Conference Agenda

It's evident that the year 2023 has seen the emergence of artificial intelligence in numerous professional settings, including the field of Industrial Design. Across all professional forums and associations of Industrial Designers, discussions are ongoing about this technology and how it will impact the professional practice of Industrial Design. Many professional designers and their teams are experimenting with the new tools that incorporate this technology, exploring their possibilities and analysing how their application can add value at different stages of their design process, considering the strengths and weaknesses of their teams.

In the academic sphere, there has been a proliferation of publications in recent years exploring and mapping AI-based tools that can be applied in different stages of the design process. The reality is that many of these tools are still in the research and development phase, making it challenging to identify which ones will genuinely be implemented in professional practice. However, beyond the tools, what is actually happening in the day-to-day professional practice of these designers? What are the challenges that AI is creating for professional Industrial Designers?

On the one hand, AI tools require a certain level of expertise and knowledge to use effectively. This can be a barrier for some designers who may not have the necessary skills or resources to use these tools. On the other hand, there is the market and the clients who are also aware of the transformation being brought about by AI. Their demand and requirements will also change as other professionals offer design processes incorporating AI tools.

Consequently, what will happen with the training of future industrial designers? What new skill and capability needs arise from this revolution? What convergence is occurring between disciplines such as AI algorithm programming and industrial design? Will this new paradigm change the profile of the designer and the composition of design teams?

This contribution focuses on the perspective of professional designers, who are the prospective employers of our students. These professionals at present, can provide a more realistic view of what is happening in professional practice and what profiles of young Industrial Designers can bring value to their teams and companies in the coming years.

To achieve this, our team has conducted qualitative and quantitative research among industrial designers working in a wide variety of companies, studios, and design consultancies. Through questionnaires and the snowball technique, we have gathered feedback from of professionals in several European countries, identifying and understanding the main barriers and benefits of these AI tools, as well as the training needs perceived for the new generations of Industrial Designers.

The conclusions of this work represent a significant starting point for the changes to be introduced in the curriculum of universities offering degrees in Industrial Design or Industrial Design Engineering. Furthermore, our conclusions can help identify opportunities for developing new AI tools specifically for the Industrial Design process, targeting the less covered phases of the design process.

Within tertiary education disciplines traditionally regarded as “technical”, students have a notably tendency to focus on the skills required for their intended profession; be that mathematics, engineering competencies, coding, manufacture, design, chemistry, to name just a few. There is often less focus on “professional” competencies, such as presenting, orating, negotiating, bargaining and interpersonal communication, sometimes referred to as “soft skills” although this term is somewhat dated and is largely being replaced in the lexicon with the more appropriate “professional skills”. This presents an interesting paradox as frequently many graduate employers express a significant desire to hire graduates who have developed their required technical competencies but additionally professional competencies. Indeed, in a great many instances graduate employers actually place more of a value on the professional skills of a prospective hire as they will undertake additional or more bespoke technical training during on-boarding of new hires in their particular practices. It is a request frequently encountered from industry advisory boards to develop students so that they have a good level of professional competency when they enter the graduate employment market. This raised the question of how this can be best achieved when a curriculum has many technical competency based classes but comparatively few professional or interpersonal competency based classes.

While presentations and critiques have been beneficial up to a point, it is observed that if these are offered as informal or formative parts of the curriculum participation can be low and no demonstrable benefit is achieved, particularly since in-person attendance has presented challenges following the increase in online modes of attendance. Additionally the increasing prominence of generative AI tools has mean that many educators are rethinking their means of assessing learning and understanding of subject matter. Accordingly, a new form of experimental assessed oral presentations and “flipped” classroom sessions and activities have been developed. While these have been successful to an extent they only address some aspects of the professional competencies required and typically only really “one way” activities where any back and forth discussion or exchange is limited. As part of designing a new masters class within the technical discipline of product design at the XXXX in XXXX it was sought to create a new class where these professional skills, including negotiation, discussion, interpersonal communication and debate are developed and fostered. This approach has precedence in other fields such as medicine, language, culture, education, politics and business, and has demonstrated success in these fields. Could such an approach to learning activities and assessment work in the product design technical setting?

This research explores the efficacy of debate activities and assessment in developing the professional competencies of students enrolled in technical disciplines. It will address whether or not there is an improvement in these competencies amongst students and additionally if student’s confidence in these competencies is improved.

Progress in digital design tools has continuously changed the engineering design process. The application of Artificial Intelligence (AI) opens up completely new opportunities for the development of innovative products and systems. Computational design synthesis techniques such as generative design can be used to explore a design space with many solutions optimized for different objectives that may even exceed the capabilities of experienced human designers. By using CAD tools that deploy these techniques, designers no longer have to limit themselves to the variation and simulation of a few parameters, which is due to the time pressure in product development, but also to the lack of specialist knowledge of the complex correlations. Instead, a broad open solution space with an unrestricted number of potential solutions is provided by computational support. Engineering designers thus can focus on evaluating the solutions and selecting the solution that makes the most sense for the specific application. This is dramatically changing the product development process. The impact of AI on the design process, the handling of the new techniques and methods, as well as the implementation for future product development and innovation activities results in an enormous need for training and further education of designers.

This paper presents a comprehensive skill development programme for industry professionals and engineering students to provide the necessary skills (methodology and tools) in terms of generative engineering, design automation, structure and topology optimization. It includes an introduction to generative engineering (GE) as well as its foundations and software applications. The concept of the skill development programme is predominantly organized as eLearning divided into learning nuggets but is complemented by an additional hybrid practical part. The paper describes the approach employed in developing this program and highlights its outcomes. The teaching methodology and concept along with the focal teaching points are introduced. In addition, subsequent optimization measures and requirements are determined, which are based on the evaluation of the learning paths and learning nuggets carried out in the project by industry participants and their feedback. Finally, the potential of the suggestions for improvement and the resulting changes are discussed.

Extended reality has better learning in less time and optimizing resources. This paper explores a student-centric course experiment rooted in the application and practice of a recently developed educational platform. The Tec21 educational model is based on the development of disciplinary and transversal competencies, and for this, the design of educational innovations is fundamental. In recent years the design of virtual simulations has rapidly increased in number as well as in sophistication. Virtual laboratories based on virtual reality and augmented reality had exponential growth, which has kept its pace of creating new platforms for lessons based on XR technology.

Although present research has presented several examples that showcase virtual environments and have purposely been designed for students to learn from, the platform independence is growing where users can experience different learning formats with minimal disturbance as technology is striving to reach further seamless solutions. This research presents the results from specific learning scenarios through so-called DBT (design-build-test) exercises for different groups of industrial engineering students. The students were introduced to the MxREP simulator and the TecXR platform. These are augmented guideline design tracking, intuitive support, and virtual reality design scenarios that allow students to repeat the physical DBT exercise in a timely manner to provide more depth and understanding of step-wise design parameters. The specific course exercise was designed to emphasize life cycle educational activities that originate from the lecture design objectives, instructions and activities, and definition of educational objectives. Also, the design of simulator parameters and the interface with virtual and augmented reality lessons to achieve three essential objectives development of skills, learning, and engagement. The findings showed that students show great appreciation towards utilizing XR as part of their learning. The variation of the platform noted that the more fixed VR process enables it to focus more on process-related design steps, whereas the augmented support increased co-design engagement among student cohorts that participated.

Despite the rapid development of artificial intelligence (AI), skepticism persists among educators regarding its role in design education. This study uses a systematic literature review to locate and summarize the core papers from 2020 to 2023, categorizing the role of AI in design education. Following the PRISMA method, 35 papers were selected for review. The research reveals the potential impacts of AI on developing students' design skills, perceptions of AI applications among students and teachers, and challenges in implementing AI technologies. Drawing from these findings, the study proposes implications of AI on both the practice and theory of design education. By shedding light on the current state of AI integration in design education, this research aims to inform educators, policymakers, and stakeholders about the opportunities and challenges presented by AI technologies. Understanding these dynamics is crucial for effectively harnessing AI's potential to enhance design education and prepare students for future demands in the field.