The self-learning system!

System Description

Cutting-edge technology for predictive maintenance

MACHINE LEARNING

What are the benefits?

1. Cost Reduction - Early identification of faults allows maintenance before significant damage occurs, avoiding higher repair costs.

2. Increased Operational Efficiency: - Minimization of unplanned stops, ensuring more continuous and efficient production.

3. Extension of Equipment Life: - Predictive maintenance allows precise intervention, extending the life of assets.

4. Optimization of Spare Parts Inventory: - Accurate prediction of faults reduces the need for excessive spare parts inventory.

5. Increased Safety: - Early detection of problems reduces operational risks, promoting a safer environment.

6. Time Savings: - Minimization of downtime, resulting in higher operational availability.

Case Studies:

Machine
Learning

Predictive Maintenance in the Automotive Industry - Automotive companies, such as Tesla, have implemented predictive maintenance systems in their electric vehicles. This involves analyzing real-time data from car sensors to predict potential component failures, improving reliability and operational efficiency.

Predictive Maintenance in the Railway Industry - BNSF Railway, a railway transportation company, implemented predictive maintenance solutions using machine learning to monitor the wear of components such as wheels and engines. This resulted in significant cost savings and increased fleet uptime.

Predictive Maintenance in Mining Equipment - Companies in the mining sector, such as Rio Tinto, have adopted predictive maintenance systems to predict failures in large equipment, optimizing operation time and reducing costs associated with unplanned stops.

Nuclear Energy Sector - In the nuclear energy sector, machine learning in predictive maintenance has been explored to anticipate and prevent failures in critical equipment, ensuring the safety and efficiency of nuclear operations.

Health and Medical Equipment Diagnostics - Hospitals have applied machine learning techniques for predictive maintenance of medical equipment, such as magnetic resonance imaging and CT scanners. This helps prevent unexpected failures and ensures that equipment is always ready for use.

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System Proposal:

Technological
Explanation

IoT Sensors for Data Collection - Using vibration, temperature, pressure, and other relevant sensors for equipment condition. - Accelerometer sensors to monitor vibrations and detect misalignments. - Temperature sensors to identify overheating in motors and critical parts. - Pressure sensors to measure pressure in hydraulic systems.

Machine Learning Algorithms - Neural Networks: - Deep neural networks can be employed for recognizing complex patterns in data collected by sensors. - Supervised Learning Algorithms: - Use of supervised algorithms to train the system with labeled data, identifying patterns of known failures. - Time Series Analysis Algorithms: - Suitable for predicting failures based on temporal patterns in data, considering evolution over time.

Cloud Platform for Data Processing and Storage - Use of cloud services such as AWS, Azure, or Google Cloud to process and store large volumes of data in a scalable and secure manner. - Storage in a distributed database to ensure data integrity and availability. - Cloud computing resources for training and execution of machine learning models.

The combination of these technologies will enable a robust implementation of the predictive maintenance system, providing real-time analytics, accurate predictions, and efficient data storage for future references and system improvements.

The system that schedules your company or industry shutdown!

SMART STOP

General shutdowns can be adopted for various reasons, such as preventive maintenance on all equipment, replacement of parts and components, reorganization of the production line, employee training, among others.

Concept - The concept of SmartStop from Solutions is the ideal solution for efficient management of Maintenance Shutdowns. With it, you will have precise control of activities, real-time monitoring, online or offline logging, and integration with PWA. Simplify and optimize your shutdowns with SmartStop!

What is Smart Stop? - Execution management system for Maintenance Shutdowns

What types of maintenance? - General Shutdowns, Scheduled Shutdowns, and Cold Shutdowns

What are shutdowns for? - Maintenance of industrial factories, as per regulations

Where does SmartStop help? - In the control of activity logging for projects registered in the Microsoft PWA (Progressive Web App)

How are activities logged? - Can be performed by mobile devices. Online or Offline

Brazilian Regulations

SMARTSTOP

Norma Regulamentadora 12 (NR-12) do Ministério do Trabalho e Emprego (MTE) Regulatory Standard 12 (NR-12) of the Ministry of Labor and Employment (MTE) - establishes minimum requirements to ensure the safety and health of workers who interact with machines and equipment.

Norma Regulamentadora 13 (NR-13) do MTE Regulatory Standard 13 (NR-13) of MTE - establishes requirements for the operation of boilers and pressure vessels.

Norma Regulamentadora 22 (NR-22) do MTE Regulatory Standard 22 (NR-22) of MTE - establishes safety and health requirements for work in mining.

Norma Regulamentadora 36 (NR-36) do MTE Regulatory Standard 36 (NR-36) of MTE - establishes ergonomic requirements for work activities in health establishments.

Lei nº 6.514 de 22 de dezembro de 1977 Law No. 6,514 of December 22, 1977 - establishes safety and health standards at work and penalties for violations.

Portaria nº 3.214 de 8 de junho de 1978 do MTE Ordinance No. 3,214 of June 8, 1978, of MTE - approves the Regulatory Standards (NRs) that establish minimum safety and health requirements at work.

Lei nº 9.433 de 8 de janeiro de 1997 Law No. 9,433 of January 8, 1997 - institutes the National Policy on Water Resources and establishes guidelines for the management and sustainable use of water resources.

Download our portuguese presentation in PDF

SMART STOP

More Projects

Systems described above - Some of the systems, I described in more detail above.

MLC3, MLC2 and MLC1 - Control systems for Continuous Casting Machines in a multinational steel production industry - I acted as a P.O in the last project, we managed to deliver the product 5 months ahead of schedule, it was a success!

- Below, you can DOWNLOAD (Only Portuguese) examples of documentations created by me. I developed and published the content, following the format and standards defined by the client.

Cel190 - Caixa Econônomica Federal - BANK CHAT BOT service

MasterTec - Financial management, inventory, user control, and Service Order Management System - Multiplatform Android, Web.

DentalMaster - Financial management, inventory, user control, and Dental Care Portal - Multiplatform Android, IOS, and Web.

More - I worked on more projects for the Federal Senate, Central Bank of Brazil, Caixa Econômica Federal, and TJPA (State Court of Pará), as well as several other personal and corporate projects.

Software Engineering

Software Engineering with Emphasis on Quality and Software Testing.
In pursuit of professionalization and further enhancement of my capabilities to manage and develop quality software, understand processes throughout their cycles, I sought the necessary techniques and methodologies for effective and essential development. Among various knowledge areas, my specialization deeply covered:
Agile Methodologies Quality Software Business Intelligence Source Code Quality (Clean Code) Software Testing Leadership and People Management Strategic Business Communication Design Patterns Usability Engineering Configuration Management, Version Control, and Change Management Alternative Data Architecture and Models - NoSQL / Data Warehouse / Data Mining Analysis and Specification of Requirements Project Management with Scrum.

Systems Analysis and Development

It's not enough to know a little about technology: as a systems analyst, I needed in-depth and complementary technical knowledge. I aimed to master different programming languages, understand operating systems (such as Linux or Windows), and hardware platforms. In addition to seeking broad knowledge in the field, I graduated as a more complete professional, capable of seeing the system as a whole, in an integrated manner.
Through hard work, dedication, and continuous study, I acquired and improved my skills, and today I can carry out a system project until it is delivered for use. Essentially, as an Analyst, I can:

1. Perform maintenance on existing systems and repair them as necessary.
2. Define the requirements and functionalities of a system to be developed.
3. Develop, test, and implement systems based on the definition of requirements and resources.
4. Develop system documentation. In the documentation, I can include tutorials, user manuals, maintenance routines, and standards for new versions.
5. Provide customer support. With technical knowledge, as an analyst, I guide the user on how to use the system and also identify bugs based on customer complaints.
6. Identify, map, and analyze technological options and tools in the market to be acquired by a company.

Maintaining a Microsoft Windows Server 2003 Environment

Specialization in Networks.
Among others, I have several specializations in complementary knowledge. This one, in the creation and maintenance of servers and network environments, is something I believe is worth mentioning. Network knowledge goes beyond understanding protocols and anticipating possible invasions; it also helps in the development of complex systems that depend on intranets, VPNs, RDPs, and many other network-layered applications and their protocols, useful in a development environment.

Analyst

As an Analyst, I have a solid academic background with a Postgraduate degree in Software Engineering and a degree in Systems Analysis and Development. With over 9 years of experience in the field, I excel in Agile environments and have extensive knowledge of tools and methodologies, including Scrum, KANBAN, RUP, UML, and BPMN. My skills encompass business analysis, process mapping, requirement gathering and specification, testing and validation, with specialization in requirement management and planning. Additionally, I possess strong interpersonal, negotiation skills, and goal-oriented focus. I am committed to leading projects to contribute to the development and enhancement of software products, aligning them with market and customer needs.