The utilization of data in design is a crucial aspect of shaping the product and service development. Despite the lack of extensive research on this subject, this study aims to bridge the gap by introducing the ‘D³IKIT’, a data-driven design process and toolkit. Through workshops, this process and toolkit offer a practical method for creating innovative product and service concepts using data and machine learning. Developed and tested with the participation of 42 individuals, the ‘D³IKIT’ provides valuable insights for both practitioners and academics.

Cyber-Physical-Systems provide extensive data gathering opportunities along the lifecycle, enabling data-driven design to improve the design process. However, its implementation faces challenges, particularly in the initial data capturing stage. To identify those, a comprehensive approach combining a systematic literature review and an industry survey was applied. Four groups of interrelated challenges were identified as most relevant to practitioners: data selection, data availability in systems, knowledge about data science processes and tools, and guiding users in targeted data capturing.

This paper presents a collaborative solution developed to enable people without prior Internet of Things (IoT) knowledge to ideate, conceptualise, role-play and prototype potential improvements to their work processes and environments. The solution, called the Karakuri IoT toolkit and method, was tested in two workshops with eight production leaders at a Swedish manufacturing company. Outcomes were analysed from the perspectives of materials interaction and instruments of inquiry. Results indicate the solution can help people conceive and prototype improvement ideas at early design stages.

This study proposes a diary method enabled with IoT sensors for user research in design. It addresses the limitations of diary methods by incorporating sensor data to trigger user self-reports. The focus is on how sensor data influences self-reports and designers' perceptions. Results show that sensor-enabled diaries offer more diverse content and overview of users’ lives and designers perceived the proposed method potentials, suggesting significant potential for IoT in user research.

This study aims at developing a new user research method that uses IoT sensors embedded at users' homes to enable users to recall their memories. The proposed method was evaluated by experiments where four participants individually created user journey maps with quantity data that was collected for seven days. The results showed that IoT sensor data increased the quantity, clarity, and accuracy of recalled memories. This study argues that IoT sensors can be an effective approach to increasing user research quality by triggering users' memories without interfering with users' ordinary lives.

This paper investigates which activities and success factors can be identified for the data-driven validation of functional requirements. For this purpose, a case study is conducted at a machine tool manufacturer. To validate functional requirements by analyzing data of reference products, these activities must be performed iteratively: basic work, interdisciplinary work, programming and check results. For the successful execution of data-driven validation, the success factors: data origin, acceptance, data quality, knowledge about data and combination of domain knowledge must be considered.

This contribution introduces an approach for data-driven optimization of products and their product generations through a Closed-Loop Engineering approach resulting from the German research project DizRuPt. The approach focuses on data-driven product planning by ensuring data consistency and traceability between product planning, product development, and product operation by combining aspects and functions from Product Lifecycle Management (PLM) and the Internet of Things (IoT). The presented approach is illustrated and validated by pilot applications from the research project.

Industry 4.0 integrated with robotic and digital fabrication technologies have attracted the attention of manufacturing researchers. Autonomous assembly with supervisory control and data acquisition (SCADA) systems holds the promise of greater scalability, adaptability, and potentially evolved design possibilities helping to maintain efficiency, process data for smarter decisions, and communicate system issues to help mitigate downtime. This paper concerns with developing an intelligent control system based on SCADA in the Internet of Things (IoT) platform to process configuration and reconfiguration of an autonomous assembly system. The implementation study certifies the effectiveness of the proposed IoT-based SCADA control system in autonomous assembly.

Novel IoT market solutions and research promise IoT modules that do not require programming or electrical setup, yet shop floor personnel need to face problem solving activities to create technical solutions. This paper introduces the Karakuri card deck and presents a case study composed of four workshop sessions in four manufacturing settings, where shop floor personnel tested the cards as a means of ideating and presenting conceptual IoT solutions in the form of diagrams. The results indicate the validity of the proposed conceptual solutions and suggest prototyping as a next step.

The terms IoT and Industry 4.0 are promising increasingly sophisticated solutions, but the realisation will depend on the inclusion of robust and reliable sensors. If the gathered data is flawed or inaccurate the performance of the whole system will be compromised. By reviewing research on robustness indicators, mechatronics and sensor properties as well as listing mechanical noise factors and providing an electromechanical trade-off example, the paper highlights the importance of considering both mechanical and electrical noise factors and robustness in early development of connected devices.

With the introduction of ‘5G’ data transfer gets faster and further reaching than ever before. This new communication technology paves the way for an exchange of skills and competencies between humans and machines. This raises the question of how future users can profit and understand the potential brought about by these technologies. This paper elaborates the use of demonstrators in a pilot study as research tools and assesses their potential. It gives first insights why demonstrators are suitable to set a basis for public recognition for body-worn CPS and how to promote innovative visions.

Radio-frequency identification (RFID) technology is a consolidated example of wireless power transfer system in which passive electromagnetic labels called tags are able to harvest electromagnetic energy from the reader antennas, power-up their internal circuitry and provide the automatic identification of objects. Being fully passive, the performance of RFID tags is strongly dependent on the context, so that the selection of the most suitable tag for the specific application becomes a key point. In this work, a cost-effective but accurate system for the over-the-air electromagnetic characterization of assembled UHF RFID tags is firstly presented and then validated through comparison with a consolidated and diffused measurement systems. Moreover, challenging use-cases demonstrating the usefulness of the proposed systems in analyzing the electromagnetic performance of label-type tags also when applied on different material or embedded into concrete structures have been carried out.