Industrial Engineering
Minimum Workload: 540 hours
Coordinating Professor: Prof. Alexandre Ferreira de Pinho, PhD.
Contact e-mail: epr.pg@unifei.edu.br
The program
UNIFEI’s Graduate Program in Industrial Engineering is a Methods, Process and Product Engineering course, which intends to plan, design, install and control productive systems aiming for integration and optimization of factors of production. Its methods and techniques are applicable to every kind of activity in every economic sector, although they’re mainly used in the primary and tertiary sectors.
The program started in 1994, initially offering only master’s degrees; since 2012, it also offers Ph.Ds. It is divided in mandatory and optional courses, seminars and research paper advising, focusing on scientific research and dissertations.
Our main purpose is allowing future Masters and Ph.Ds. to take immediate responsibility on the planning, managing and operating of production systems, as well as providing the fundamentals for scientific research in the program’s areas.
The Masters Program in Industrial Engineering aims to develop well-prepared professionals from the hard sciences and business administration areas, and also exceptional technology and production systems researchers; while the Doctoral Program forms outstanding researchers in the fields of modeling, optimization and control.
Research Lines
Control
This research line studies and applies mathematical and statistical techniques to products, processes and services. Such techniques are specially created for monitoring processes, including monitoring, acquisition, analysis and signal processing, featuring:
- Signal processing, system stability, analysis and simulation of dynamic systems.
- Analysis of open-loop and closed-loop systems; Basic control actions: proportional, integral and derivative (PID); frequency-domain, root-locus, and state-space analysis and design of control systems.
Modeling and Optimization
This line studies and applies methods of modeling and optimization to process portfolios, products and services, featuring:
- Statistics and Predictive modeling. heteroscedastic modeling, autoregressive modeling, multivariable modeling (principal component regression, partial least squares, weighted least squares, Seemingly Unrelated Regression).
- Metaheuristics: stochastic optimization, dynamic optimization, multi-objective optimization, lexicographic programming, genetic algorithms, particle swarm, ant colony, gradient algorithms.
- Multiple dual optimization, robust programming, correlated duals, desirability, principal components optimization, multivariate uncertainty analysis.
Modeling, Optimization and Control
This research line studies and applies mathematical and statistical techniques to products, processes and services. Such techniques are specially created for monitoring processes, including monitoring, acquisition, analysis and signal processing. It also studies and applies methods of modeling and optimization to process portfolios, products and services.
Quality and Products
This line researches means of developing, improving and establishing models for quality management, with emphasis on continuous improvement of standard management systems, as well as project management processes, product development and innovation, including both quantitative and qualitative research methods.
Production Systems and Logistics
This line focuses on computational modeling tools, aiming for excellence in productive systems, involving logistic aspects and quantitative and qualitative methods. Reference models for managing productive knowledge are also developed and applied.