University competence centres (UCCs) are created to enhance university-industry collaboration and knowledge sharing among collaborating partners. This study investigates the organisation of knowledge sharing among firms in UCCs through a qualitative case study of UCCs with or without a focus on research in their activities. Data collection was done through interviews and observations over a period of 24 months. While the findings indicate that both types of UCCs are non-neutral, they also reveal several different characteristics that appear primarily based on a strong tie either to the first (education) or the second (research) mission of academia. Although both types of UCCs act to build a common meaning among participating organisations, the focus on the first or the second mission leads to this meaning is primarily being constructed in the firm-to-firm or university-to-firm interfaces, respectively. Whereas cross-industry knowledge sharing is emphasised by both types of centres, it is thus more strongly emphasised by UCCs without a focus on research as it helps to avoid harmful effects of knowledge spillovers. The focus on the first mission also appears able to sustain the organisation of knowledge ecosystems created by UCCs without a focus on research in a prefigurative form, which is otherwise typically transient. Furthermore, the challenges to sustainability are different, with centres focused on research being pre-occupied with funding issues, while centres not focused on research leveraging on others means to maintain the interest of industry. The findings contribute to innovation management research and practice by refining current understanding of processes and practices of university-industry collaboration, and how they contribute to facilitate (cross-industry) collaboration and knowledge transfer. Given that university-industry collaboration is often promoted in national innovation policies to create value for society as whole, our findings contribute towards enabling organisations, managers as well as governments to take more informed actions when engaging in such collaborations.

A viable option to reduce global warming related to internal combustion engines is to use renewable fuels, for example methanol. However, the risk of knocking combustion limits the achievable efficiency of SI engines. Hence, most high load operation is run at sub-optimal conditions to suppress knock. Normally the fuel is a limiting factor, however when running on high octane fuels such as methanol, other factors also become important. For example, oil droplets entering the combustion chamber have the possibility to locally impact both temperature and chemical composition. This may create spots with reduced octane number, hence making the engine more prone to knock. Previous research has confirmed a connection between oil droplets in the combustion chamber and knock. Furthermore, previous research has confirmed a connection between oil droplets in the combustion chamber and exhaust particle emissions. However, the co-variation between oil originating particle emissions and knock has not been investigated. The current study examines the connection between knock and particle number in the exhaust, when running on fuel with low soot production. A single cylinder spark ignited heavy-duty engine was used. It was equipped with port fuel injection and fueled with methanol, which produces very little soot at lambda 1. Consequently, the measured exhaust particle numbers were assumed to origin essentially from engine oil. Three grades of oil, in combination with three piston ring configurations, were used to vary the amount of oil entering the combustion chamber. Results from knock limited operation at both medium and high engine load showed that an increased number of particles in the exhaust was associated with an increased likelihood of knock. The authors find the hypothesis that an increase in particle number correlates with an increase in auto-ignition tendency to be confirmed.

The present study uses a pin-on-disc tribometer to evaluate friction, wear, and airborne particle emissions for a rail-wheel contact. Test pins from UIC60 900A rail carbon steels were in contact with three types of test discs surfaces: R7 wheel carbon steel, laser cladding overlayed martensitic stainless steel, and laser cladding overlayed Ni-based-8% MnS self-lubricating alloy. Test results show about halving of the coefficient of friction, 0.42 to 0.22, and one ten-power lower specific pin and disc wear of discs with self-lubricating overlay compared to standard railway carbon steel contacts. Using stainless-steel overlayed discs also resulted in one ten-power lower specific disc wear, but pin wear is unchanged. Particle emission for the tests with discs with self-lubricating overlay is constant at almost 200 particles/cm3 while running in the distance is needed for the other tests. Almost all generated airborne wear particles were in the sub-100 nm range. The use of laser-cladded (LC) overlay reduced the number of airborne wear particles in the sub-100 nm range by more than a factor of 10.

During the last decade, self-driving vehicles have become a major topic of interest, promising to transform transport by making travel safer and more efficient. However, as we move closer to making these vehicles a reality, it has become clear that introducing them into society might not be as straightforward as once thought, and there are growing doubts about the benefits they are supposed to offer.

In this thesis, I investigate the societal impacts of self-driving vehicles by exploring four aspects: reasons for researching self-driving vehicles, how these vehicles could be implemented, the societal impacts of fully implementing self-driving vehicles, and their relationship to sustainability goals.

I find that the motivation for researching this topic is often opaque, and the existence of the technology itself is used as a justification for more research. 

Furthermore, most research into realising self-driving vehicles focuses on purely technical aspects such as designing better algorithms. However, I show that many challenges remain connected to the sociotechnical intertwinement of self-driving vehicles. For instance, I illustrate how they will interact with pedestrians and how services using self-driving vehicles would be practically organised.

Additionally, self-driving vehicles are likely to impact many aspects of society, such as congestion, accessibility, and economic factors. However, I demonstrate that no single framework successfully captures all the identified societal impacts, which are likely to depend on diverse factors such as geographical variations.

The impacts further affect sustainability, where new challenges are likely to emerge. I show that while current tools to govern the transport system are still relevant, a comprehensive approach is needed to ensure that policymakers make well-considered decisions. 

In conclusion, I call for a more balanced view of self-driving vehicles. Introducing this new technology requires careful planning and governance to ensure that self-driving vehicle systems genuinely enhance our quality of life and help build a sustainable future. 

The design and analysis of large casted parts present significant challenges due to their complex geometry. Finite Element (FE) modeling is a vital tool for understanding the performance of casted components. However, the computational requirements associated with these parts often lead to excessive processing times and resource utilization. This thesis aims to enhance the efficiency of the mid-surface model creation by developing an FE modeling approach suited explicitly for large casted components. The study begins by exploring the background of casted parts and their applications. A comprehensive analysis of modeling and meshing techniques is conducted, emphasizing their application to large casted components. Building upon this knowledge, different ideas are examined, leading to the proposal of a methodology combining CAD strategies for design features, hybrid meshing techniques, and approaches aimed at reducing FE modeling time to streamline the overall process.To validate the proposed approach, a series of case studies involving casted parts with varying levels of complexity are undertaken. Real-world casting process parameters are considered, highlighting the advantages and limitations in each ideation phase. The proposed methodology is tested and show cased to expert engineers to evaluate its efficiency and feasibility. Furthermore, the efficiency of the new approach is quantitatively evaluated in terms of processing time. The developed methodology offers engineers and researchers a powerful tool to accelerate the design process and optimize FE modeling time while managing computational costs. As industries continue to push the boundaries of size and complexity in casted part design, the insights and techniques presented in this thesis offer a valuable resource for addressing the various engineering challenges inherent in future endeavors.

The focus on sustainability has impacted all products and product development, Hiab is also attempting to do this by switching to electric power instead of the conventional engine-powered operation for its products. For this conversion a separate design is required to house the needful batteries, this thesis aims to create a solution for this requirement. The thesis presents a battery box and mounting structure that is safe, light and durable. Research was also conducted on the standards available for battery housing and all the factors affecting them. An iterative design process was undertaken generating multiple design concepts that were evaluated and refined through Finite Element Analysis simulations. Vibration, Dynamic Shock and Drop test analysis are carried out to replicate the tests mentioned in the standards. The final result is an optimized design which is 20 percent lighter than the original structure and is easier to manufacture.

Wave energy is a huge power source that can make a significant contribution to the production of renewable energy in the future. It can generate as much as 10% of the world´s present energy consumption [1]. However, Wave Energy Converters (WECs) is a relatively new field, which requires new technology development, and testing before efficient WECs can give any significant contribution to the energy production. The main difficulties lie in the harsh marine environment and the fact that wave power is delivered with high forces and low speeds. The high forces necessitates strong and durable mechanical structures and the slow speed makes efficient energy conversion challenging. Further, there is a very large variation in wave height over time, and during storms, the largest waves can be 10-25 times higher than the average wave height at the site. The maximum forces and motions can thereby be tremendous if not handled properly, and makes the development of efficient Wave Energy Converters (WEC) challenging. The dimensioning forces strongly depend on the wave power concept, the WEC implementation and the actual Power Take-Off (PTO) system. Of the many different types of WECs being researched and developed, this paper focuses on the development of a winch based point absorber wave energy converters (WBPA-WECs). This paper presents the development of a solution for a flexible chain where an elastomeric bearing is used as a means to achieve the relative motion between the links in a chain. With this solution no sliding is present and the motion is achieved as a deformation in the elastomeric bearing. A design process is formulated for determining a suitable configuration of layers of steel shims and elastomers. A test rig for bearing tests has been developed and results from these experimental tests in combination with material tests and FE analysis are presented in the paper. These are presented in the context of illustrating the proposed design process for designing these type of laminated elastomer bearings. The different steps in this design process have been illustrated for the defined test bearing and we can conclude that our findings indicate that the proposed process can be an important support method for further development of this approach with elastomer bearings.

This article presents a novel emotionally expressive robot platform targeting social engagement with children. This platform was implemented in accordance with UNICEF's policy guidance on artificial intelligence (AI) for children, focusing on factors such as safety, transparency, reliability and explainability. The robot prototype is presented from a design and development perspective, outlining all utilized electromechanical components that enable its 11 degrees-of-freedom and sensing functions. Preliminary evaluation results are provided in terms of dependability and expressiveness of basic emotions, thus demonstrating the robot's potential to facilitate trustworthy and secure interactions with children.

Research on digital transformation focuses on business models and technological innovation but it often lacks a detailed exploration of how firms develop, execute, and evaluate related and unrelated digital diversification strategies. To address this gap, this study employs a multiple case study approach to uncover the varied processes and outcomes of implementing digital diversification programs in established firms. The findings reveal that established firms frequently refine and adjust their digital diversification strategies to achieve desired results. Specifically, related digital diversification strategies benefit from well-defined market segments, clear technological focus, and robust senior management support. In contrast, unrelated digital diversification strategies thrive through extensive exploration and experimentation with novel digital technologies and markets, reduced senior managerial intervention and increased middle- and lower-level management involvement. Semi-related digital diversification strategies, which incorporate elements of both related and unrelated approaches, often encounter tensions owing to conflicting traditional and new program execution methods, posing significant realization challenges. Key factors identified as instrumental in the success of digital diversification strategies include technology, markets, management & organization, and program execution. The study concludes by discussing the managerial and academic implications and offers recommendations for future research in this domain.

This paper focuses on the application of soft robotics in the area of social interaction, and presents a modular approach on the design of a soft robotic neck for integration with the social robot HARU. The proposed design incorporates soft robotics and additive manufacturing principles, enhancing safety through compliance for absorbing contacts with users or objects, while modularity allows for easy replacement or upgrade to meet HARU's specific application requirements. The paper discusses the conceptual design specifics of the soft robotic neck and provides an overview of the prototype development stages and its main functionalities.

Despite the evident upsurge of e-commerce (EC) over the past decades, the peak of online demand caused by the COVID-19 pandemic, and the huge involvement of micro and small enterprises (MSEs) in the online businesses to survive, the extant literature has neglected to analyse how MSEs orchestrate their resources between internal and external investments. Past studies, also in the case of SMEs, have tended to adopt a more firm-centric perspective focusing on the organisational conditions that determine firms’ performance after the usage of EC, failing to explore the inter-organisational relations between MSEs and other actors in their ecosystem. Indeed, as MSEs may suffer from liability of smallness and lack of resources, they may rely more than other actors on the nexus of relations that emerge within the digital ecosystem generated through the usage of EC platforms. By relying on 37 interviews with owners or managers of MSEs operating in the food and beverage industry, we investigate the dynamics of resource distribution between MSEs and the other actors in the EC ecosystem. We identified the changes in interdependencies, the information asymmetries, and the power imbalances related to the interplay between MSEs and other actors within the EC ecosystem.

An economic system built upon the sale of tangible goods produced using finite resources is inherently unsustainable. The idea of a Circular Economy (CE) as a viable pathway to sustainability has gained considerable attention from academia, policymakers, and the business community. The CE builds on a new logic in the business environment in which industrial firms operate that requires substantial changes. We face a significant knowledge gap concerning how firms internally manage the implementation and adoption of CE. Filling in this knowledge gap is critical to understanding how to implement CE at large and established firms with a considerable history of a linear logic, which are known to favor incremental improvements to existing business opportunities over radical innovation.

This thesis aims to delve into the managerial challenges that large, established industrial firms encounter when implementing CE principles, and how they address these challenges, particularly through managerial controls. Additionally, it aims to provide insights into how management can facilitate radical circular innovation and support the circular transformation of incumbent firms. To accomplish this aim, existing knowledge on barriers to CE has been synthesized through a systematic literature mapping and a systematic literature review. Next, interviews (n=68) at five large and established industrial firms provide empirical insights concerning the implementation and adoption of CE principles. In addition to the four appended papers, this comprehensive summary theorizes about the empirical findings using literature on radical innovation, sensemaking, and managerial controls. 

Building on the empirical papers, this analysis sheds light on two distinct patterns in how managers frame CE: incremental framing versus radical framing. It is argued that this has considerable consequences concerning with respect to ambitions, operationalization, and the means used to achieve a CE. In addition, the thesis theorizes about the relationship between the management control systems and the prevailing framings of CE. Based on an understanding of this relationship and the tensions and conflicts associated with the different framings, it is argued that managerial controls can act both as barriers to and enablers of CE adoption at incumbent firms. In addition to the practical and theoretical implications of this finding, the thesis pinpoints limitations and assumptions concerning managerial control systems in relation to CE and propose new avenues in light of this. 

Finally, the analysis is synthesized into an integrative framework that differentiates three different modes of organizational behaviors within the context of CE transitions: optimizing, transforming, and systems building. This framework integrates the theoretical foundations of the thesis, acknowledges the identified issues, and offers actionable implications for researchers and practitioners.

For industrial incumbents seeking business opportunities in line with sustainable development needs, the concept of Circular Economy (CE) has gained significant traction. However, getting from a strategic ambition toward actions and innovations entails many challenges for organizations. In particular, one frequently overlooked issue relates to the use of management controls in relation to the CE strategy. Using data collected through a participatory action research collaboration spanning five years, this paper aims to give a detailed and empirically based description and analysis of how a frontrunner company has approached innovation goals and measurements in light of its CE strategy deployment. By analyzing the development in the case organization, key purposes behind CE metrics are discussed and analyzed together with challenges expressed by interviewees. In particular, our findings advocate the need for experimentation, ideation, and learning, rather than highly specific and restricting control measures.

While several existing firms have begun making changes to meet a circular economy transition, it is clear that they meet with several managerial challenges. Management control systems can help managers make the radical changes and facilitate the innovation processes that is required to meet circular economy. However, little is known about how management controls are applied in the context of a circular economy transformation, and whether traditional management controls are compatible with a circular logic. This paper aims to provide detailed and empirically based insight on these issues.

This study examined three large industrial incumbent firms to see how they utilize action-, result-, and cultural controls to implement circular economy principles, and what tensions they have experienced. We used semi-structured interviews (n=38) to collect data, and thematic analysis for the analysis.

The analysis suggests that while circular economy principles are not integrated in all parts of the management control system, there are still several factors that can both enable and impede a circular transformation. Furthermore, imbalances and inconsistencies were found concerning different types of managerial controls used. Alarmingly, circular economy initiatives are at risk of being reduced to minor incremental improvements if the radical changes needed are not better understood, and changes made to the management control system to facilitate these.

This research provides rich qualitative insights bridging the new phenomenon of circular economy adoption in incumbent firms with research on innovation management and management controls.  

Traditionellt sett är en linjär produktutvecklingsprocess det självklara valet, däremot med den teknikutveckling som skett och fortsätter att utvecklas i samhället arbetar många företag mot ett mer agilt arbetssätt. Val av produktutvecklingsprocess har en direkt påverkan på organisationens innovationsförmåga. Valet är mycket viktigt vid projekt vars mål är att ta fram något nytt som uppfyller kundens behov eller önskemål, samt för företag som vill hålla sig konkurrenskraftiga på marknaden. Syftet med detta kandidatexamensarbete är att undersöka hur företag använder sig av olika produktutvecklingsprocesser samt om en kombination av agila och linjära processer är gynnsam. Arbetet undersöker studiens frågeställningar som tar upp hur och när agila samt linjära processeranvänds. När och hur kombineras de två processerna och bakgrunden till en eventuell kombination utav dessa. Undersöka när är den ena, den andra eller kombinationen av båda processerna är mest fördelaktigt. Samt vilka för- och nackdelar processerna har, även vilken korrelation processerna har när det kommer till främjande av innovationsgrad. Arbetet inleddes med en litteraturstudie inom de olika områdena; innovation, linjära processer, agila processer samt en möjlig kombination av dessa. Efter litteraturstudien genomfördes en empirisk studie av två företag med tre respondenter från vardera. Detta gjordes i form av semistrukturerade intervjuer. Respondenterna hade olika roller på företagen, men samtliga innefattande arbetsuppgifter berörde produktutvecklingsprocesser. Resultatet från intervjuerna har sedan analyserats och diskuterats och presenterats i en slutsats. Från den genomförda studien kan konklusionen dras att de undersökta företagen till den större delen av projekt använder sig av egna processer som i grunden är likt den traditionella Stage-Gateprocessen, men med en mer flexibel process liknande agilt vid uppstarten av projekt. En kombination av Stage-Gate och Design thinking är vanligt förekommande och kombinationen krävs för att matcha kraven på flexibilitet som ställs på företag som verkar på en ständigt föränderlig marknad. Till största utsträckning implementeras dock dessa processer separat och oftast används Design thinking som ett komplement till deras redan befintliga linjära process.

Systems of Systems (SoSs) integrate many critical systems our society relies on. In designing individual systems, stakeholders use bespoke protocols, custom information models, and proprietary components with limited computational resources from various vendors. We present a reference architecture that allows multiple stakeholders to carry out a flexible integration without giving up control to a single entity in the presence of the aforementioned limitations. Our architecture relies on rule engines and graph data model to integrated systems flexibly even when black-box components are used. At the same time, a federation of the rule engines allows each stakeholder to retain control over the rules that reflect their policies. We also rely on a common information model based on ontologies to account for the information model mismatch and reduce the duplication of integration efforts. Moving rule execution to the standalone rule engines allows deployment in resource-constrained and proprietary environments. A uniform application programming interface (API) is used to integrate rule engines across systems as well as components within each system with a respective rule engine. We also present a novel algorithm to determine dependencies across rules deployed in different rule engines within the federation. This allows domain experts to develop rules as usual without having to deal with the distributed aspect of the system. We also present a proof of the sufficient condition to ensure all necessary notifications will be sent to ensure correct rule activation across different rule engines. Compared to other systems involving distributed rules, the proposed architecture is well-suited for the integration of transactional workloads commonly found in enterprises. The qualitative evaluation based on the Architecture Tradeoff Analysis Method (ATAM), applied to a telecommunications use case, shows that the architecture possesses the “interoperability”, “modifiability”, and the “functional completeness” quality attributes with a trade-off around rule expressiveness. The quantitative evaluation demonstrates speedup over the single-node setup in most scenarios except in case of highly optimized rules and a poor network performance simultaneously (tr<10ms, tn=100ms).

High accuracy autonomous positioning systems are becoming increasingly important in today’s chemical industry because they can obtain precise experiment results automatically and hence allow lab technicians to focus on other tasks concurrently. One time consuming process is the process of sampling chemical test results into the correct container, especially when the tests are many and infrequent. This is where an automated sampling machine, or an autosampler, comes into play. If this sampling process is automated, the accurate sampling is achievable without the full time attendance of a lab technician. This thesis explores how to construct a small footprint autosampler in the form of a gantry, complete with electronics, actuation of all axes and relevant embedded software needed for implementation in a lab setting. This thesis also explores how to optimally control the stepper motors in charge of axis actuation, by comparing classic open loop control, PD control and an adaptive LQI controller. This is done by developing a mathematical model of the system using MATLAB Simulink, followed by developing and optimizing the controllers on the model and then implementing and verifying the controllers on the physical system. The conclusion of this thesis is that the PD controller performs best for controlling a stepper motor. It performs slightly better than open loop control and has the additional advantage of reference following. The adaptive LQI performed the worst on the model and additionally, it could not be implemented on the physical system due to how the system was constructed in hardware.

Overview: Few companies and organizations remain innovative for long periods of time, and despite high ambitions, many innovation initiatives fail to yield the desired results. Identifying how best to measure the effectiveness of innovation initiatives is key to ensuring that those efforts actually help an organization achieve its overall goals. This article offers organizations and their leaders practical advice for measuring innovation effectively. Specifically, it defines innovation measurement and its importance in precise terms and summarizes six years of our research on innovation measurement in multiple firms and industries. We articulate nine critical lessons for improving innovation measurement in real-world practice clustered into three overarching themes: Strategy, Organization, and Measurement Design. Each of the nine lessons elucidates a problem, identifies potential consequences, and proposes concrete solutions that organizations can implement as they strive to better measure and, ultimately, improve their innovation management initiatives.

Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. This thesis project is carried out at Wrlds AB, Stockholm. At Wrlds, all machine learning is run in the cloud, but they have been attempting to run their AI algorithms on their embedded devices. The main task of this project was to investigate alternative network structures to minimize the size of the networks to be used on human activity data. This thesis investigates the use of Fast GRNN, a deep learning algorithm developed by Microsoft researchers, to classify human activity on resource-constrained devices. The FastGRNN algorithm was compared to state-of-the-art RNNs, LSTM, GRU, and Simple RNN in terms of accuracy, classification time, memory usage, and energy consumption. This research is limited to implementing the FastRNN algorithm on Nordic SoCs using their SDK and TensorFlow Lite Micro. The result of this thesis shows that the proposed network has similar performance as LSTM networks in terms of accuracy while being both considerably smaller and faster, making it a promising solution for human activity recognition on embedded devices with limited computational resources and merits further investigation.

Creativity and Innovation Management has grown substantially over the last couple of years, both quantitatively and qualitatively. From 2016 to 2021, the number of submissions has grown from 287 to 395. Most of the growth was realized in Asia: The number of submissions from that continent increased from 72 in 2016 to 193 in 2021. The rest of the world remained (close to) stable: 215 in 2016 and 203 in 2021. Equally important, the Thomson ISI Impact Factor increased from 1.423 in 2015 to 3.051 in 2021 and further to 3.644 in 2022. This is not where our ambitions end, though. We want to be the ever-better outlet for authors researching, and practitioners working in, the fields we cover. Editing a journal with the ambition to continuously increase its quality while dealing with a substantial growth requires teamwork—teamwork among the editors and the editorial office, teamwork between the editors and their reviewers and, as surprising as this may sound, teamwork between the authors and their reviewers in a top-quality reviewing process. The purpose of this piece is to present and discuss some reviewing standards. In particular, we aim to share with our reviewers what we think is an excellent reviewing process. Furthermore, we formulate our ideas about what it is that makes a review an excellent one. The title of this piece is deliberately ambiguous. It denotes that Creativity and Innovation Management strives for reviewing excellence—as in an excellent reviewing process. It also denotes that we reach for the stars and hope to one day receive and, hence, review only excellent submissions.

The expedited rise in the emission of Greenhouse Gases in the automotive industry is countered by the advancement in electric vehicle (EV) technology. Consequently, internal combustion (IC) engines are being replaced by electric motors throughout every technical field. 40% of the failures among those motors are due to bearing failure. Modern advancement in inverter technology escalates the chance of electric failure making bearings even more vulnerable. Among the mitigation strategies against electric failure of bearing, hybrid bearing and lubricating grease characteristics optimization are the most prominent ones. However, the energy efficiency and grease performance of hybrid bearings, are still lacking comprehensive research support. A methodology or a test machine to optimize the electrical characteristics of grease remains an obstacle to overcome. The thesis intends to address both problems by addressing them with equal significance. Bearing current phenomena are studied and broken down to derive a methodology to examine and compare the electric characteristics of greases. Besides, a design for a new test machine that can test bearings and grease under electric voltage is developed. Simultaneously, hybrid bearings are tested for long-term operation with lithium, polypropylene and polyurea thickeners. The results are compared against each other and with steel bearings. The results indicate that the hybrid bearings are more energy-efficient than steel bearings. Polypropylene-based grease was better in terms of energy consumption closely followed by lithium complex grease.

This study investigated the implementation of a remaining range estimation algorithm for electrical vehicles, an essential feature to define a vehicle's reliability on the road. The implementation was made on an electrical motorcycle, comparing three models: a dynamic force based model, a power based model and a mass estimation model. The mass model estimated the mass with the help of a RLS algorithm and is a combination of the force based model and the power model. It investigates the possibility to further increase the accuracy of a range estimation algorithm by estimating the total mass of the vehicle over a driving session. On top of these models, two kinds of prediction methods for future consumption were evaluated: the average-past prediction and the home-intention prediction. Both models uses past data to predict the future, but the home-intention prediction is a suggested method to further improve the classic average-past method, where the beginning and end of the vehicle's driving sessions is assumed to be the same location. Tests were executed for the models on an electrical motorcycle provided by the company CAKE. A test equipment were put on the motorcycle, consisting of microprocessors and sensors, used for computation and collection of data. With this equipment, experiments were performed on three test routes with different conditions, comparing the models’ accuracies. The results showed that the Power Model, even with its lower complexity performed best overall, while the Force Model showed mixed results. Depending on the prediction method the Force Model performed either at the top or at the bottom. When the results were analyzed, this behavior seem to be the result of insufficient/faulty hardware which were essential for the average-past prediction to achieve proper results. The Force Model using home-intention prediction consistently performed better, as long as its prediction was correct. The Mass Model was executed offline and were then used to simulate the effect it could have had online. This showed promising result, suggesting improved accuracy if implemented online, but which in this thesis is left as a suggestion of improvement for future work.

The concept of Digital Twins has attracted more and more attention from both the academia and the industry in the recent years, much thanks to the possibility of bidirectional communication between physical objects and their digital replicas. However, despite its growing prominence, the existing literature on Digital Twins remains limited. This is especially true for literature on guidelines and frameworks for constructing digital models for use in Digital Twins. This thesis examines the kinematics underlying such digital models, aiming to create an optimized kinematic solution for the pick-and-place robot Codian Delta D4. More specifically, the report presents a comparative case study to investigate how two different digital models, characterized by varying levels of kinematic detail, impact the performance of the Delta D4 robot in terms of accuracy and computational efficiency. The results reveal that the inclusion of additional details did not significantly impact computational efficiency. However, it was observed that the added details introduced minor deviations in accuracy. A continued assessment is therefore necessary to decide which deviations are acceptable for the model’s intended purpose and whether the resources required for the extra development are justified. The authors suggests that the more detailed model, excluding the spring components, is a promising foundation for a future implementation of a Digital Twin of the Delta D4 robot.

This report examines the evolving landscape of energy stations in the context of the growing electric vehicle (EV) market and the strategic implications for innovation management within Company X. Amidst the rapid technological advancements and shifting consumer behaviors towards sustainable transportation, the research focuses on defining the requirements of today's and tomorrow's EV drivers and integrating these insights into actionable strategies for Company X. The thesis employed a mixed-methods approach, combining quantitative surveys with qualitative observation visits as well as qualitative interviews internally at Company X. This method allowed the research to delve deeply into user needs, preferences, and the operational challenges faced by Company X as it navigates the transition to sustainable energy solutions. Our findings highlight the critical role of product development initiatives and the importance of strategic innovation management in fostering a responsive and adaptive approach for Company X. The report provides recommendations for enhancing product development and innovation management practices to better align with the fast-evolving market demands and regulatory landscapes. The insights and strategies outlined in this report are intended to guide Company X and similar companies through the complexities of the EV market, supporting sustainable business growth and the broader transition towards a fossil-free society.

Reducing the environmental impact of machinery relies on all machinery components operating more efficiently. Rolling element bearings are an indispensable part of all modern machinery, enabling and facilitating machine operation. Greases, an often overlooked machine component, are an essential part of rolling bearings and have the greatest scope for improving the bearing efficiency. Thus, studying the mechanisms of friction generation and energy loss originating from the grease and all of its components in a grease-lubricated bearing is fundamental for further improving their efficiency.  This is a challenging task since only fully formulated commercial greases are often available, making it difficult to study in isolation the contribution of each individual component to the friction process. The complexity of studying grease lubrication increases further due to the intricacy of measuring friction within the bearing. Robust methodologies and standards for measuring grease efficiency within a rolling element bearing are scarce and must be developed.

This doctoral thesis investigated the effect of different grease components, such as different grease thickeners and a non-halogenated ionic liquid grease additive, on the frictional performance of rolling bearings operating under conditions typical of those encountered in electric motors. This required that a new and robust experimental set-up was designed with the purpose of continuously measuring friction torques from a rolling element for prolonged periods.  An evaluation of the role of each of the grease components in the process of friction generation thus became possible. First, the effect of the running-in procedure on the grease ageing was studied. Imposing an increasing speed profile appeared to induce a mild ageing on the greases. In the second and third studies, the effect of different thickeners on the lubrication performance during the bleeding phase was studied under steady-state conditions. Compared to lithium-complex grease, polypropylene grease reduced the energy consumption of the grease-lubricated bearing. A modified polypropylene grease, with recycled polypropylene in the thickener, was also tested. The experiments with the recycled polypropylene grease finished successfully with no traces of bearing damage and friction torque values lying between the lithium complex and polypropylene greases. This represented a milestone in the development of greases with recycled materials. In a fourth study, the effects of three different grease thickeners (lithium complex, polyurea (diurea) and polypropylene) were evaluated on lubrication performance and energy-saving potential during prolonged conditions of transient and variable speeds, typical for electric motors of battery electric vehicles. From the analysis of the resulting friction torques, it was concluded that the thickener influences the friction torque through the process of dynamic bleeding and that friction torques under both steady-state and transient speed conditions were predominantly controlled by rolling friction.  In the fifth study,  the addition of a non-halogenated ionic liquid to a LiX grease resulted in a drastic 45% reduction of energy dissipation. The feasibility and potential of using this novel grease under e-motor conditions were discussed. Finally, the overall environmental footprint (kg CO2-eq) of a grease-lubricated bearing system was estimated (production of grease and bearing together with energy consumption over a typical service life). Reducing friction torques and their corresponding energy losses through a better design of individual grease formulations appears to ensure that the greatest impact on CO2-eq released can be obtained.

The churning phase of a grease-lubricated rolling bearing significantly impacts the ageing of the grease, affecting both bearing performance and service life. The knowledge about the influence of the running-in procedure on grease ageing is limited. In this paper, we studied grease ageing in a ball-bearing running-in process with two additive-free greases made with the same base oil but different thickeners: lithium-complex and polyurea. Rheological characterization of the used greases was performed after two different 48-hour running-in speed profiles. Both procedures employed a step-wise running-in process, either increasing or decreasing speed, while maintaining the same total duration and using the same speeds. The results reveal that grease ageing in the bulk and near the raceway varies significantly depending on the speed profile used and the level of ageing induced by the speed profiles is thickener-dependent. The PU grease exhibits more severe ageing when subjected to a running-in profile with sudden high speeds (decreasing speed profile). Conversely, the LiX grease is more susceptible to ageing during a running-in profile with increasing speeds. The implications of the applicability of these speed profiles in industrial and research applications are also discussed. 

Due to their advanced tribological and electric properties, ionic liquids (ILs) are seen as potential lubricant additives in emerging green technologies. To verify their potential in complex machinery, an evaluation of tribological performance at the component and machine level is necessary. This work presents the effect of using a non-halogenated ionic liquid as a grease additive in bearings operating under driving cycle conditions. These harsh conditions are designed to be analogous to what a grease-bearing system must endure in an electric vehicle motor. One-month experiments, equivalent to 23,000 km of vehicle operation, were used to evaluate grease additive performance. Our results reveal that the addition of the ionic liquid resulted in a high-impact improvement, reducing bearing friction losses by up to 45%. Grease rheology and surface wetting measurements indicate that the sharp drop in friction torque is related to a complex balance of factors that results in a limited amount of highly effective lubricant products at the contact inlets (optimum degree of starvation).

Performance of Lithium Complex (LiX), Polyurea (PU), and Polypropylene (PP) greases in SKF6208 bearings subjected to driving cycle conditions for 28 days (equivalent to 23,000 km of electric vehicle operation) was studied by continuously measuring bearing friction torque and temperature. The energy dissipation was correlated to the differences in oil bleeding and rheology for the three greases. Evolution of the friction torque, friction torque hysteresis, and changes in grease rheology were dominated by the oil release property. The latter was determined by the thickener system and its particular response to the conditions imposed by the driving cycle. A quantitative estimate of the carbon footprint from using these greases to lubricate bearings under driving cycle conditions is also presented.

In our previous publication, we showed that grease thickened with polypropylene could be a potential contributor to electric motor efficiency by reducing the bearing energy consumption by 22% in comparison to the most common type of grease: lithium grease.  

This work studies the feasibility of using polypropylene grease, with recycled polymer material as part of its thickener, in rolling element bearings operating under conditions typical of an electric motor. The frictional performance of a bearing lubricated with the recycled polymer grease was evaluated in deep groove ball bearings operating for 385-hour experiments under a wide range of speeds (up to 10,000 rpm). Friction torque results were complemented with rheological tests of the greases before and after the tests. The recycled polypropylene grease denoted significant rheological changes after the bearing tests. Such rheological changes were reflected in the higher energy dissipation in comparison to a reference polypropylene grease. However, the grease with recycled polypropylene led to a lower energy dissipation than a reference lithium complex grease. This represents a milestone in the development of greases with recycled materials in the grease thickener and shows the potential of using this grease in a real application. 

Automated driving vehicles have shown glorious potential in the near future market due to the high safety and convenience for drivers and passengers. Image sensors' reliability attract many researchers' interests as many image sensors are used in autonomous vehicles. We propose an online image sensor fault detection method based on comparing the historical variances of normal pixels and defective pixels to detect faults. For fault pixels without uncertainty, with a detecting window of more than 30 frames, we get 100% accuracy and 100% recall on realistic continuous traffic pictures from the KITTI data set. We also explore the influence of fault pixel values' uncertainty from 0% to 25% and study different fixed thresholds and a dynamic threshold for judgments. Strict threshold, which is 0.1, has a high accuracy (99.16%) but has a low recall (34.46%) for 15% uncertainty. Loose threshold, which is 0.3, has a relatively high recall (83.78%) but mistakes too many normal pixels with 18.17% accuracy for 15% uncertainty. Our dynamic threshold balances the accuracy and recall. It gets 100% accuracy and 58.69% recall for 5% uncertainty and 78.38% accuracy and 55.39% recall for 15% uncertainty. Based on the detected damage pixel rate, we develop a health score for evaluating the image sensor system intuitively. It can also be helpful for making decision about replacing cameras.

Large battery production facilities, often referred to as Gigafactories, are a complex design task that involves a lot of working disciplines. This requires good capabilities for communication and planning to be able to integrate the building, machines, and operators in the factory. This project is made within the Factory Layout and Modelling team in Blueprint at Northvolt, which is responsible for designing and scaling up the next generation of battery Gigafactories. The purpose of this thesis is to increase knowledge and further enhance a standardized workflow for how to manage machine interfaces. The empirical findings from the study are based on a qualitative study where 16 interviews were held with people working as Factory Layout Engineers, Utility Engineers, Automation Engineers, and Design Leaders. The empirical findings confirm there is a need for having a standardized way of marking up interfaces early in the design phase to mitigate the risk of design errors to occur in later stages. Based on the empirical findings the most important interfaces are the utility interfaces, material flow interfaces, the human-machine interfaces, and the civil, structural, and architectural interfaces. It is also important to mark up the operator’s movement around the machine and the areas where repair and maintenance is needed. This creates an understanding of the machine’s effective footprint area and shows the total workspace area needed around the machine. In this project, specific design guidelines and a new drawing template have been proposed to facilitate the visualization and handling of machine interfaces. Interface management is an emerging topic for production companies. During the last decade, this area has been developed as a management discipline within some large companies. In conclusion, the usage of interface management is necessary to increase communication of system boundaries and to decrease the cost when building new factories.

There is an ongoing transition towards driverless trucks within the truck industry. However, there is limited research regarding the aftersales aspects of driverless trucks. Therefore, the purpose of this thesis project is to investigate expected challenges and current visions of the aftersales system for driverless trucks within the organization of Scania CV and Traton. The study aims to identify potential obstacles in the development of aftersales activities for driverless trucks in hub-to-hub contexts and proposes guidelines for managing the development. Hub-to-hub is defined as long-haulage transports between terminals. The thesis project covers several theoretical fields relevant to the subject, including product service systems, ambidextrous organizations, change management, visions within organizations, and handling ambiguity. The study was conducted by executing two field visits at Scania workshops to establish an understanding of the current aftersales system design, discussions with two experts within Scania CV, and two rounds of interviews with a total of 14 respondents from relevant departments at Scania CV and Traton to source empirical data on the current visions of an aftersales system for driverless trucks. The first round of interviews was mostly with upper managers and the second round with lower managers. According to the findings, there are various ambiguities and challenges regarding both technological and business-related aspects of the aftersales system design for driverless truck applications, establishing a need for collaboration between the concerned departments. There are differing visions between departments and within them. Various theories can support the collaboration process and handle ambiguity. Based on the empirical findings, a dissection of the current status quo is presented, and a discussion of how more favorable conditions for aftersales development can be induced.

Frugal innovation is a strategy for organizations that provides products with cost advantages compared with the existing solutions. Frugal innovation can be applied to both products and services across industries. We provide lessons for managers and organizations based on a scientific review of frugal innovation as an innovation strategy. Using published studies, four distinct frugal innovation strategies are introduced. Frugal innovation can be operationalized across different industrial contexts. It also interplays with other firm innovation strategies. We also identify concerns and barriers associated with frugal innovation approaches. 

A statistical, energy-based approach is employed to experimentally characterize the ability of different greases to reduce friction when a point contact is subjected to repeated reciprocal displacements of smaller magnitude than the contact diameter. This approach allows the assessment of lubricant fretting performance with respect to its ability to remain within the contact and also its boundary lubrication properties. The results indicate that composition-dependent boundary lubrication properties of greases loaded with non-halogenated ionic liquids containing bis(oxalato)borate ([BOB]) and bis(mandelato)borate ([BMB]) anions can result in no detectable wear and low friction, even under conditions of moderately high pressures and where the original contact area is never fully uncovered. This discovery paves the way for the development of anti-fretting ionic greases.

Rolling element bearings, when subjected to small oscillating movements or vibrations, run the risk of being damaged by mechanisms such as Standstill Marks and False Brinelling. Damages resulting from these phenomena can decrease bearing fatigue life and increase wear-induced friction torque. These failures do not correlate well with standard life estimation approaches. Experimental studies play a crucial role in gaining knowledge in this area. The review integrates knowledge from experiments ranging from single contacts to laboratory and full-scale bearings in wind power and aerospace applications. The generalization is achieved using a non-dimensional amplitude parameter that relates rolling element travel during an oscillation to the Hertzian contact size. The review encompasses testing methods, procedures, reporting practices, result scaling, and application-specific considerations.

This thesis investigates the efficacy of integrating prototyping methodologies and robust design principles at the initial stages of the design workflow to optimize resource utilization. This acquired knowledge is applied in the development process of an industrial parts feeding machine. The aim of this machine is to present fasteners in a defined orientation in a controlled manner after receiving them in an unordered manner. This project encompasses extensive phases of research, analysis, brainstorming and prototyping, including a classification of the different prototypes like sketches, CAD models, multibody simulations and physical prototypes. A subsequent analysis is carried out and a viable production-ready solution is proposed. Additionally, an economical analysis is performed, valuable conclusions are extracted from the process and future work is defined.

Wave energy has an immense potential to provide clean electricity with almost zero emission, among the many renewable energy resources. While it has a huge potential to cater 10% of the current electricity demand, there are many uncertainties involved in the development of a wave energy converter (WEC). This article discusses those challenges and benefits of a product development process to address them. A winch based point absorber (WBPA) concept being developed at KTH Royal Institute of Technology has been used as reference for all discussions. A systematic design approach provides an effective way to rationalize the project from start to end. The value analysis approach is quite useful in order to eliminate rudimentary functions thereby reducing the cost. The stage gate methods makes the systematic design approach interactive and provides an understanding if a concept must be eliminated or continued with at an early stage in the project. Elements of value analysis approach and stage gate methods have been implemented along side complementing the systematic design approach to outline a design process for the WBPA-WEC. An effort has been made to address the challenges faced in the development of a WBPA-WEC.

As digital tools and technologies, such as AR, VR, Digital Twin, IoT and other interactive visualization technologies are being developed, new opportunities arise to use these to optimize the efficiency of operations, not least in the area of maintenance. One industry where maintenance is of utmost importance is the railway industry, where the goal of having a punctual, reliable and cost-effective railway traffic is dependent on the availability of maintained railway vehicles. The maintenance procedures of the vehicles are performed by technicians, working in depots to fix faults and service the vehicles. However, a lack of resources, poor coordination and information handling, and complex vehicles make the work and procedures of technicians cumbersome. The purpose of this thesis project was to investigate and give recommendations on how digital tools and technologies can facilitate the maintenance of railway vehicles. To do so, a qualitative study has been performed consisting of 12 interviews with technicians and depot staff. The purpose of the study was to understand their main challenges and time-consuming activities. Moreover, the potential use of digital tools and technologies to facilitate the identified challenges has been analyzed to establish recommendations on what tools and technologies can be used and how they should be used to aid technicians. The main challenges and time-consuming activities found include finding and accessing relevant information quickly and easily, understanding the information available, and collaborating with actors for support and expertise. The digital tools and technologies recommended consist of tablets to access information quick and easy, AR to visualize instructions and create an environment for remote support, AI to quickly search and filter information to enhance troubleshooting procedures, Digital Model to visualize vehicle configuration and link and structure information, and lastly, real-time data transfer utilizing eMaintenance technologies to faster receive information about the vehicle and its faults. The results of this thesis project can give direction for future research and the development and integration of digital tools and technologies to facilitate technicians in the maintenance of railway vehicles.

A crucial requirement for firms to remain competitive is to consistently and simultaneously engage in exploratory and exploitative activities. The academic literature has broadly accepted that the development of dynamic capabilities (ie firms’ abilities to create, reconfigure and improve resources and capabilities to fit their changing environments) are vital to meeting this competitive requirement. Research has predominately addressed these dynamic capabilities from a management perspective. Little attention has been paid to the influence of the board of directors on these firm capabilities even though boards hold the fiduciary responsibility for the corporation and its long-term viability. Even less has been written on how boards ought to organise themselves and develop their dynamic board capabilities to support and govern corporate renewal and performance effectively. This paper aims to start addressing this gap by using two related aims. First, a process framework for board behaviours is proposed that ensures, and supports, a systematic way of building and developing corporate-level dynamic capabilities. Then, evidence is presented and reviewed from a survey of two board member communities which supports the idea that board capabilities are essential for a firm’s successful renewal and economic performance, and need to be improved in practice. This framework is closely aligned with well-established components identified by the management literature but differs in having the board as the unit of analysis. A crucial question and action agenda is proposed for boards eager to acquire and develop their dynamic capabilities.

This report describes a masters’ thesis in Industrial Design Engineering at the Royal Institute of Technology in Stockholm, conducted for Venhälsan at Södersjukhuset in Stockholm, in collaboration with Sös Innovation. The purpose of the project was to contribute to improving the psychosocial well-being of people living with hiv, who are monitored by the Infektionsmottagning 2 at Södersjukhuset. The project followed a service design methodology, involving stakeholders at all stages using various human-centered methods. The work began with a literature study, examining previous research on hiv and stigma. This was followed by a pre-study involving researchers, patient organizations, and staff at Venhälsan to create an understanding of the healthcare context and the psychosocial support offered by different actors today. The main study involved people living with hiv and consisted of a series of in-depth interviews, which, after a variety of analysis methods, led to insights that formed the basis for the subsequent concept generation. The concept generation involved a workshop with Venhälsan staff, brainstorming, and feedback sessions with members of the patient group, using trigger materials. The project resulted in the development of an Hiv Handbook that patients receive in connection with their hiv diagnosis. The handbook contains six different themes: About hiv, Venhälsan, Knowledge, Recognition, Disclosure, and Acceptance, and aims to address and mitigate these topics for the patient, thereby helping a patient in a crisis situation. In addition to the handbook, all ideas and insights from the project were compiled and delivered to Venhälsan for potential future work.

Stateflow models are complex software models, often used as part of industrial safety-critical software solutions designed with Matlab Simulink. Being part of safety-critical solutions, these models require the application of rigorous verification techniques for assuring their correctness. In this paper, we propose a refutation-based formal verification approach for analyzing Stateflow models against invariant properties, based on bounded model checking (BMC). The crux of our technique is: i) a representation of the state space of Stateflow models as a symbolic transition system (STS) over the symbolic configurations of the model, and ii) application of incremental BMC, to generate verification results after each unrolling of the next-state relation of the transition system. To this end, we develop a symbolic structural operational semantics (SSOS) for Stateflow, starting from an existing structural operational semantics (SOS), and show the preservation of invariant properties between the two. We define bounded invariant checking for STS over symbolic configurations as a satisfiability problem. We develop an automated procedure for generating the initial and next-state predicates of the STS, and a prototype implementation of the technique in the form of a tool utilising standard, off-the-shelf satisfiability solvers. Finally, we present preliminary performance results by applying our tool on an illustrative example and two industrial models. 

The complexity of deploying automated vehicles (AVs) has been grossly underestimated and vehicles at high levels of automated driving (SAE level 4 and above) have so far only been deployed in very limited areas. Highly automated AVs will face complex traffic, e.g., due to occlusions and unpredictable road-user behaviour, and AVs may shift the distribution of crashes. This has given rise to a renewed interest in connectivity and collaboration, with the need to monitor (emerging) behaviours and risk, and the promise to improve road traffic safety and performance by resolving the “information gap”. This motivates further investigations and research in this direction. In this paper we set out to identify barriers and important directions towards solutions for such collaborative systems, as formed by connected automated vehicles and a supporting cyber-physical infrastructure. Drawing upon a state-of-the art assessment and interactions with experts, we conclude that the current state-of-the art is fragmented, and therefore investigate key topics related to collaboration barriers and propose research questions to address them, hoping that the provided structure can also assist in guiding future research. The topics cover, (i) the socio-technical and system of systems nature of collaborative systems, (ii) the multifaceted design space and architectures with related trade-for such systems including between safety, performance and cost, and (iii) trustworthiness issues, ranging from safety and cybersecurity to privacy and ethics.

The purpose of this thesis work is to improve the perceived climate comfort in larger truck cabins since the European commission’s new stronger carbon dioxide standards have introduced an update to the EU 96/53 directive. This directive increases the dimensions and weights of heavy truck motor vehicles, extending the driver’s cabin length by 500 mm in order to increment the truck’s energy efficiency and aerodynamics. This update was seen also as an enabler to improve the truck driver’s performance, comfort and preference towards Scania. Since the cabin of the truck is to be considered the place where the driver spends the most of its time, ensuring the driver’s comfort when resting inside means to ensure the accomplishment of their labor safely. One system used to provide comfort in the cabin when resting is the climate control unit. This unit creates an inner climate controlled environment by providing warm or cool air through an installed Heating Ventilation and Air Conditioning (HVAC) system. In order to introduce a new auxiliary unit, the design thinking methodology was chosen. This allowed to ground the proposed concepts on the actual needs of the final users. Based on their input, the aforementioned concepts were analyzed and downsized in order to prototype and test the selected ones. The final concepts of a 500 mm larger cabin were tested in a climate chamber under warm and cold conditions: 37°C and -15°C respectively. Then, these concepts were compared against the short cabin (current cabin) and the 500 mm larger cabin without any mounted prototype. During each test, a thermal manikin was placed in the cabin’s bed in order to obtain not only temperature readings, but also the estimated comfort that the user would sense under these circumstances. As it could be expected, the 500 mm larger cabin without any added concept presented a temperature degradation of the current HVAC system compared to the short cabin. The areas of temperature concentration (warm or cold) were identified, being the rear wall of the cabin the most affected. The implementation of the concepts compared to the larger cabin gave positive results, reducing the time to reach the set temperature in the HVAC system controls in both warm and cold environments. The analysis of the results lead to the conclusion that the enlargement of a truck creates a need to maintain or improve the behavior of its HVAC system. The implementation of an auxiliary unit to the main system in the rear of the cabin showed not only temperature enhancements, but also a thermal comfort improvement for the user, allowing it to rest and therefore, to fulfill its tasks with the best mental and physical conditions.

"Early Access" refers to a software release strategy wherein consumers can acquire an incomplete version of the software and contribute to the development process by providing feedback. It has developed into a prevalent preference in the industry, embraced by a growing number of studios that decide to co-develop their upcoming games together with their customer base. Although the strategy is widely used, the perception of what the “Early Access” term practically translates to is fragmented: the operations and practices encompassed under the label differ from one studio to another, generating ambiguity around the term and lacking a clear, common understanding of the principles, variations, and frameworks that can be employed to implement this strategy. This research aims to build clarity around the model, understanding its key elements, common methods, and processes. We aim to provide insights into success factors and explore their dynamics from both the developers' and community perspectives of the process.

We performed an exploratory study, based on the findings from a qualitative analysis of insights gathered from 13 semi-structured interviews with developers, community managers, and practitioners within the industry. The analysis followed the GIOIA methodology, which enabled us to unfold the intricate array of insights and structure the information into six main aggregate dimensions of the core elements of Early Access, which were then compared to the results of a literature review of articles related to fields that share similar dynamics with Early Access practices.

The result is an extensive analysis of the Early Access methodology, as well as a set of principles and key factors for a successful approach to the model. The conclusion incorporates the pillars of the Early Access model, decoding its ambiguous definition, and presenting the variables that generate the variation of Early Access implementations, and their interdependencies. Furthermore, we analysed the community-building element and its key success factors, as well as presented an expanded approach to the feedback loop, highlighting the importance of a vision during the developed process and the evolution of roles and structures due to the method implementation.

Research background: Digital ecosystems in Europe are heterogenous organizations involving different economies, industries, and contexts. Among them, Digital Innovation Hubs (DIHs) are considered a policy-driven organization fostered by the European Commission to push companies’ digital transition through a wide portfolio of supporting services.

Purpose of the article: There are DIHs existing in all European economies, but literature needs more precise indications about their status and nature. The purpose is to study a distribution of DIHs and differences in portfolios of DIHs’ services across European economies. Therefore, the paper wants to deliver more precise data on effects on national and European policies. This is required to define their final role and scope in the complex dynamics of the digital transition, depending on regional context and heterogeneity of industries.

Methods: Data on 38 economies was collected from the S3 platform (on both existing and in preparation DIHs) and further verified by native speaking researchers using manual web scrapping of websites of DIHs identified from S3. To find potential similarities of digital ecosystems in different economies as emanated by the existence of DIHs, clusterization (Ward’s method and Euclidean distances) was applied according to the services offered. Economies were clustered according to the number of DIHs and the spread of DIHs intensity in different cities. The results were further analyzed according to the scope of the provided services.

Findings & value added: The applied clustering classified European economies in four different sets, according to the types of services offered by the DIHs. These sets are expression of the different digitalization statuses and strategies of the selected economies and, as such, the services a company can benefit from in a specific economy. Potential development-related reasons behind the data-driven clustering are then conjectured and reported, to guide companies and policy makers in their digitalization strategies.

With a rapid shift in our society to e-mobility, novel grease formulations for machine efficiency, reliability, and availability are even more important than ever. Greases are expected to provide low friction and noise while extending the machine service life. Whether the grease should be electrically conductive or not remains a subject of debate. The chapter discusses grease architecture and how to tune it in view of the latest and upcoming specification requirements. Selection strategies for base oils, thickeners, and additives are discussed. Integrating these components in the final formulation is a delicate process of balancing required properties that can be contradictory. Grease testing methods are addressed reflecting the need for complementary characterization of grease energy efficiency, conductivity, and protection against fretting. The arguments are made in connection to the representative transmission components.

The paper shows how grease thickener polarity affects performance of the typical powertrain components: gears and rolling element bearings. Greases based on a non-polar polypropylene thickener reduce friction losses (more than 20%) in high-speed deep groove ball bearings and provide a longer service life (more than 2 times) in highly loaded bevel gears, compared to the greases based on polar lithium thickeners. The electrification and sustainability trends have led to additional requirements to be addresses during grease design process: tunable electric conductivity and reduced environment footprint. The grease design challenges caused by the novel requirements and potential solutions are discussed.

In this chapter, we propose a roadmap for the development of education in mechatronics. This development is intended to support future mechatronics engineers in accepting challenges in evolution, development, and sustainability. We explore curricula design, learning strategies, and misalignment between education and professional needs in relation to these challenges. The exploration is based on the fact that the subject mechatronics has now been around for 50 years, and, in particular, relates to the experiences and previous research of the authors, who are based at KTH Royal Institute of Technology where most of the empirical data is from. In this chapter, we argue that the above challenges require new roles, skills, and competencies among mechatronics engineers. With examples from complex product development, we argue that an increased systems perspective with systems architect competencies and experiences can support the embracing of additional systems design factors, which, for example, can enable sustainable development aspects into product design. We explore the interface between mechatronics and systems engineering, via embedded systems, as a possible future development of the subject of mechatronics. Embedded systems can be seen as a related subject, or as a subset of mechatronics, or vice versa. With this chapter, we argue that the subject of embedded systems can provide a shortcut for mechatronics education to approach the role of systems engineering, thereby reaching a level of competence and skills where the above challenges can be approached. The mechatronics engineer can play an important role in sustainable development. With existing curricula, mechatronics engineers are prepared to accept complex problem-solving, utilize solutions from various domains and disciplines, and create domain-independent solutions. These skills are crucial in embracing sustainable development, which puts the mechatronics engineer in a unique position. We also bridge the above discussion with current trends in learning, such as life-long learning and e-learning. The mechanisms that enable the mechatronics engineer to achieve a systems engineering skillset, which, according to our results, needs to be based on engineering experiences, is facilitated both by a professional education system (life-long learning) and by a flexible setup (e-learning).