Titulo Estágio
MachineMan5.0 - Management of Heavy Construction Machinery through Industrial Wireless Sensor Networks
Áreas de especialidade
Comunicações, Serviços e Infraestruturas
Local do Estágio
DEI-FCTUC
Enquadramento
A new generation of manufacturing and industrial systems are growing, in a new industrial evolution that connects wireless technologies with powerful devices, capable to make their own decisions. In fact, in the Industry 4.0 paradigm, industrial systems are becoming more powerful and complex in order to keep with the requirements needed to optimize production. To achieve such paradigm, Industrial Wireless Sensor Networks (IWSNs) are a key technology capable to achieve micro-intelligence, with low-cost, and mobility, reducing even further today’s already short production cycles, and at the same time allowing new industrial monitoring applications.
Specifically, in the last decade, more reliable and deterministic communication standards were proposed (i.e. WirelessHART, ISA100.11a, WIA-PA and the ZigBee). Other options include technologies such as WiFi, 3G, 4G, or narrow band long distance technologies such as LoRa and Sigfox.
At the same time, until now, Industrial Control Systems (ICSs) have remained disconnected from the Internet, relying in the airgap principle to ensure security. Nevertheless, there is a lack of monitoring technologies applicable to these new industrial wireless standards, contrary to what happens with most common wired technologies. The lack of these tools can be explained by several characteristics present in current IoT devices like the fragmentation of the operating systems, the need to develop specific firmware for each application, different hardware architectures, etc.
On the other hand, this concept of automatic monitoring and control of environments is already used by many applications from industrial applications that monitor and actuate over several factory processes, to social applications that aggregate data from various users to achieve metropolitan-wide goals, such as reducing pollution and traffic, these environments can encompass a multitude of domains. Tool condition monitoring is also essential to assure factory efficiency by helping to cut machine downtime (estimated up to 20%) traditional approaches include deploying sensor devices to capture machine functional parameters and environment variables (such as cutting force, vibration, acoustic emission, temperature) and carry out a data processing pipeline including signal acquisition, processing, feature extraction, classification to help diagnose the problem.
Objetivo
This project aims to contribute to the proposal, development, and evaluation of a management architecture (with focus on monitoring) that can be used to support the daily operations of a big Portuguese construction company. The intended solution will comprise devices deployed in construction equipment that collects information about the equipment status and sends this data to a backend for further analysis, reporting, and alarming (using a specially developed user interface based on a dashboard) by using a combination of private LoRaWAN networks and the Internet. This innovative technological solution aims also to use machine learning mechanisms in IWSNs to allow optimizing production, and the monitorization in real time not only for the construction machines, as well as the discipline of work and performance of the maneuvers of those machines. This will support gains of efficiency and quality of effective operations.
Plano de Trabalhos - Semestre 1
1) The first task includes studying the state-of-the-art on equipment remote monitoring, LoRaWAN and J1939 bus communications, the existing prototype, and the technologies to support the development of the project.
Beginning date: September 2022
Estimated duration: 2 month
2) Proposal of an extension of the existing backend architecture to support automatic data analysis and reporting, supported on machine learning and data visualization techniques, that enables to better visualize equipment status, generate alarms, and integrate with currently used company information systems software.
Beginning date: November 2022
Estimated duration: 2 months
Plano de Trabalhos - Semestre 2
3) Development of the new backend functionality. This will also require establishing a new testbed for supporting a complete separation between current development and the new features development.
Beginning date: January 2022
Estimated duration: 3 months
4) Integration and final tests. This task includes the integration of all the developed functionalities and tests on the lab testbed and with live data from the remote equipment’s.
Beginning date: April 2022
Estimated duration: 2 months
5) Thesis writing will be done over time, this last month is intended to include new results and compile all material as well as text revisions.
Beginning date: June 2022
Estimated duration: 1 month
Condições
Integration in a research team with large experience in WSN, IWSN, IoT, and IIoT.
The selected student may apply to a 3-month research Initiation Grant, with a monthly amount of €835.98. The grant may be extended to cover subsequent 3-month periods, depending on the candidate's performance and results.
Observações
Work will be co-supervised by
- Prof. Jorge Sá Silva (DEEC)
- Prof. André Rodrigues (CISUC/ISCAC)
Orientador
Fernando Boavida
boavida@dei.uc.pt 📩