Many consumers dispose of their electronics before their intended lifetimes, contributing to the growing amount of e-waste. Repair is seen as a promising strategy to extend product lifetimes,but many consumers encounter motivational, product and system barriers. Within the context of product design, emerging AI and IoT technologies may help mitigate these barriers to increase consumer willingness to repair.This Master’s Thesis explores the barriers consumers encounter when trying to self-repair dishwashers. In collaboration with ATAG, the DW60 dishwasher, their flagship model featuring the latest technologies and IoT connectivity, was used as a case study. ATAG’s professional and self-repair context, along with the DW60’s design, were analysed to identify key barriers and the potential of IoT and AI solutions throughout the consumer repair journey.The barriers start with a lack of effective triggers to encourage regular care activities, which can lead to product breakdown due to overdue maintenance. In case of product malfunction, error messages help identify the breakdown but offer little guidance for further fault diagnosis.Available documentation focuses on cause-oriented fault diagnosis but offers little help when a component is defective, leading to extensive trial and error with no assurance of finding the exact cause. Additional repair information is fragmented, difficult to access, incomplete, overly text heavy and can be difficult to understand for non-technical users.To address these barriers, this project introduces a concept that combines intuitive dishwasher design for repair with AI assistant support. When a malfunction occurs, users can scan a QR code displayed next to the error message to access a website-based AI assistant. This virtual agent guides them through fault diagnosis, repair decision-making, spare part sourcing, and component replacement. The system delivers adaptive, context-aware information and instructions, featuring clear descriptions, visuals, and safety warnings. Additionally, IoT-enabled sensors and cloud-based repair knowledge bases support data exchange and analysis. This enables real-time task verification and quick diagnostic testing. The system prioritises the most severe potential causes, leading to a more targeted and systematic approach to fault diagnosis and post-repair validation. These features make the repair process manageable for repairers while simultaneously building their confidence. This is further facilitated by a redesign of theDW60, incorporating intuitive disassembly and reassembly, including cues that also assist the AI assistant’s visual support.Qualitative user testing results show the potential of intuitive product design and IoT-supported AI guidance to increase consumers’ willingness to repair dishwashers, particularly during fault diagnosis and repair arrangement. Additionally, this system could be further developed and applied to the wider field of appliance care. Future research should therefore focus on further validation of desirability, feasibility and viability by both users and manufacturers. ... Read more

This project examines the barriers consumers face when attempting to repair personal electronics, with a specific focus on wireless Active Noise Cancellation (ANC) headphones. While these devices have become increasingly common, repair is often overlooked in favour of replacement due to psychological resistance, economic factors, and practical limitations. Through research into user attitudes and product architectures, this project identifies the main hurdles to repair, such as a lack of knowledge, intimidating product design, and insufficient support materials.

Based on these findings, this project proposes a solution that addresses the main challenges preventing user-led repair. The final concept introduces a diagnosis-to-repair system supported by an intuitive physical headphone design and an AI-powered digital assistant. The design focuses specifically on the four most common malfunction scenarios reported by users - cushion wear and tear, hinge breakage, charging issues, and audio malfunctions.

The experience is designed to lower the perceived complexity of diagnosis and repair by actively engaging users directly in the troubleshooting process. The proposed headphone design enables users to easily switch cables between ports, allowing them to quickly isolate issues without the need for tools or full disassembly. This encourages active learning through doing while keeping stress and confusion to a minimum. At the heart of the headphone concept is a tiered repair model - common, high-frequency issues, such as ear cushion replacement or battery swaps, are tool-free and quick, while higher-complexity tasks remain accessible with minimal guidance. The process is supported by a digital repair assistant, hosted on common messaging platforms like WhatsApp and Telegram, ensuring familiarity and universal accessibility to repair information when users need it the most. It guides users in identifying the problem, then adapts to their input and repair confidence level, modifying its instructions accordingly, while using helpful visuals, and offering alternative repair pathways- all in a single, accessible, and unified platform.

The result aims to support the broader goals of sustainability and circularity by making repair more approachable and attractive, reducing friction, and enabling users to make confident, informed decisions at the point of device failure. The end goal is to extend headphone lifespans and reduce electronic waste by re-framing headphone repair from a burden into an empowered, user-driven experience.
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