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The programme focuses on the most relevant and essential industry 4.0 (I4.0) technologies and concepts related to operations and maintenance, for an industrial production context.
You learn how both operational and maintenance processes can be optimised by making them ‘smart’, using new (I4.0) technologies, such as robotics, big-data analytics, digital twins, cloud computing, etc. The programme covers technologies that facilitate an advanced digitalisation of product and process information (e.g., smart sensors), technologies that are used in production and maintenance (e.g., cobots), and technologies that connect production equipment/assets and people (e.g., Industrial IoT platforms).
This postgraduate programme is jointly organised by Ghent University and KU Leuven. It stands firmly on its own, but also opens the door to more. The programme forms an integral part of the upcoming Advanced Master of Science in Smart Operations and Maintenance in Industry (expected in 2023), in which students will be able to register for one of three in-depth and hands-on elective tracks, and further improve themselves as Smart O&M specialists. Participants who successfully complete the courses in the postgraduate programme will be granted exemptions in pursuing the homonymous advanced master’s degree.
In this advanced master’s programme, students learn how both operational and maintenance processes can be optimised by making them ‘smart’, using new (I4.0) technologies, such as robotics, big data analytics, digital twins, cloud computing, etc.
The programme covers technologies that facilitate an advanced digitalisation of product and process information (e.g., smart sensors), technologies that are used in production and maintenance (e.g., cobots), and technologies that connect production equipment/ assets and people (e.g., Industrial IoT platforms).
This master’s programme is jointly organised by Ghent University and KU Leuven. Students will be equipped both with a comprehensive understanding of the scientific techn(olog)ical knowledge in the – interdisciplinary – field of Smart O&M and with the ability to apply this knowledge in a real industrial setting, from a system approach.
The master’s programme delivers Smart Operations and Maintenance Specialists, capable of implementing and deploying innovative technologies with a real added value for the industry.
The programme contains 24 ECTS. After successful completion of the programme, you receive the Postgraduate Certificate: Smart Operations and Maintenance in Industry, awarded by KU Leuven and Ghent University.
*all lessons – except for project work where ‘on campus’ presence is required – take place in a hybrid virtual classroom, which allows you to choose – on a per class basis – whether you attend the class on campus or (live) online. Moreover, recordings will be provided.
High computing power at low costs, reliable and high bandwidth sensorisation and communication, and new computational modelling techniques have enabled us to simulate the physical world in a virtual one. It has led to the Digital Twin concept, a virtual replica that acts identically as a physical asset and remains synchronised with the asset during the lifecycle.
This opens up a plethora of possibilities, e.g. it can be used to optimise system parameters on the fly, to check the system’s condition live, or to virtually explore future design improvements. Through lectures and illustrative use cases, this course gives students an in-depth view on how to define a Digital Twin, its essential building blocks, and how to validate and use it to create added value in an industrial setting.
One of the key methods to improve industrial processes is an enhanced usage of current machinery. By monitoring the physical signals emitted by machine elements, it is not only possible to distinguish between a healthy and faulty machine, but also to predict when failing would occur.
Monitoring and prognostics optimise the need for replacement parts, reduces maintenance efforts, and increases machine reliability, which in turn makes factory maintenance and management easier, more efficient and more cost effective.
Through theoretical lectures, real-life cases and practical applications, students learn which physical signals are the most relevant, how to detect, acquire and analyse them, and how to relate these signals to potential failure.
This course introduces students to the complex world of management strategy formulation for one of the main domains of a manufacturing company, i.e. operations. The course describes the components and drivers for operations management in a contemporary business context. Challenges are identified and the role of new and emergent smart technologies is explored.
The course zooms in on production and maintenance, two important pillars in operations management.
Students learn about the different types of strategies possible for both production and maintenance, its essential concepts and opportunities, historical evolutions as well as the outlook. The course also teaches how to follow up performance, since it is imperative for all businesses to have quantitative tools to measure, monitor, check and predict the performance of their operations management.
New technological evolutions are drastically changing the way factories can and need to operate. The so-called “smart factories” have a highly digitalised shop floor that continuously collects and shares data through connected devices, machines, and production systems. These data can be used to (self-)optimise operations and to proactively address issues, improve manufacturing processes and respond to new demands by tapping the built-in reconfiguration potential.
Students learn how to design factories in a smart way, and how factories can be re-designed to become smart. A lot of digital tools are available to support factory design processes based on 3D digital models, which are virtual replicas of the (envisioned) real factory and can evolve towards digital twins in the operational phase to facilitate decision-making (e.g., what-if scenario analysis).
Upcoming programme: 26 Sept. 2023 – 24 May 2024, excluding the final examination period.
First semester
Tuesdays from 15:00 until 19:15
Thursdays from 12:30 until 20:00
Fridays from 08:30 until 16:00
Second semester
Tuesdays from 15:00 until 19:15
Thursdays from 16:00 until 18:45
Fridays from 09:45 until 16:00
In English
On campus, in a hybrid setting or online
Two locations, but never two locations on the same day:
– KU Leuven Bruges Campus
– Ghent University Campus Kortrijk
High computing power at low costs, reliable and high bandwidth sensorisation and communication, and new computational modelling techniques have enabled us to simulate the physical world in a virtual one. It has led to the Digital Twin concept, a virtual replica that acts identically as a physical asset and remains synchronised with the asset during the lifecycle.
This opens up a plethora of possibilities, e.g. it can be used to optimise system parameters on the fly, to check the system’s condition live, or to virtually explore future design improvements. Through lectures and illustrative use cases, this course gives students an in-depth view on how to define a Digital Twin, its essential building blocks, and how to validate and use it to create added value in an industrial setting.
More info…One of the key methods to improve industrial processes is an enhanced usage of current machinery. By monitoring the physical signals emitted by machine elements, it is not only possible to distinguish between a healthy and faulty machine, but also to predict when failing would occur.
Monitoring and prognostics optimise the need for replacement parts, reduces maintenance efforts, and increases machine reliability, which in turn makes factory maintenance and management easier, more efficient and more cost effective.
Through theoretical lectures, real-life cases and practical applications, students learn which physical signals are the most relevant, how to detect, acquire and analyse them, and how to relate these signals to potential failure.
More info…New technological evolutions are drastically changing the way factories can and need to operate. The so-called “smart factories” have a highly digitalised shop floor that continuously collects and shares data through connected devices, machines, and production systems. These data can be used to (self-)optimise operations and to proactively address issues, improve manufacturing processes and respond to new demands by tapping the built-in reconfiguration potential.
Students learn how to design factories in a smart way, and how factories can be re-designed to become smart. A lot of digital tools are available to support factory design processes based on 3D digital models, which are virtual replicas of the (envisioned) real factory and can evolve towards digital twins in the operational phase to facilitate decision-making (e.g., what-if scenario analysis).
More info…This course introduces students to the complex world of management strategy formulation for one of the main domains of a manufacturing company, i.e. operations. The course describes the components and drivers for operations management in a contemporary business context. Challenges are identified and the role of new and emergent smart technologies is explored.
The course zooms in on production and maintenance, two important pillars in operations management.
Students learn about the different types of strategies possible for both production and maintenance, its essential concepts and opportunities, historical evolutions as well as the outlook. The course also teaches how to follow up performance, since it is imperative for all businesses to have quantitative tools to measure, monitor, check and predict the performance of their operations management.
More info…The course ‘Digital Twins Deployment in the Manufacturing Industry’ (4 ECTS) is taught in all three tracks but uses different track specific exercises. All these elective tracks leverage upon one or more compulsory courses and can be considered ‘specialised’ courses, which constitute ‘the next step’ in the gradual growth path towards more applied learning and increasing complexity of interdisciplinary integration. Therefore, they are integrally scheduled in the second semester.
A top priority of smart operations and maintenance specialists is retrofitting ‘classic’ or even ‘brownfield’ mechanical installations to make them usable in an Industry 4.0 environment. The central question in this course (4 ECTS) is how to retrofit a certain asset into a smart and robust machine with limited cost/impact (limited downtime) but with maximum smartness. Retrofitting technologies will be taught and students will learn how to get started, how to deal with limited/missing information, how to deal with standards and protocols, etc.
Beside retrofitting an old machine, the course also focuses on how to design new machines in such a way they can be easily upgraded in the future (upgradable design). As such, the course nicely fits with the overall idea that not only state of the art technology should be taken into account, but that off the shelf technology as well presents a challenge in an existing industrial context.
Another priority of smart operations and maintenance specialists is determining the appropriate use of sensors, sensor models and sensor networks, since data from smart sensors drive Industry 4.0. The course ‘Smart Sensing Technologies’ (4 ECTS) constitutes a deep dive into smart sensor technology, without losing the link with legacy systems (such as ‘traditional’ sensors and existing sensing platforms). Principal course topics are the smart exploitation of sensor data (how to enrich sensor information) and the optimal use of smart sensors (how to select and calibrate sensors).
The course ‘Digital Twins Deployment in the Manufacturing Industry’ (4 ECTS) is taught in all three tracks but uses different track specific exercises. All these elective tracks leverage upon one or more compulsory courses and can be considered ‘specialised’ courses, which constitute ‘the next step’ in the gradual growth path towards more applied learning and increasing complexity of interdisciplinary integration. Therefore, they are integrally scheduled in the second semester.
The course ‘Reconfigurable Manufacturing Systems’ (4 ECTS) concerns the factory reconfiguration potential, making full use of flexible automation technologies with a focus on robotic components. The course deals with state-of-the-art robotic components such as cobots and robots, tooling and fixture (overview of gripper principles), navigation (mobile robots), manipulation (arms) and coordination (such as fleet control of AMRs, dual-arm tasks, mobile manipulators). The robotic capabilities provide manufacturing execution systems (MES) with options to automatically reconfigure manufacturing systems (e.g. layout, task allocation) in order to quickly respond to changes imposed on the factory floor (e.g. changes in the product mix, operator unavailability, machine breakdowns).
The course ‘Safe and Secure System Integration’ (4 ECTS) focuses on safety and security. The different attributes of so-called ‘dependable’ systems are discussed: secure computing, resilient and fault-tolerant hardware and software, reliability of safety-critical systems, safety assurance, robustness, integrity, maintainability, safety and security by design, …
The course ‘Digital Twins Deployment in the Manufacturing Industry’ (4 ECTS) is taught in all three tracks but uses different track specific exercises. All these elective tracks leverage upon one or more compulsory courses and can be considered ‘specialised’ courses, which constitute ‘the next step’ in the gradual growth path towards more applied learning and increasing complexity of interdisciplinary integration. Therefore, they are integrally scheduled in the second semester.
The course ‘Decision Support for Maintenance Logistics’ (4 ECTS) deals with models that help decision-making activities in a maintenance logistics context. The focus is on implementing these models, at a tactical level. More specifically there will be an emphasis on the following support tools for decision making:
The course ‘Human Centered Manufacturing’ (4 ECTS) elaborates on the more complex work environment imposed by Industry 4.0. The human role – and especially the role of the operator – is heavily subject to changes, as human-machine interaction plays a major role in an industrial context. This course focuses on enabling technologies for so-called ‘human centric’ manufacturing (such as VR) and discusses assistive and collaborative technological tools (such as cobots and exoskeletons) to improve human well-being in the factory (workplace ergonomics, cognitive load, off- and on-the-job training, etc.).
