Projects
Projects
Research Projects
2022 – Present
Optimization of Manufacturing Processes through Forging and Stamping Using Artificial Intelligence Techniques
Description: This project focuses on optimizing manufacturing processes through forging and stamping in the production of ultra-high mechanical strength components. Since modern industries began implementing Industry 4.0, these advancements have only become viable with the adoption of new technologies, including Process Simulation (CAD/CAE), Artificial Intelligence (AI), the Internet of Things (IoT), cloud data storage, and digital twins. These tools are expected to be employed as outcomes of this project.
In the first phase, computational simulations based on Finite Element Analysis (FEA) will be conducted to model the parts and production batches, applying artificial intelligence algorithms to detect potential production deviations in the simulated batches.
In the second phase, new alloy forming technology will be developed through practical analyses and theoretical studies, starting with the manufacturing (forging and stamping) of high-strength steels. The key process parameters will be monitored using sensors. The measured parameters (e.g., force, tool displacement and speed, temperature, etc.), combined with literature data (e.g., thermal parameters for heat transfer analysis, friction coefficients, grain size calculations, etc.), will form a database for process simulation and analysis. This database will enable companies to correct production errors in real-time, contributing to the development of an Industry 4.0 model.
Status: Ongoing
Project Type: Research
Students Involved: Undergraduate (1); Master’s (1); PhD (2)
Team Members: Roderval Marcelino; Lirio Schaeffer (Coordinator); Iury Melo Américo; Jeferson Borges Cardoso
2021 – 2024
Development of Smart and Energy-Efficient Greenhouses for High-Value Crop Cultivation in Hydroelectric Dam Communities
Description: Today, sustainable development is an increasingly pressing concern, and hydroelectric projects are being designed in alignment with these concerns. This project aims to enhance and expand the perception that hydroelectric ventures are sustainable and aligned with 21st-century demands.
The goal is to provide an alternative income source to hydroelectric dam-adjacent communities, improving their quality of life. This initiative has social impact by granting farmers greater autonomy, reducing their dependence on direct financial support, and promoting pesticide-free seedling production for improved quality and productivity.
The project’s main output is the integration of various technologies, including energy efficiency, computational intelligence, IoT, and controlled environment agriculture. Two smart, energy-efficient greenhouses (12m x 8m) will be developed, equipped with monitoring and control systems for temperature, substrate conditions, humidity, irrigation, lighting, and CO2 levels to optimize cultivation conditions and increase crop productivity.
A web-based computational platform with IoT and AI will manage these greenhouses, supported by photovoltaic systems and bioclimatic architecture to enhance energy efficiency. Additionally, the project includes an economic and financial feasibility study and business model development to ensure long-term sustainability and improved living conditions for hydroelectric-adjacent communities.
Status: Completed
Project Type: Research
Students Involved: Undergraduate (4); Master’s (4); PhD (1)
Team Members: Roderval Marcelino (Coordinator); Vilson Gruber; Alexandre Leopoldo Gonçalves; Giuliano Arns Rampinelli; Braz da Silva Ferraz Filho; Thayane Lodete Bilésimo; Bruno Espíndola Pansera; Andriele Bratti Machado; Nicolas Cechinel Rosa; Gustavo Simões Mendonça; Jonathan Possenti Damasceno; Diogo Klock Ferreira; Maisa Benedete Duarte; Vinícius Santana Farias; Janini Cunha de Borba; Natalia da Silva Tiscoski; Valdir Nesi Junior
2021 – 2023
A Framework for Scientific Paper Review Based on Blockchain and Smart Contracts
Description: Distributed ledger technology (DLT) is evolving and gaining prominence across various economic sectors. Blockchain, initially popularized by Bitcoin, has extended its applications beyond cryptocurrencies to scientific and academic fields.
The traditional peer review system for scientific papers has been criticized for its lack of transparency, high costs, and lack of incentives for researchers. This project aims to evaluate whether blockchain technology can support a new peer review model, improving transparency, reducing costs, and incentivizing researchers’ participation.
A proof of concept will be developed using the Ethereum blockchain and the Remix IDE, enabling smart contract development in Solidity to facilitate the proposed workflow. Functional testing will be conducted to simulate transactions and validate the prototype’s performance, ultimately confirming the framework’s feasibility.
Status: Completed
Project Type: Research
Students Involved: Master’s (1)
Team Members: Roderval Marcelino; Cristian Cechinel (Coordinator); Allan Farias Fávaro
2020 – 2023
The Influence of New Information and Communication Technologies on Craft Beer Production
Description: Craft beer production in Brazil is rapidly growing, but many processes remain manual, making it difficult to replicate batches and maintain consistent quality. While some manual steps are essential to preserve the artisanal nature, lack of standardization negatively affects product uniformity.
This project evaluates the impact of integrating Information and Communication Technologies (ICTs) in controlled brewing environments. The approach involves:
🔹 Studying the craft beer production process
🔹 Developing an embedded system to monitor brewing variables
🔹 Implementing an AI-based control system
🔹 Prototyping an automated brewing system to measure the impact of ICTs
The expected outcome is improved product quality and increased revenue for craft brewers.
Status: Completed
Project Type: Research
Students Involved: Undergraduate (2); Master’s (1)
Team Members: Roderval Marcelino (Coordinator); Eduardo Farias; Bruno Espíndola Pansera; Armando Mendes Neto
Funding: CNPq
2016 – 2020
Precision Agriculture
Description: Application of image processing techniques in precision forestry and development of embedded systems in controlled environments.
Status: Completed
Project Type: Research
Students Involved: Undergraduate (3); Master’s (1)
Team Members: Roderval Marcelino (Coordinator); Yuri Crotti; Luan Carlos da Silva Casagrande; Renan Cunha dos Santos; Braz da Silva Ferraz Filho
