Awards and Partnerships

Our mission is to assist in the technological development of manufacturing by addressing key production problems such as:

ESG & Energy waste

Operational inefficiency can result in energy losses due to rework of parts, material waste, generation of waste, and pollutants. Our system can identify engines operating at non-production times. We have also worked in reducing gas consumption in the coke oven process. In the same belt, Scrap rates also count for an important environment enhancement issue, as non-conforming parts are discarded. Also, the costliest processes in the manufacturing process can become burdensome and time-consuming when poorly managed, leading to delays and waste on the production line. Our solution addresses this problem by optimizing the production line with data-driven tools.

Decentralized data

In the manufacturing process, data is often created and stored in different forms and types. Data silos occur when there is no agile information sharing between subsequent areas of a process, for example. Each department usually has its own way of managing and handling data, which can lead to problems in understanding the generated information and communicating results.

Lack of professional training to implement advanced manufacturing solutions

Knowledge of the requirements for implementing Industry 4.0 tools is lacking in companies, as employees are only experts in knowledge of manufacturing functions.

Our solutions

We utilize Artificial Intelligence to help industries become more competitive, profitable, and efficient in their processes. Our unique solution consists of 3 stages:

Industrial IOT
& Big Data

Data Streaming Industrial IOT

Database

OEE and KPI

Analytics &
Industrial B.I

Real Time Information

Alarms for operation

and Maintenance

Smart
Factory

Digital Twin

Anomaly Detection

AI operation

Implementation of Artificial Intelligence in manufacturing processes

Even if the operation’s data is scattered across different sensors, PIMs, and PLCs, Ubivis can collect and centralize production data through our exclusive hardware. The information is centralized and stored in a Big Data infrastructure.

 

Integrated IoT Solution : With our IoT platform, data from different sources such as mobile devices, desktops, sensors, electrical panels, PIMs, and PLCs can be collected. By eliminating paperwork and digitizing information, it is possible to concatenate and centralize all data related to the manufacturing process. We know that it is common to have data scattered across different platforms and devices. Therefore, it is necessary to centralize and provide agile access to process information.

Asset Management via
analytics platforms

We build customized dashboards and Business Intelligence (BI) tools with key performance indicators (KPIs) chosen by the client. We also offer tools for implementing condition-based maintenance with OEE monitoring. Our solution is provided through our exclusive Production Optimization Console.

Asset Management via analytics platforms provides a tool for monitoring asset performance and identifying possible delays and failures in operations. The customizable dashboards offer a detailed view of the data and enable actions to correct the failures. We also offer real-time alarms that notify non-conforming operation parameters, facilitating decision-making by operators.
Some of the key KPIs related to manufacturing operations include:

  • • Mean Time Between Failures (MTBF): Measures the efficiency of preventive and predictive maintenance, representing the average time a piece of equipment operates before a failure occurs.
  • • Mean Time To Repair (MTTR): Measures the efficiency of the maintenance team in restoring equipment after a failure, including the time required to identify the problem, diagnose the root cause, order parts, perform repairs, and test the equipment.
  • • Failure Rate: Measures the number of equipment failures in a specific period, providing information about the reliability and durability of the equipment.
  • • Overall Equipment Effectiveness (OEE): Measures the overall efficiency of equipment in terms of availability, performance, and quality.
  • • Remaining Useful Life (RUL): Measures the remaining time until equipment needs to be replaced, allowing maintenance to plan for equipment replacement before it fails.
  • These KPIs, along with others, are tracked and analyzed through our analytics platforms to provide insights and drive improvements in the manufacturing process.

Overall Equipment Effectiveness (OEE) of a production line from the Production Console Operation system

Production downtime with filters to select machines, production lines, time periods, and cause.

For maintenance tracking, we also offer Dashboards addressing KPIs such as Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR).

AI to boost your factory's productivity

It is possible to make the operation completely autonomous through the implementation of Digital Twins with a dual layer of Artificial Intelligence. Digital Twins are real-time simulations of the manufacturing operation based on collected data. It is possible to autonomously automate the setup of production parameters through Robotic Software. This second layer of artificial intelligence on the trained digital twin enables it to make inferences, classifications, and suggest optimizations in input parameters.

Double AI layer - Software Robot

  • Digital Twin for a given industrial operation

  • AI algorithm performing inference for optimization of process parameters

Among the Artificial Intelligence solutions for the industry is Process Anomaly Detection.

Ubivis also provides a Correlation Map where statistical similarities between operation parameters can be visualized. Ubivis works with two types of correlation maps.

Trend Analysis / Predictive Maintenance

Trend analysis is important to determine if, and especially when, a critical variable will reach an undesired limit, alerting the responsible party to take precautions before it happens, thus avoiding further losses. It has a significant impact on predictive maintenance, as it can indicate whether, with the current machine operation parameters, the variable or sensor will exceed the ideal operating limits, thereby reducing the equipment's lifespan.

Maintenance for Critical Assets

  • MONITORING

    Comparing between historical and real-time asset data

  • KPIs

    Conditional performance analysis rules

  • AWARENESS

    Identify conditions of occurrence of an active event

  • DASHBOARD

    Visual analysis and reports

The differentiator that you can only find in Ubivis products:

We have developed our own gateway for concatenating data from different sources to build Big Data.

We deliver an end-to-end Software-as-a-Service solution, while companies competing with Ubivis provide Platform-as-a-Service, which requires the company to have qualified professionals to work on these platforms.

Ubivis provides the solution on our own platform called Production Optimization Console (COP), specifically developed to integrate with different systems and highly flexible in customization when installing new sensors on the line, adding and configuring new dashboards, graphs, and other functionalities.

A Ubivis entrega resultados prontos e customizados aos clientes;

These are some of the proven results by our clients:

92% reduction in field test validation time

83% reduction in field test execution time

25% reduction in machine downtime

Over 40% decrease in process variability, increasing quality and reducing raw material consumption

12% increase in production processes

Our Clients

Successful Cases

Project with Shell with 90% reduction in operations time
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Gerdau: Intelligent synchronization of steel mill cycles
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Ball - Can production machine - Bodymaker Smart System
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Denso: Autonomous Welding by Artificial Intelligence
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Petrobras: Ubivis was selected and is implementing the challenge of inspection technologies using artificial intelligence to predict critical equipment
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Petrobras: Ubivis was selected and is implementing the challenge of inspection technologies using artificial intelligence to predict critical equipment
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Ubivis wins Smart Factory tender to implement 20 optimization systems for metal-mechanical industry with the Senai Technology Institute
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