Both conversations in a single episode, to listen to on the way to the plant.
Well done for looking to improve
Ubivis is your partner in that.
The track
Every lesson answers one question
The order is there for a reason: you cannot pick an indicator before you know what the machine can count. Keep scrolling to walk through it.
01
Lesson · 6 min
Introduction: why going digital changes the bottom line
Every plant has three ways to grow: charge more, produce more, or spend less. In a crowded market the first two stall, and the third is what is left. This lesson shows where digitalization cuts cost, and where Ubivis fits in.
- What a plant is chasing, and which of those goals technology reaches first
- Where live data meets bottlenecks, waste, and energy use
- What each lesson in this module covers
02
Lesson · 6 min
What Industry 4.0 is
From craft production to the connected plant, in four leaps. The lesson walks through the three earlier revolutions, shows what the fourth adds by joining the physical and the digital, and introduces the fifth, which puts sustainability and people at the centre.
- Steam, electricity, and the PLC: what each revolution solved
- IoT, artificial intelligence, computer vision, and cloud on the shop floor
- Industry 5.0, and why it talks about people
- Maturity levels: every plant starts from a different point
03
Videocast · 9 min
The Ubivis story, with the CEO
A conversation with Paulo Cesar Griiettner about his background, the early projects, and the market need that brought Ubivis into being. He explains how the company reached Industry 4.0 through practice, one project at a time.
- The training and the career hurdles that came before the company
- Which shop-floor problem gave rise to Ubivis
- How digitalization, data, and artificial intelligence entered the product
04
Videocast · 8 min
The industry of the future
Part two of the conversation with the CEO. The subject now is where manufacturing is heading: what connectivity and data-driven decisions have already changed, what still stalls inside companies, and what Industry 5.0 proposes.
- Productivity and competitiveness: where technology has already paid off
- The obstacles that show up in every digital transformation
- Industry 5.0: customization, sustainability, and ethical use of technology
- The skills the next decade will ask for
05
Lesson · 7 min
How to reach the fourth industrial revolution
Buying sensors, software, and artificial intelligence puts nobody in Industry 4.0. This lesson covers what comes first: monitoring to have data, standardizing the process, integrating systems, and building the habit of deciding by the numbers.
- The mistake of treating purchased technology as a finished transformation
- Monitoring as the first step, at any level of automation
- Why artificial intelligence projects fail when the data foundation is thin
- Pilots, proofs of concept, and steady improvement instead of one big leap
A stopped machine gives no warning. The data does.
Who teaches
Joelton Gotz
PhD in Electrical Engineering, researcher in industrial systems. The lessons come from real shop-floor problems: what the controller already knows and nobody went to fetch, why the pretty dashboard does not change the shift, and how to pick a first indicator without turning the team into spreadsheet clerks.
Research in industrial systemsIoT and automationPredictive maintenance
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