Conference Agenda

Trust is fundamental in our acceptance and decision-making of that which we surround ourselves with. This paper reviews existing frameworks and discourse around types of trust and identifies key factors for trust formation, maintenance and ongoing use. It establishes a need for a framework focusing on the design of trustworthy objects, especially those that are technology-embedded. It identifies a series of factors and recommendations when designing for trust. Stemming from a creative practice-based PhD from Aotearoa, New Zealand, the project seeks to design a product for the horticultural industry that enables more efficient data collection around fruit size. When yield correlates with financial outcomes, growers distrust data from the packhouse not matching estimations. Using digital technologies generates richer datasets safely and efficiently, allowing for a greater understanding of the state of the orchard at a given time. The factors found have relevance and application across a broad range of industries.

With a diversifying workforce well-being is an increasingly important topic to be addressed in manufacturing. Whereas mental well-being has been well studied in the HCI community for knowledge workers, well-being for factory workers has been mainly assessed in terms of ergonomics and task optimization. Concerns are about safety and accident prevention, but not about the tacit experience of the workers themselves. In this paper, we analyze an assembly line from two viewpoints: the HCI/Design, and the industrial engineering. We show the differences and commonalities in methods and identify both sides limitations. We present four themes of well-being which emerge from the combined understanding of both sides and identify the gains of a combined approach. This paper presents a first step towards a human-centered understanding of well-being in factory environments and towards design opportunities for digital interactive support systems.

This research examines how a New Product Development (NPD) design team incorporated multidisciplinary knowledge to redesign a modular cab. Design teams that implement digital innovation often use cutting edge techniques, such artificial intelligence and big data, to inform their design decisions. However, these techniques are often managed by other teams with different knowledge backgrounds. Therefore, optimising learning processes between multidisciplinary teams is crucial to design new products effectively. This research reviews existing team learning processes, then conducted a case study to examine how a NPD design team learn from an interaction team to integrate knowledge into their design process. Aside from the information processes established in the literature review, we found that design teams working in interdisciplinary projects also translated and contextualised their information to ensure knowledge accuracy.

Disabled people, from younger to older adults, are at comparative disadvantage regarding work. Design for inclusion at work tends to focus on individual adaptations (often stigmatising) or general accessibility guidelines (often insufficient). Furthermore, there is a tendency to focus on inability rather than on extreme abilities, which seem to be the ones enabling workers to appropriate existing products and create their own designs. Therefore, design research requires more input from diverse workers as users to inform the design inclusive industrial workstations. Departing from theory and ending with analyses of workers' designs, this paper argues that the articulation of the concept of ‘extremes’, as used in inclusive design theory, with the study of appropriation in industrial shopfloors can be a source of information, inquiry and inspiration for new design research towards worker inclusion.

In the industrial robotics field, mastering the operation of traditional industrial robot teaching systems requires operators to undergo intricate training, hindering production efficiency. To address this challenge, we proposed an interaction design framework for industrial robot teaching systems based on tangible interaction theory. This study outlined how our proposed framework, anchored in tangible interaction paradigms, provided architectural direction for the design of these teaching systems, markedly enhancing operators' efficiency in learning operations. We utilized this framework to direct the interaction design of a welding robot teaching system and validated the framework's feasibility through experimentation. Experimental results revealed a notable enhancement in operator learning efficiency with the implementation of the new system compared to the traditional teaching system. This study provides theoretical and practical evidence for the reduction of operational complexity in industrial robot teaching systems, enhancement of production efficiency, and optimization of the working experience for operators.