Canon Professional Printing (CPP), 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. Pigment Design System is the basis for all UIs, 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.
This project offers two 4-year design-research PhD positions. To address the goal of Canon Professional Printing, we will, together with the CPP design and R&D teams, focus on two clusters of research questions around UI/UX and functionality/service:
1. How can data and AI techniques help in getting more insight in how users compose their UI ecosystem based on the applications provided within the Pigment Design System. More specifically, we want to address the following questions:
2. How can data and AI techniques help in getting more insight in how different users utilize printers and software in their workflows. More specifically, we want to address the following questions:
This project aims to generate new knowledge and actionable methodological advances regarding workflow design for smart operator support, workflow-oriented and servitized predictive maintenance, and finally the use of digital twins in the user interface design of high-tech systems. The project will be part of the 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. The project leverages ongoing methodological developments in the Industrial Design department with other regional industries (for example, e/MTIC MEDICAID project), and will use and contribute to the ‘Data-AI in Design’ efforts at TU/e and beyond.
You will be part of an innovative multi-disciplinary team
The two PhD positions will be embedded in a multidisciplinary academic and industrial supervision team to tackle the challenges in a timely and effective way. The research will be carried out in three phases: contextual research, data-supported design, and evaluation and iteration.
Design Research PhD position 1: understanding customers and customer roles
In this design research position, the PhD student will explore how to use data-enabled design methods to understand and evaluate the context, the roles, and the workflows of CPP customers. During the first phase he/she will be carrying out contextual research by means of in-depth functional data collection and qualitative methods. In the second phase he/she establishes data-supported design. In the third phase he/she will be leading the evaluation.
Design Research PhD position 2: designing new workflow integrations with AI-supported personalization
In this design research position, the PhD student will explore how to design for and evaluate workflow integrations and work with advanced analytics to develop AI-supported personalization tools. During the first phase, he/she will be generating propositions based on the insights in the design of adaptive, personalized user interfaces in the Pigment design system. In the second phase, he/she will design and implement new UIs and workflow support. In the third phase, he/she will follow the evaluation and iterate accordingly.
Methodologically, we will rely on data-supported ethnography, data-enabled design, and research-through-design, and leverage CPP’s data platform and analytics expertise. Throughout the project, we see opportunities to work with advanced artificial intelligence to steer real-time data collection, product and UI adaptation and the modelling of workflows. Given the multi-disciplinarity of EAISI researchers and partners, we will be able to rely on experts in data mining, process mining, federated learning, and hybrid machine-learning approaches to further refine analysis and design propositions. The two PhD candidates will closely collaborate and share design research methods, data, AI models, and technological platforms as complementary focus points of each PhD position.
The PhD students will explore the questions 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. These will be closely involved in the co-creation process.
Eindhoven University of Technology (TU/e, www.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 a maturing department with over 650 students, both Bachelor and Master, and around 40 research staff members and about 10 lecturers. 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 PhDs 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 students. At the TU/e, the positions are 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 their homes, at work, in transit, while doing sports or going out.
Requirements for Position 1
Requirements for Position 2
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager dr. Mathias Funk, email m.funk[at]tue.nl.
General information about the Department Industrial Design, candidates will find on http://www.id.tue.nl.
Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services Industrial Design, tel. +31(0) 40 2475336, e-mail: HR-IndustrialDesign[at]tue.nl .
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
We invite you to submit a complete application by using the apply button. The application should include the following documents (all in English):
The deadline for applications is 19 February 2023. However, if you are interested, we invite you to apply as soon possible. Selection will begin immediately and continue until the position has been filled.
Please note that a maximum of 5 documents of 2 MB each can be uploaded via the apply now button. If you have more than 5 documents you will have to combine them.