healthcare system. Over the next 10 years, diagnosis and survivorship rates of colorectal cancer are expected to rise due to better detection methods and treatment innovations. Therefore, Remote Patient Monitoring (RPM) is being explored as a telehealth solution, but it faces challenges in addressing the multifacet and subjective nature of mental health. Current mental health assessments are often biased and limited by a Western, individualistic perspective. This creates an opportunity to design a more inclusive, collective RPM strategy that involves a patient’s social environment, especially their spouse, as dyadic coping (shared stress regulation) is more effective than individual coping. Therefore, the objective of this thesis is to investigate ‘how to design a strategy to remotely monitor and contextualize mental health by leveraging romantic couples’ collective and contextual data’.

This thesis indicated that social interaction is essential in maintaining relationship satisfaction, crucial in enhancing effective dyadic coping. A data-enabled design approach was applied to design a custom remote research tool-kit for seamlessly and compliant data collection, and contextualizing social interaction through visualizing and co-analyzing the collected data. User research was conducted over a period of 7 days (where 2-3 days were dedicated to data collection) with three Dutch, romantic couples aged between 55 and 75 years old, living together. Thematic analysis resulted in design guidelines, along with identified strengths, limitations, and future research opportunities regarding social interaction interpretation and contextualization. This thesis contributes to the design and research community by offering insights into romantic couples' social interactions and providing guidelines for creating holistic, collective RPM strategies for telehealth innovations, beneficial for cancer survivorship follow-up care.

Cancer is a complex disease marked by uncontrolled cell growth and has a widespread impact on individuals and society. Its incidence has been increasing globally, with a notable rise in cases in the Netherlands from 56,000 in 1989 to 118,000 in 2019. There will be approximately 232,000 new cancer diagnoses by 2032 (Source: iknl.nl).

Breast cancer, the most frequently diagnosed cancer among females worldwide, is a significant concern amid rising cancer rates (WHO, 2024). In the Netherlands, it is among the most prevalent cancers, with 15,634 cases reported in 2023 (NKR Viewer, n.d.). Despite significant advancements in diagnosis and treatment, cancer remains a severe and multifaceted challenge and impacts individuals, their families, and society as a whole. For individuals, the illness inflicts significant physical harm, manifesting as chronic pain, fatigue, loss of appetite, and other symptoms that drastically reduce quality of life. The psychological and emotional toll is equally profound, with individuals and their loved ones experiencing intense fear, anxiety, and stress (Costa et al., 2016). Following a diagnosis, individuals encounter a flood of information related to their condition, treatment options, supportive care resources, medical regimens, etc. making it overwhelming and complex. This complexity is amplified in breast cancer due to the multitude of subtypes and variants, accompanied by a wealth of information accessible online.

While healthcare providers strive to communicate information effectively through verbal and written formats for the individuals to navigate in this unfamiliar world, their time constraints and workload frequently restrict the depth of support they can offer. This results in individuals turning to gather information from diverse sources, such as online platforms, family, friends, etc. This decentralised approach is unavoidable and offers diverse views resulting in complexity, ambiguity, and confusion and leading to “information overload”. Information overload is a multi-dimensional construct and a complex phenomenon and usually occurs when the available information surpasses one’s capacity to absorb it effectively. There are several factors that cause information overload and these factors result into intertwined effects like inability to effectively process, understand and utilise the information, etc.

Given the prevalence, the focus of the study is on breast cancer in women and aims to address these challenges by supporting them in understanding the complexities of the cancer diagnosis and treatment options based on their preferred level of involvement, ultimately enabling them to make informed decisions in their care journey. The findings from this project can benefit the healthcare system as a whole, the stakeholders involved, including individuals with breast cancer, their companions, and healthcare providers, by equipping them with the support tools to navigate and understand the healthcare journey. Furthermore, it can provide the necessary information support to individuals post-diagnosis, alleviate the burden on healthcare providers and strengthen communication between providers and patients.

This graduation project, conducted in collaboration with Agis Innovations, aimed to develop a cow localisation solution that could be integrated with existing ear sensors for cows. This addition was crucial as current cow localisation solutions were inaccurate, expensive, or not user-friendly. The inability to promptly locate cows can cause unnecessary pain for the animals and reduce farm efficiency. Moreover, timely cow localisation can reduce the need for fertility hormones and antibiotics.

The project was divided into two main aspects: technology and user interaction, allowing for separate evaluation and design optimisation. A comprehensive literature review on cow localisation technologies and the existing market revealed the need for a solution that is highly accurate, cost-effective, supports long battery life, and offers a long detection distance. No existing solutions met all these criteria. The technology analysis identified an unused, novel, and promising new distance measuring technology. User research highlighted the shift from small to large farms, requiring a larger, often low-literacy workforce. Literature and empirical data from farmer interviews and worker questionnaires pointed to low work engagement, particularly in cow localisation tasks. Consequently, two user evaluation criteria were established: intuitive user touchpoints and a user interface (UI) that enhances work engagement.

From the user perspective, analysing the complete workflow of cow localisation revealed three phases, each having different detection distances and accuracies. Integrating these phases provided a solution with both a long detection distance and high accuracy. Insights into farm workers’ engagement revealed unmet fundamental needs. By incorporating personal profiles, hands-on tutorials, and gamification features like leaderboards and rewards, the UI was designed to enhance workers’ sense of competence, recognition, and purpose. This improved engagement is anticipated to enhance cow care and increase productivity. The UI’s intuitiveness was based on the three localisation phases, with each phase having tailored visualisations to guide users towards the cows effectively.

In the technology aspect, the new technology was first evaluated through field testing and Python simulations to prototype localisation ideas. A physical prototype demonstrated the feasibility of locating a tag device, achieving an accuracy within 2 metres. This met the accuracy requirement, allowing users to identify cows easily. The limited use of routers kept costs low, while smart location update frequencies minimised power consumption, supporting long battery life.

Integrating the user and technology aspects addressed the research question. The localisation solution is feasible, requiring minimal hardware changes for Agis Innovations. It is viable, leveraging the latest technology with a user-centred development approach, and desirable, providing an essential tool for efficient herd management. This solution not only boosts productivity but also enhances cow wellbeing, aligning with the project’s ultimate goal of improving animal welfare.

With an increasing population and more prevalent staff shortages in healthcare, digital technologies can play a crucial role in bridging the gap to deliver value-based healthcare. Therefore, any additional service integrated into their workflow must either enhance efficiency in delivering care or add significant value to the care provided. Anything less would not align with their context of use and, consequently, would not effectively reach the end-user (patient).

As a market leader in joint arthroplasty, Zimmer Biomet introduced the mymobility care management platform. This platform offers remote patient monitoring, personalized care plans, telehealth services, and real-time data analytics to enhance patient engagement and streamline healthcare delivery. However, the adoption rate of this platform remains low, particularly when compared to the company's broader success in the implant market.

Through an analysis of quantitative patient outcome data and demographic data related to its use, it was found that one of the primary barriers to adoption was the low eagerness among healthcare professionals (HCPs) to use the care-management platform.

By leveraging the usage data currently collected by Zimmer Biomet and conducting qualitative inquiries, barriers to adoption were identified and opportunity areas were mapped. These insights led to the creation of a strategic roadmap designed to boost the adoption of the mymobility platform over the next five years.

User-centric design practice rely on journey maps and personas as a way to communicate user needs to the design team (Lanius et al., 2021). However, journey maps in practice have been found to lack a dimension that could inform designers about intrinsic cognitive needs of the user. This research project aims to address this gap by exploring ways to make human cognitive data designer-friendly. Through multi-study approach, including the Research through Design (RtD) (Godin & Zahedi, 2014) method, the study investigates dimensions of the relationship between designers and cognitive user data to make it easy-to-approach in future.

Following the context exploration studies, designers' perspectives and practices regarding cognitive user data are delved into. Findings from exploratory interviews reveal varied interpretations of cognitive data, challenges in accessing and visualizing data, and a keen interest in its potential benefits for design processes. Designers identify time constraints as a major hurdle but express enthusiasm for the posterity and revisiting advantages of effective cognitive data visualization.

The RtD method helps in investigating a way of presenting holistic data to designer that merges intrinsic and extrinsic factors of the user. Designers favor clarity, interactive exploration, and reliability in data presentation. The study provides a comprehensive list of neurophysiological measures that can aid designers in decision-making. Additionally, insights into designers' thinking styles, distinguishing between big-picture and detail-oriented thinkers, add a nuanced layer to understanding their affinity with cognitive data.
The report acknowledges limitations, including biases in the Research-through-Design method, reliance on self-reported data, and the controlled environment of prototype evaluations. Future research is encouraged to address these limitations and enhance the ecological validity of findings.
In conclusion, this research offers valuable insights into integrating cognitive user data within designer practices and establishes a way of integrating observational data with user journey maps. The findings provide a foundation for developing tools and approaches that align with designers' preferences, ultimately enriching the design process through meaningful integration of cognitive insights.

The project focuses on validating ultrasound plant sensor technology through grower insights. The primary goal is to understand how growers monitor their crops, using terms like "vegetative," "generative," "strong," and "weak." Additionally, we aim to gather their reasoning behind certain plant assessments. By correlating these insights with data from ultrasound sensors, we hope to provide interpretable information that growers can use in their cultivation practices.

Making cultivation more efficient for growers is crucial to the challenge of producing enough food for the world’s growing population. By using technology that supports growers, we can help them scale up their operations and ultimately produce more food.
We conducted interviews to investigate how tomato growers monitor their crops. Usability testing was also performed to design an intuitive, straightforward way for growers to share their insights. The result of this effort is an app that collects growers' subjective plant assessments efficiently.

The next crucial step is to begin collecting data through the app to see if there’s a common truth in the growers' insights. If such a pattern is found, the growers' assessments can be correlated with the ultrasound sensor data, and ultimately provide actionable insights back to growers in the terms they frequently use: "vegetative," "generative," "strong," and "weak."
Ultimately, these actionable insights would be combined with other data types to generate tailored advice for the grower. An exploration will be done to determine how this could take shape.

Our routine interactions with connected products and services result in the collection and indefinite storage of personal digital-trace data. These data are increasingly entangled with our lives. What we experience is scattered around multiple data points: our browsing history can account for our interests and worries, our messaging logs can account for our social relationships, and our purchase history can account for our dietary preferences. Digital-trace data is increasingly valuable for scientific research as it can offer insights into specific aspects of our daily experiences. Researchers across various disciplines have been developing methods and tools to access these data. One of these, and the focus of this thesis, is data donation. In this thesis, I develop alternative data donation approach informed by the principles of Data Feminism. This approach, called Sensitive Data Donation, aims to empower donors to know and care for their data and promotes different forms of knowledge and participation. It is directed at intimate research contexts, such as the home and the body, which are inherently private and situated spaces where it is crucial to explore and negotiate people's relationships with their data. @en

Behavioural data that shows how and what people do could help designers unlock new ideas and perspectives about their users. However, collecting this data is expensive and time-consuming, and ethical concerns inevitably arise because the data often contains personal information. Ortega presents designerly data donation as an efficient and ethical approach that encourages the active participation of users to obtain contextualised data (Ortega et al., 2021). This subtle switch of attitude towards data collection will help designers reduce concerns about budget or invasion of privacy. Designers can build up proper triggers to inspire users to donate their data and provide enough information to enable donors to autonomously participate in their control and choice. While its potential has been defined, there are a few challenges to further integrating this concept in practice. In particular, designers must understand the whole system to plan the right strategies to call for donors, taking the right action at the right time. With this in mind, the main focus of this project was how to deliver the concept of designerly data donation as a design method for designers in practice. A design challenge and related activities were conducted with UX designers of The Valley and the data-centric design lab at TU delft, after which I proposed the initial shape of the DDD toolkit that can be used in practice as a result of this project.

The number of cardiac patients (people with heart problems) is growing all the time. Given that any person who encounters a cardiac condition should undergo cardiac rehabilitation (CR), a program to rehabilitate the heart and learn to manage it in daily life, it is expected that the health system will also grow exponentially in order to meet the high care demand. However, this is not the case. Currently, only 28 percent of the eligible patients get referred to CR because the health system does not have the capacity to include all of them (Van Engen-Verheul et al., 2012). Moreover, the full take-in and supervision of the cardiac patients in CR lead them to find the transition to their daily life after finishing CR quite hard.

One solution to tackle this problem is to delegate some of the care parts at home, called blended care, so that more patients can enter CR while learning to manage their condition early on.

However, there are two main problems concerning this structural change in CR care. First, because of the loss of frequent contact with health professionals, implementing blended care risks losing personalization in care.Secondly, when delegating care at home, health professionals lose insights and feedback into the care delivered at home. Therefore, patient health outcomes might become compromised.
In this regard, this project proposes a design concept to support the blended CR care for the patient (with an app) and physiotherapist (with a dashboard) by homogenizing the care delivered at home and the CR center while centralizing the patients by making them active and responsible for their care. Moreover, it personalizes the CR care path, not in terms of exercises or changes in the workflow, but in a way that makes sense to the patient following their CR interests. The concept is composed of an intelligent solution with three different modules that utilize the feedback loops integrated into it to understand the patients’ input and adapt to them, realizing the personalization effect.

The first module concerns the personal goals that patients need to set as they enter the care path and explains the motivation and type of the goal the patient wants to achieve. The second module aims to engage the patients with their exertion data during the care path (a subjective score from six to twenty with which patients report how heavy they find an activity) by helping them actively reflect on their performance and goals to take necessary actions. It realizes this effect by understanding their exertion zones and asking patients subsequent questions to make sense of the data via a quick check-in after rehabilitation. The third module uses the outcomes of the previous modules to provide personalised insights and advice.

This thesis demonstrates that there is a need for improving the working conditions of gig workers. It establishes a need for an increase in empathy from consumers towards delivery riders. Delivery riders often make use of E-bikes which provide an excellent foundation for data collection. The main research question is stated as follows:

How can empathy towards delivery riders be increased through communicating behavioural data to the consumer?

After establishing background and related work through desktop research, an exploration into the implementation of multiple sensors was initiated. This led to the insight that communicating heart rate data is the most promising dataflow to evoke empathy. The effect of communicating live heart rate data, next to static personalised information was empirically tested. After which all insights were synthesized into 5 design drivers which provided input for a brief design cycle. The final output is a demonstration, including a prototype, of a proof of principle that evokes empathy through communicating live heart rate data.

The most important insight substantiated in this thesis is the positive correlation that communicating live heart rate data has to the experienced empathy from end-consumers towards delivery riders. This led to the final proof of principle that revolves around a way to implement this into the delivery service context.

The conclusion of this study is that there is a strong indication that showing live heart rate data to consumers increases the experienced empathy. This could be implemented in various ways and provides a foundation for future work. More research is needed to establish the exact origin for the increase in empathy. This study is limited to exploring one way of communicating live heart rate data so more research is needed on different possibilities regarding visualization, communication and information versus the effect on experienced empathy.

Intelligent and connected services have become essential in the manufacturing industry. The surge of these services has even started a new phase of industry; industry 4.0. The COALA consortium aims to develop a service to assist operators within this new industry. The COALA consortium is an European Union Programme and aims to develop a Digital Intelligent Assistant (DIA). The DIA supports operators in situations characterised by cognitive load, time pressure, and little or zero tolerance for quality issues with trustworthy AI components. Diversey is one of the consortium’s partners and perceives COALA’s DIA as a viable solution to their stoppage challenge on their production lines in the factory. These stoppages can be caused by various bottlenecks, which are hard to determine due to the production lines’ complexity and processes. Therefore, this thesis explores how to prepare for AI service adoption within the factory of Diversey. However, management from the Diversey factory has attempted to identify the bottlenecks by collecting production information through operator data entries. Unfortunately, the operators did not provide the tool with quality data entries. Therefore, replacing this tool with the DIA most likely not succeed, especially when the new tool utilises AI technology that requires learning data to generate insights. In order to explore this resistance toward new tools within the factory, I used the frame creation method of Dorst. This method excels at finding innovative solutions for problem definitions with previously unsuccessful attempts. The method explores underlying themes within the context to reframe the problem definition and find new solution spaces. The themes are formulated from interviews with management, eight support staff employees across four departments, a team lead, and six operators. Four themes are generated by analysing the values, interactions, and ‘currency’ exchanged between stakeholders. These themes regarding new tools describe the unclear contributions to operators’ work, the lack of acknowledgement regarding operators’ role and expertise towards production improvements. These themes result in a lack of trust between operators and management, which diminish the willingness to adopt new tools. Additionally, management expresses concerns about the themes expertise and consistency, which are essential to the manufacturing industry. In order to address these themes, COALA’s DIA is reframed as a stage for expertise and exploration. Instead of simply requesting data entries, operators are put in the spotlight where they can showcase their knowledge and expertise. Additionally, this stage provides a space for operators to explore production improvements through collaboration with COALA’s DIA. The framing of the problem definition addresses the data collection aspect of COALA’s DIA. However, AI systems change over time as the systems adapt to the data input. Additionally, the thesis did not assess the users’ perception of the current DIA interface. Therefore, I recommend further research into human-AI interaction with regards to the system’s evolution over time and the interface. Lastly, the themes are generated from one production line’s operators who are experiencing the most stoppages. The themes cannot directly be generalised to other production lines as the number of stoppages, or other contextual factors can influence the themes.

This Master’s thesis looks at the development of a Service Design solution for a Supportive Health System in the field of nutrition. The project is scoped within Clear, a young organisation using Continuous Glucose Monitoring technology (CGM) to support better nutritional habits. This thesis applies a mixed-methods approach, integrating quantitative and qualitative data collection and analysis to answer the following questions: (1) How shall responsible parties generate a Preventive Health behaviour in the in- dividual? (2) How shall design parties integrate data in the design of Supportive Health Systems? And (3) How shall organisations deliver services that integrate Supportive Health Systems to facilitate Preventive Health Behaviour? The end goal of the final service solution presented in this thesis is to offer a proof of concept for a viable proposition in the emerging field of Personalised Nutrition. It is meant to be a guide for implementation to the collaborating organisation, and an actionable way to provide inspiration for key stakeholders of the field.

Millennials, a generation of individuals born between 1981 and 1996 that are shaping the current working class. One trait that makes millennials stand out from other generations is that their generation is the most stressed out. It is estimated that 20% of employed millennials in the Netherlands are suffering from symptoms due to stress. These symptoms include less life satisfaction, tiredness, and, most importantly, insomnia. The fact that stress causes insomnia makes stress a relevant problem for Somnox, as its mission is to help 100 million people sleep better by 2030. Somnox is a Dutch scale-up that focuses on developing companion-like innovations that improve human wellbeing through the power of breathing. The fast-growing company is on the look-out for new ideas to expand its product portfolio. One of these ideas is a portable breathing regulation device. The assignment’s initial brief was to turn this rough idea of a portable breathing device into an advanced concept design. I approached this by adopting an iterative approach in which I quickly ideated, built prototypes, and validated these with users. This approach has led to the final concept: the Somnox Mini. The Somnox Mini is a portable breathing regulation device that simulates breathing motion using robotics. By following the device’s breathing frequency, the device guides the user in slow breathing - which is a breathing exercise in which the breathing frequency is reduced to 6 breaths per minute. Research shows that breathing at this particular frequency induces a biological phenomenon called respiratory sinus arrhythmia (RSA), which synchronizes the heart rate variability (HRV) and breathing frequency. This stimulates the body’s relaxation response. Long-term practice of slow breathing has been proven to balance overactive stress response and improve insomnia symptoms.

The goal of this thesis was to design a way for Ford to provide users more value during long-distance Battery Electric Vehicle (BEV) trips. Users tend to buy their vehicle for the 95th percentile of use-cases. In the Netherlands, the average amount of km driven per day is 32 km, which is easily covered by any BEV currently on the market, without the need for charging during these trips. This means long-distance trips are the 95th percentile of use.

For mass-market BEV adoption, the Early Majority needs to be attracted. Within the Early Majority consumer segment, there are certain target groups that are most likely to adopt BEV driving. These are the potential BEV drivers and were identified through literature research. However, these target groups are not yet investing in BEVs due to the following adoption barriers that play a role in long-distance BEV trips: charging time, charging infrastructure and range. Through qualitative research such as interviews, observations and netnography, the reasons behind these adoption barriers were researched.

A solution has been created that mitigates these adoption barriers. The solution is a digital, data-driven, in-vehicle service system. The technical working principles of the service were designed with a new method that has been created along with the concept development, called Data Journey Mapping. This Data Journey Map shows how the different components within the data ecosystem communicate and what data they transmit. Together with Ford engineers, the working principles of the service system have been validated.

The solution has been validated with potential BEV drivers and current BEV drivers. Both groups stated the solution has significant added value. Potential BEV drivers stated that this solution would pull them toward investing in BEVs. Current BEV drivers stated that this solution could be decisive when comparing BEVs.

By launching this service system, adoption barriers of Potential BEV drivers are mitigated. This could result in an acceleration of BEV adoption in the Early Majority consumer segment, which is needed for the mass-market adoption of BEVs.

Dutch primary school teachers are strapped for time currently, and this is impeding the adoption of innovation. This is also a problem for Faqta, who are trying to sell their innovative teaching method. To convince teachers to learn, several theories and strategies are explored in this report, and how they can be applied on a digital video learning platform, the Faqta Academy, to answer the question “How can primary school teachers be inspired & motivated to learn & apply new educational methods with the Faqta Academy?”. The three most effective strategies to convince and captivate teachers are Microlearning, Self-determination Theory and Gamification. Microlearning lowers the bar of entry, while gamification keeps the attention over a longer period of time. Application of self-determination theory makes sure that teachers can actually internalize the motivation to apply the learnt material, by promoting Autonomy, Competence and Relatedness.This report explores how to apply these to Faqta’s Academy by introducing several design strategies in a framework for motivation, and applies them to the Academy through a workflow.

Data-centric research is all about trying to obtain useful insights on products that its researchers trying to create/design by collecting usage data on their prototypes. This type of research, usually performed by data-scientist, make use of machine learning techniques in order to improve any system or product that makes use of automated decisions. Now that other researchers, in this case researchers from design studies, would like to perform data-centric research. Therefore, they must be made aware of the issues that could be introduced by using machine learning to automate decisions in electronic devices. To address the issues around bias, we thought that it would be good to make them aware through some type of system where they should be made aware of bias. So we proposed that there was a need for a system where the user could explore bias present in the dataset or introduced by machine learning practices. To be able to find biases we had to decide which bias toolkit which led to use of the AIF360 toolkit that we eventually used to create FairData. FairData lets the user explore bias in datasets that include machine learning predictions by going through and iterative process consisting of a exploration stage and a result stage. The exploration part contains the parts for analysing the datasets by going through the attributes and making small modifications to the dataset. At the results page of this system it will show a change in bias represented by multiple metrics to support the users in becoming aware of bias. The experimentation part of this thesis showed that our system is able to inform two different groups of participants (compute science & industrial design) about the bias present in the dataset. The experiment made it clear that even though participants have different behaviour when analysing/exploring the dataset, they all tend to become aware of the bias by looking at the different metrics provided by FairData. It also seems that it is possible to support users in trying to reduce this bias as they can see the effects of the modifications done to the dataset.

The thesis aims to investigate how the Sleep Robot system (a Sleep Robot, its application, and servers) can adopt a data-enabled loop to make optimal use. The research has three main objectives: (1)understanding the needs and concerns of using the Sleep Robot system in different user profiles, (2)building a data loop of the Sleep Robot system with subjective and objective data, and (3) identifying the design principles of long-term engagement in a data loop.

To answer the research question and fulfil the objectives, the thesis adopted a four-diamond design process. In the discovery phase, the research reviewed the literature on personal informatics and sleep solutions, then plotted the Somnox data ecosystem. In the refining phase, the user research was performed to obtain profound insights, create a journey map, and user profiles by using a sensitizing diary, fetching data from servers, creating data visualization, and conducting interviews. The user research found that users stick to standardized breathing settings without engaging themselves in self-experimenting with breathing settings due to the lack of guidance and support. Thus, the project’s design goal is to let users feel guided and at ease during self-experimenting different breathing settings.

By going through creative sessions and user testing in the developing phase, the research found out four essential design elements to achieve design goal: (1) step by step learning experience, (2) dynamics of breathing rate, (3) growing together through empowering the breathing recommendation system, and (4) breathing with a specific goal which reflects causes of poor sleep. Eventually, the proposed design integrated these four elements into three levels of personalized breathing rhythms, including customized breathing, optimized breathing, and contextualized breathing.

In the evaluation phase, the proposed design was evaluated through user scenarios and high-fidelity prototypes. The results showed that users highly appreciated the guidance and ease through measuring personal conditions to tailor three-level breathing rhythms. This study emphasizes the transition role of the proposed concept from three-level of personalized breathing with a data loop and, ultimately, toward the adaptively synthesized breathing.

This thesis project investigated how user-centred design(UCD) contributes to the railway maintenance planning optimisation. A new UX concept and digital prototype were designed to provide intuitive interaction and clear structure to support the planners confidently and independently optimise railway maintenance planning on a digital platform.

This project is under the context of the Dutch railway infrastructure maintenance. With increasing demands for transport on the Dutch railway, optimising maintenance planning for existing infrastructure is challenging for the Dutch railway network management organisation ProRail. Thus, a data-analytic software ProRail Maintenance(PRM) for railway maintenance planning optimisation was developed for the maintenance planners at ProRail. However, as an analytic tool, the outcomes and functions came first for the company while the user experience(UX) was neglected at first, which leads to a series of usability problems and requires much learning time from the users.

Based on the above situation, two initial research questions were proposed: “What are the causes of these usability problems?” “Will UCD help to improve the UX of PRM and How?” A series of UCD methods were used in the whole process to understand users’ needs, generate and iterate concept and the final design was evaluated by the final evaluation test.

The initial goal in the research phase was to understand the context, problems of PRM and causes and users. Literature research was conducted combined with interviews with experts to understand the Dutch railway maintenance planning. By analysing the qualitative and quantitative data collected from interviews and user testing of PRM, a list of problem statements, design goal and requirements were defined. In the design phase, a series of design activities with users(e.g co-creation session, prototype tests) were conducted to generate ideas and iterate the concept by prototype tests with users. By involving users in every stage of the process, I got instant feedback and had a deeper understanding of the users’ needs and quickly verify the hypothesis and iterate concept.

The final concept called Macomi Maintenance consisting of four main functional pages: Homepage, Input, Analysis and Result. It covered the main operations needed to optimise the planning, which achieved an excellent usability performance evaluated by 8 participants in the online evaluation tests. It was found that showing information in an organised way(in this case I used cards and tabs) and provide enough guidance helped to reduce the time and fear of learning new software. All participants could finish the assigned tasks without hints in the evaluation test and show more willingness and confidence to learn Macomi Maintenance.

With 2,975 safety violations in the US alone, the lockout safety routine, one of the most important safety methods in the industry, remains unsafe. This is caused by the limited adherence of companies employees to the preset protocols. Heavy industries primarily focus on the efficiency of their processes and recognise the rising potential of smart product solutions to serve their key safety as efficiency interests. This project aims to meet the demands of the industry by the design a smart lockout use case that enhances the lockout process in terms of safety and efficiency, and that can be adopted by the heavy industry. For the company of TWTG this thesis researches the potential of this product and establishes a digital lockout use case and smart concept design to evaluate the value delivered to the industry. Through an empirical research study knowledge is gathered on the unknown user behaviour in the lockout process and corresponding lockout materials handlings and methods. This qualitative research study uses protocols reviews, user observations and field studies to provide real-life insight on the manifestation of behavioural routines for a leading industry. Consequently, expertise on lockout routines and smart product innovations in the industry is gathered through consultations with ten industry experts to gather verifiable evidence on unsafety and the potential of smart product solutions in the lockout process. This research concludes safety in the lockout process is highly dependent on the correct interpretations of the user. A false perception of safety is easily established when activities are not correctly executed. Positively, smart product solutions provide severe potential for the industry to support correct behaviour of operators and identify the life-threatening violations of the lockout procedure. Moreover, interviews with managing and external stakeholders from the industry state a marginal impact on existing industry materials and lockout routines are demanded in order to introduce smart product solutions successfully. Through a variety of use case evaluations with both managers and operators related to the lockout process, the desired level of disruption to these materials and routines is evaluated for the industry of Royal Vopak. From these insights, a smart lockout use case is established for a sizeable market. The selected smart lockout routine provides pro-active feedback on operators activities and real-time validation of a safe work environment. The ease of implementation is supported by the investigation of compatible solutions with existing materials, low battery power solutions, the LoRa network and wireless communication technologies, allowing to meet the identified context requirements and deliver a feasible product solution. An appearance model of the smart lockout product is developed to allow the industry to emphasise with the developed concept. The safety and efficiency value of the smart lockout use case is revealed through an objective evaluation with eight respondents representing the majority of directly related employees to the lockout process from three industry locations. Consequently, consultations with the deployment and innovation leaders from the industry advocate the establishment of the smart lockout routine. With this study, the company of TWTG desires to deliver a unique safety product for the global market.