Project overviewThis design research project is situated in the context of professional printing, a broad category from large format printing of posters and banners to high-volume printing of books, magazines, and flyers. As you can imagine, the machines used for this are complex and they need professionals to operate them. In a way, you can think of these machines as small 'factories in a box': paper sheets are loaded, pre-processed, brought to the right temperature, fed into a printing engine, sheets are turned around, collected, folded, and so on—until the final product is ready. This complex system is modular and configurable, so different types of print jobs can be run as fast as possible. On the human side, operators load and monitor the machines, service technicians maintain and repair print engines, and engineers develop new types of engines and invent novel ways to overcome production challenges such as print quality and speed, or environmental factors.
Now, what about the design team? They work on a lot more than what you might imagine, from physical printer components to tangible user interfaces, web-based workflow management systems and documentation. They look at the services and processes around operation, maintenance and service, and they research the future of professional printing. And that's where you come in!
This project offers a fully funded 4-year design-research PhD position. In this design research position, you will explore how to design for and evaluate workflow integrations for these printing systems. Your project focuses on generating propositions for the design of adaptive, personalized user interfaces. You will design, implement, and evaluate new interfaces and workflow support for specific use cases. This project aims to generate new knowledge regarding workflow design for smart operator support, workflow-oriented and servitized predictive maintenance, and advances in the user interface design of high-tech systems. Together with a second design research candidate at ID, you will focus on
design, data and AI tools and methods that give the design team more insight in (1) how users compose their UI ecosystem, and (2) how different users utilize printers and software in their workflows. Methodologically, we will rely on data-supported ethnography, data-enabled design, and research-through-design. Throughout the project, we see opportunities to work with generative AI in product and UI adaptation for better workflow support.
Project backgroundCanon Production Printing (CPP, https://cpp.canon), formerly Océ, is a leading multinational manufacturer of high-end digital inkjet printing hardware and software for professional printing markets. CPP solutions are used by variety of customers in different markets, having different business models. In addition to supporting diverse businesses, CPP printing solutions are also used in varied ways and workflows, at different scales and process integrations. Even between two similar types of customers there might be considerable differences in how they organize their work, both at company and at operator level. To address this diversity, CPP is developing the Pigment Design System as one design system across the whole hardware and software portfolio. The Pigment Design System is the basis for all user interfaces (UI), making them highly flexible and customizable for an optimal and personalized experience. How users configure and interact with these UIs gives CPP an understanding about customer workflows and how CPP products are used in these workflows.
Eindhoven University of Technology (TU/e, https://tue.nl) is one of Europe's leading research universities. The Eindhoven area, in the southern part of the Netherlands, is one of Europe's top 'innovation ecosystems', with many high-tech companies and institutes. TU/e is intertwined with many of these companies and institutes, and research at TU/e is characterized by a combination of academic excellence, industrial relevance, and societal interweaving. The
Department of Industrial Design (ID) of the Eindhoven University of Technology (TU/e), founded in 2001, is the home for design research and education at TU/ewith over 850 students, both Bachelor and Master, 100 PhD students and postdocs, and around 45 research staff members. The mission of the department of Industrial Design at TU/e is Research on and Education in
the Design of Systems with Emerging Technologies in a Societal Context. The position is situated within the research cluster of 'Future Everyday'. The Future Everyday cluster investigates the everyday interactions between individual people and the highly interconnected technology that surrounds them. Researchers in the Future Everyday cluster measure, model and design for the user experience when individuals interact with social-technological networks in various professional settings in the high-tech industry.
Be part of an innovative multi-disciplinary teamIn your PhD project, you will explore the research question by applying the research-through-design methodology with hands-on designing and prototyping in close contact with the CPP R&D teams, users, and stakeholders of the Pigment Design System such as UX architects, UX designers, Visual UX Designers, Quality Leads and Workflow Architects. You will also collaborate closely with other design research PhD candidates at the Industrial Design department. Together, you will share design research methods, data, AI models, and technological platforms as complementary focus points. These will be closely involved in the co-creation process. Given the multi-disciplinarity of designers and researchers at CPP and TU/e, we will be able to rely on experts in design and design research but also data mining, process mining, federated learning, and hybrid machine-learning approaches to further refine analysis and design propositions.
The PhD will be under the supervision of Prof. dr. Lin-Lin Chen and Dr. Mathias Funk in the Department of Industrial Design at Eindhoven University of Technology. The project will be executed in collaboration with Canon Production Printing, Venlo; Frederique de Jongh of CPP is closely involved in the supervision of the PhD position. The project will be part of the TU/e EAISI program and therefore share, learn, and disseminate within the EAISI community and through the TU/e master programs Data Science and AI, AI in Engineering Systems. The project aims for open-access publishing of widely applicable methods and is organized to enable close collaboration and colocation of researchers from the project partners.
Prospective starting date: May 1, 2024.