[APDIO] Call for 3 Phd Grants

["Susana Relvas" <susana.relvas@tecnico.ulisboa.pt>]

The project RD0652 - DM4Manufacturing, POCI-01-0145-FEDER-016418 is opening three Grants for Phd Student in scientific fields: Engineering Science and Technologies, Operation research, Operation Management

Deadlines: The call is open between the 14 and 18 of February  2020.

More information in: http://www.eracareers.pt/

 

The DM4Robotics project proposes a multidisciplinary approach to perform the co-development on advanced robotics and advanced Decision-making techniques to prepare the next generation of manufacturing. Manufacturing competitiveness depends largely on its productivity, flexibility and agility to react to market demands. Advances in manufacturing technologies with high flexibility, such as robotics, will play an important role in future manufacturing industries, but its impact in the overall decision-making strategies is still an open question.

The main objective of the DM4Manufacturing project is the integrated development of advanced robotics with decision making methodologies to maximize the productivity of the factories of the future. On the other hand the decision making tools will have to evolve to deal with production technologies with high flexibility, capable of performing different tasks with minimum reprogramming, capable of sensing the environment and working in environments designed for human‐use. This new paradigm represents a challenge for the traditional production process modelling techniques, where machines are almost static resources and the flexibility is completely provided by the human resources. Following a human‐centered automation methodology, the DM4Manufacturing project will search the optimal automation level for each manufacturing scenario, to produce efficiently but also to promote better working environments.

 

1. The work plane for  Internal Logistics and inventory control:

Product based manufacturing industries rely in strong internal logistics operations that enable efficient production strategies, as assembly line feed and support or components and supermarket management. Inventory accuracy is cornerstone for production efficiency. Agile decision making in flexible manufacturing elevates the need for integrated planning and scheduling for overall shop-floor operations and control. This task focuses in solution methods for the augmented planning problem integrating internal logistics and inventory control requisites

 

2. The work plane for  Monitoring advanced robotics operations for sustainability

Manufacturing companies deal, on a real-time basis, with shop-floor uncertainties and complexities associated with the high number of components and with the unstable market.  A set of KPIs to address sustainability in manufacturing contexts are going to be developed, quantifying the efficiency and effectiveness of actions in the manufacturing floor and involved supply chain. Sustainability issues in the planning and scheduling decisions through the inclusion of environmental and social indicators will be addressed, leading to a sustainable planning and integration system.

 

3. The work plane for Planning and optimizing maintenance activities

Maintenance activities have evolved from a supporting activity to an essential element of the business strategy for any manufacturing production system namely aeronautics and automotive systems. Characterized by a high degree of uncertainty, such activity emcompasses three main sub-activities that have been currently addressed in an independent form: capacity planning; parts forecasting; and task scheduling. This task explores the integration of such sub-activities pursuing higher flexibility and increased industrial performance. Bayesian Networks will be used within the problem structuring allowing for the linkage of the involved tasks with efficient forecast methods serving as inputs to the planning and scheduling of maintenance tasks, the latter defined through the use efficient optimization and heuristics methods.

Deadlines: The call is open between the 14 and 18 of February  2020.

APPLY NOW!

Best regards
Tânia Pinto Varela

 

 

 

Tânia Pinto Varela, PhD

Assistant Professor

Co-Coordinator of Bsc and Master Degree in Industrial Engineering and Management

Department of  Engineering and Managment

Instituto Superior Técnico

Av. Rovisco Pais, 1

1049-001 Lisboa, Portugal