May 2020 | 4rd place in the Simio Student Simulation Competition

The goal was the propose recommendations for optimizing waving and picking strategies in warehouse management.

Dec 2019 | 3rd place in the Simio Student Simulation Competition

The challenge was to optimize the operations of an airport by studying and evaluating alternative processes and technologies from the passenger arrivals to the terminal areas.

Nov 2019 | Finalist in the EUREKATHON Student Competition

EUREKATHON is a data-driven competition that addresses societal issues associated with sustainable development goals.


Digital twin of manufacturing sites

The manufacturing industry strives for tools that are capable of quantifying, demonstrating, and finding the sweet spot of running the processes, production lines, plants, and supply chains. The immediate objective is to smooth out the running systems as much as possible, even when the systems are running under severe conditions. Although this goal appears to be contradictory, emerging manufacturing paradigms, as is the Industry 4.0, support the development and application of tools focused on improving output and quality and reducing downtimes. While this path is generally well seen, there is still work to do to estimate the extension of such benefits in the existing systems. To accomplish this, data-driven methods, such as simulation, take advantage of data to learn how to make the best decisions.

Current Team

  • Alexandre Jesus, Systems Simulation, MSc Student
  • Edmundo Sérgio, Large-Scale Optimization, MSc Student
  • Márcia Dias, Machine Learning, MSc Student
  • Paulo Nascimento, Process Optimization, MSc Student
  • Paulo Serrano, Lean 4.0, PhD Student


Decision-support challenges in the chemical-pharmaceutical industry: findings and future research directions
Marques, C. M., Moniz, S., de Sousa, J. P., Barbosa-Povoa, A. P., & Reklaitis, G.

Hybrid optimisation approach for sequencing and assignment decision-making in reconfigurable assembly lines
Maganha, I., Silva, C., Klement, N., dit Eynaud, A. B., Durville, L., & Moniz, S.

Optimal design of additive manufacturing supply chains
Basto, J., Ferreira, J. S., Alcalá, S. G., Frazzon, E., & Moniz, S.

A simulation approach for spare parts supply chain management
Caldas, N., Pinho de Sousa, J., Alcalá, S. G., Frazzon, E., & Moniz, S.

Integrating Simulation and Optimization for Process Planning and Scheduling Problems
Vieira, M., Moniz, S., Gonçalves, B., Pinto-Varela, T., & Barbosa-Póvoa, A. P.


DM4Manufacturing Aligning Manufacturing Decision Making with Advanced Manufacturing Technologies | PORTUGAL 2020 | Budget: 1.677.691,31 euros | Partners: Universidade de Coimbra, INESC TEC, and Instituto Superior Técnico.


Simulation of Operations

Introduces simulation methods with a focus on modeling and analysis of real-world problems. Covers queuing models, probability and statistics in simulation, conceptual modeling, verification and validation of simulation models, and process design and analysis. Applications to manufacturing, logistics, transportation, and services will be discussed. It includes a team project to solve a large-scale simulation problem of practical interest.

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Production Management

Addresses the theory and practice of production management as a functional area of the operations. Covers process design and analysis, production line balancing, design of factory layouts, forecasting methods, inventory models, production planning and scheduling, concepts of supply chains, and key lean manufacturing tools. It includes a team project to solve a problem of practical interest.

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Communicating with Data

Aims at equipping students with knowledge and communication skills, and focuses on learning the strategic and tactical use of data to conduct decision-making processes. This curricular unit seeks to increase communication skills and use data tools through practice and real-world examples. Emphasis will be placed on the communication of quantitative information as well as the improvement of communication skills in general.

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The path to the simulation of digital manufacturing systems

New approaches for simulation will leverage best practices to engineer factories and production processes at the earlier stages of their development. This can be done by using several models to investigate a broad spectrum of complex issues.
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Strategic decision-making in the pharmaceutical industry

In the pharmaceutical industry, the ability to bring new drugs into the market consistently is a central issue to remain competitive and maintain economic sustainability. Several challenges arise during this phase.
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Decision-making in the drug development process

Major technological advances are changing the way pharma companies operate and manage their operations. These companies are continually being challenged to become ever more cost-efficient and responsive to the delivery of drugs.