Syllabus

Discipline:

Research Methodology in Production Engineering

Research Fields:

I and II

Syllabus:

Develop scientific training through the introduction of concepts about scientific methods, research project models and mechanisms for disseminating acquired knowledge. Reflect issues related to pedagogical practice, as well as the processes of evaluation and learning in higher education.

Discipline:

Production Systems

Research Fields:

I and II

Syllabus:

Address issues that characterize production management. Functions of manufacturing systems. Types of Production Systems. Paradigms of production. Stages of production planning. Demand forecasting. Materials and inventory management systems. Mathematical models. Production planning, scheduling and control systems: traditional systems. Lean Manufacturing. Developing the Project of Production Systems. Production management in the supply chain.

Discipline:

Operational Research

Research Fields:

I and II

Syllabus:

To develop the ability to model problems using mathematical programming. Introduce the main mathematical methods as support in the decision making process in Production Engineering: Linear Programming, Duality Theory and Sensitivity Analysis, Integer Linear Programming, Mixed Integer Linear Programming and Binary Programming. Reflect on the application of the methods studied in solving real problems and discuss its implication in decision making.

Discipline:

Statistical Methods

Research Fields:

I and II

Syllabus:

To provide the student with an introduction that enables him/her to scientific research through planning, collection, presentation and data analysis. Present the main concepts in probability, sampling techniques and statistical inference.

Discipline:

Scientific Seminars

Research Fields:

I and II

Syllabus:

Presentation and discussion of dissertation projects by students and teaching staff.

Discipline:

Strategic Operations Management

Research Fields:

I

Syllabus:

To study the levels of strategy and the strategic role of operations, the strategies of operations and the areas of decision of an operating system, the elaboration of operations strategies and management. Resource and capability-based models, audits in operations and world class manufacturing will also be covered.

Discipline:

Information Systems

Research Fields:

I

Syllabus:

To study the concepts of information systems and to deepen the knowledge about information systems in the context of production systems and management by business processes. Approach decision making and information systems under the focus of the decision-making process and decision support systems (DSS). Understand the intelligent decision support systems and knowledge management systems.

Discipline:

Tools for Multicriteria Decision Making

Research Fields:

I

Syllabus:

Address the basic concepts and historical contextualization of multicriteria decision making. Presentation of examples of multicriteria problems. Study the main tools for multicriteria for multicriteria decision making: MAUT (Multi Attribute Utility Theory), AHP (Analytic Utility Theory), AHP (Analytic Hierarchy Process), ANP (Analytic Network Process), ELECTRE (Élimination Et Choix Traduisant), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations), TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) and DEMATEL (Decision-Making Trial and Evaluation Laboratory). Explore case studies with real applications of the tools studied.

Discipline:

Logistical Systems

Research Fields:

I

Syllabus:

Present a view of the components (Supply, Manufacturing Support and Distribution) of a logistical system and the issues involved with internal and external integration of these components. Discuss contemporary approaches involving business logistics: Reverse logistics, Humanitarian, Hospital and Green Supply Chain.

Discipline:

Planning and Quality Control

Research Fields:

I

Syllabus:

Concepts and basic principles of Quality. Models of Quality Management. Six Sigma approach. Tools for Planning and Controlling Quality: Basic Quality Tools, Statistical Process Control (SPC), Design of Experiments (DoE), FMEA (Failure Mode and Effects Analysis). Regression Analysis, Logistics and Reliability.

Discipline:

Application of Lice Cycle Assessment Techniques

Research Fields:

I

Syllabus:

Address the concepts and applications of Life Cycle Assessment techniques in industrial processes.

Discipline:

Sustainable Supply Chain Management

Research Fields:

I

Syllabus:

Study the approaches of organizational sustainable management; Business strategy and sustainable management; Environmental management; Organizational functions and sustainable management; Management of sustainable operations and chains; Typology of environmental, social and economic technologies; Sustainable supply chain management practices; Generation of sustainable value.

Discipline:

Mixed Integer Nonlinear Programming

Research Fields:

II

Syllabus:

Develop the concepts and applications of nonlinear optimization in industrial processes.

Discipline:

Modeling of Logistical Systems

Research Fields:

II

Syllabus:

Study of logistics systems, with emphasis on urban, humanitarian and emergency logistics, addressed by mathematical models for Logistics Systems (Probabilistic Approach, Mesh Path and Distance Problems, Location, Zoning and Congestion).

Discipline:

Metaheuristics

Research Fields:

II

Syllabus:

Study concepts of complexity, combinatorial optimization, heuristic and metaheuristics methods (Simulated Annealing, GRASP, Tabu Search, Genetic Algorithms, Ant Colony Optimization, Hybrid Algorithms). Applications of Metaheuristics in classical problems of Production Engineering.

Discipline:

Smart Systems

Research Fields:

II

Syllabus:

Definitions and general characteristics of intelligent systems. History, state of the art and applications in academia and industry. Knowledge-based systems and knowledge representation. Fuzzy logic systems (fuzzy logic). Artificial neural networks. Implementation analysis and aspects of smart systems in applications in areas of production engineering and industrial systems and automation. Computational work of implementation and simulation of intelligent systems.

Discipline:

Stochastic Processes and Simulation

Research Fields:

II

Syllabus:

Approach stochastic processes: Markovian and Semi-Markovian processes. Discrete and Continuous Parameters to Markov Chains. Applications in line. Stochastic simulation: methods based on resampling and Markov chains. Convergence diagnostics.

Discipline:

Operations Research Applied to Production Systems

Research Fields:

II

Syllabus:

Approach optimization techniques and models applied to inventory management, sequencing and scheduling of operations and programming of production systems. Develop applications for the various types of production systems.