Are you ready to engineer smarter, more sustainable industrial systems? This minor challenges you to extend the lifespan of industrial products using cutting-edge technologies like smart sensors, cobots, worker assistance systems, predictive maintenance, and digital twins. Because AI deeply influences these technologies, you will learn also the application of AI within smart sensors, worker assistance systems, etc. You’ll work in multidisciplinary teams on real-world projects with companies like Siemens and Sensing360, applying your skills in data analysis, robotics, and lifecycle modelling. Through hands-on lab work, masterclasses, and collaboration with research groups, you’ll design and prototype solutions that make manufacturing more sustainable and future-proof. Examples cases the monitoring and reduction of wastes in manufacturing, automatic disassembly for remanufacturing, extend lifecycle by predictive and just-in-time maintenance. This minor deepens your current engineering expertise and connects you to innovation networks. Plus, you’ll build a professional portfolio and contribute to an open-source repository—perfect for showcasing your skills. If you want to combine engineering with impact, this is your chance to make a difference.

 

The minor consists of:

·        Project [20 EC]

·        Two additional (deepening) courses [2 x 5 EC]

For the deepening courses, you choose at least 2 from the 3 courses given in this minor*:

·        Remanufacturing [5 EC] (CMSM-RM) In this course you will learn about the relevance of circular manufacturing and the concept of digitally supported remanufacturing. Remanufacturing is one of the R-ladder processes that restores a product to like-new or better-than-new condition. Relevant processes discussed are inspection, disassembly, cleaning, component remanufactured, reassembly, testing and finishing. Assessment of economic and ecological benefits of remanufacturing are introduced, as well as the aspect of trust in ‘as-good-as-new-or-better’ parts and products.

·        Smart Asset Management [5 EC] (CMSM-AM) Maintenance and asset management are important processes to safeguard a long lifespan for equipment. In this course you learn the basics of maintenance strategies, and how to improve these by means of data-based condition-based monitoring. You will learn to evaluate the cost and benefits of such improvements, based on practical examples.

·        Industrial Dashboards [5 EC] (CMSM-ID) In this course, you will learn how to design and implement the steps from data measurement to meaningful display on dashboards, for use in e.g. digital supported (re)manufacturing, smart asset management, etc. In the course you learn among others: 1) data sensing and acquisition, 2) data processing and data communication, 3) data storage in (time-series) databases, 4) data-analysis (including AI), 5) display and user interaction through dashboard technology. You will learn technology necessary for digital shadow or digital twin development.

* Upon motivated request, other courses may be chosen as well, provided that they satisfy the following conditions:

1.      The course provides deepening knowledge for the field of Circular Manufacturing and/or Smart Maintenance. Examples are: Robotics, PLC programming, Vision, Sensor Technology, Applied AI, Internet of Things (IOT).

2.      The contents of the course do not overlap with your educational programme.

3.      The sum of the deepening courses is at least 10 EC.

 

Upon completion of this minor, the student

·        Has demonstrable knowledge and understanding of (re)manufacturing and/or smart maintenance that builds on and exceeds the level achieved in the first two years of the bachelor programme; usually operates at a level where, with the support of specialised manuals, there are some aspects that require knowledge of the latest developments in the field of expertise.

·        Is able to apply knowledge and insights on remanufacturing and/or smart maintenance in such a way that it shows a professional approach to his work or profession, and also has competencies for drawing up and deepening arguments, and for solving problems in the field of expertise

·        Student is able to collect and interpret and visualize/communicate relevant data (in field of reman/smart maintenance) with the aim of forming an opinion that is partly based on weighing relevant social, scientific or ethical aspects.

·        Is able to communicate information (e.g. based on the collected data), ideas and solutions (for instance on innovations developed) to an audience consisting of specialists or non-specialists

Students need to demonstrate -based on a concise motivation statement that contains short course descriptions or project descriptions of earlier work-, that they have a command of the technical competencies “Analyse” and “Design” (see HBO-Engineering-domeinprofiel-2022-Engels-defweb-1.pdf) at level 2, implying ->being able to execute complex tasks in a team, adapting familiar methods to changing situations, in practice, independently within specified actions, but under supervision. 

Such course work should be finished at the time the minor starts. The programme coordinators will evaluate eligibility of the students based on the motivation statement and can ask for further explanation or examples preceding the course.

Materials distributed through Brightspace including:

-basics of data science for engineers

-research methods in engineering problems

-the basics of circularity in manufacturing

-asset management and reliability engineering intro

-smart manufacturing (ROS, python for robots, aspects of interoperability)

-principles of digital twinning.

 

Other literature is depending on the chosen electives

The schedule will be published about a week before the start of the minor program. Please send an email to tis-minoren@hhs.nl if you haven't heard anything by then.

Technical Group Portfolio

Wk 19 in semester 1,

Wk 18 in semster 2,

Sufficient

Individual participation and reflection 

Portfolio + assessment

Wk 19 in semester 1

Wk 18 in semster 2

Sufficient

Competency Based Assessment (20 EC)

Assessment

Wk 20 in semester 1

Wk 19 in semester 2

weighing 2/3

passing grade 5.5

Elective 1 (5 EC)

See below

weighing 1/6

passing grade 5.5

Elective 2 (5 EC)

See below

weighing 1/6

passing grade 5.5

 

For the courses within this minor, they are as follows:

Remanufacturing 5 EC

Portfolio assessment

week 17*

Industrial Dashboards 5 EC

Portfolio assessment

week 17*

Asset Management 5 EC

Portfolio assessment

week 17*

*Upon request the assessment date can be organised earlier but not later.

All resits are held within 2 weeks after the end of the minor

Technical Group Portfolio consists of a set of deliverables, to be discussed and agreed upon with the project client at the start of the project. Such deliverables usually are: functional & technical spec, design documentation (of manufacturing or measurement setups), datasets, data analysis reports, code, UX (specifications, mockups or applications), manuals, (research) paper or poster. Teams hand-in the portfolio twice: intermediate portfolio for formative assessment at end of first block, final at end of second block.

Individual participation includes individual contribution to the minor’s GitHub Repository in the form of: a manual (in form of movie, e-learning, step-by-step description etc.), or a reusable, well-documented piece of code/algorithm/analysis method/module or alternative to be discussed with the instructors; part of or closely related to the team work. 

Resit
In case of a no-go for the portfolio or the reflection, students will get an opportunity to improve the hand-ins, within a fixed timeframe set by the course coordinator (unless this concerns shortcomings that have been pointed out in the formative assessment but have not been improved). This implies that the students can only take part in the resit assessment sessions.

In case of an insufficient score for the assessment interview (first attempt), students can resit the interview at a scheduled time (that will be published at the beginning of the semester).