The advent of powered toothbrushes and associated mobile health applications provides an opportunity to collect and monitor the data, however collecting reliable and standardized data from large populations has been associated with efforts from the participants and researchers. Finding a way to collect data autonomously and without the need for cooperation imparts the potential to build large knowledge banks. A solution with Bluetooth low energy technology is designed to pair a powered toothbrush with a single-core processor to collect raw data in a real-time scenario, eliminating the manual transfer of powered toothbrush data with mobile health applications. Associating powered toothbrush with a single-core processor is believed to provide reliable and comprehensible data of toothbrush use and propensities can be a guide to improve individual exhortation and general plans on oral hygiene quantifies that can prompt improved oral wellbeing. The method makes a case for an expanded chance to plan assistant capacities to protect or improve factors that influence oral wellbeing in individuals with mild cognitive impairment. The proposed framework assists with determining various parameters, which makes it adaptable and conceivable to execute in various oral care contexts 

The paper presents an Artificial Intelligence-driven approach to predictive maintenance for Product-Service System (PSS) development. This study focuses on time-based and condition-based maintenance, leveraging variational autoencoders to identify both predicted and unpredicted maintenance issues in autonomous haulers. By analyzing data patterns and forecasting future values, this approach enables proactive maintenance and informed decision-making in the early stages of PSS development. 

The inclusion of interaction terms enhances the model’s ability to capture the interdependencies among system components, addressing hidden failure modes. Comprehensive evaluations demonstrate the effectiveness and robustness of the developed models, showcasing resilience to noise and variations in operational data. 

The integration of predictive maintenance with PSS development offers a strategic advantage, providing insights into vehicle performance early in the development phases. This empowers decision-makers for efficient resource allocation and proactive maintenance planning. The research highlights the limitations and potential areas of improvement while also emphasizing the practical applicability and significance of the developed models in enhancing PSS development. 

This paper presents an approach that utilizes artificial intelligence techniques to identify autonomous machine behavior patterns. The context for investigation involves a fleet of prototype autonomous haulers as part of a Product Service System solution under development in the construction and mining industry. The approach involves using deep learning-based object detection and computer vision to understand how prototype machines operate in different situations. The trained model accurately predicts and tracks the loaded and unloaded machines and helps to identify the data patterns such as course deviations, machine failures, unexpected slowdowns, battery life, machine activity, number of cycles per charge, and speed. PSS solutions hinge on efficiently allocating resources to meet the required site-level output. Solution providers can make more informed decisions at the earlier stages of development by using the AI techniques outlined in the paper, considering asset management and reallocation of resources to account for unplanned stoppages or unexpected slowdowns. Understanding machine behavioral aspects in early-stage PSS development could enable more efficient and customized PSS solutions.

A data analysis method based on artificial neural networks aiming to support cause-and-effect analysis in design exploration studies is presented. The method clusters and aggregates the effects of multiple design variables based on the structural hierarchy of the evaluated system. The proposed method is exemplified in a case study showing that the predictive capability of the created, clustered, a dataset is comparable to the original, unmodified, one. The proposed method is evaluated using coefficient-of-determination, root mean square error, average relative error, and mean square error. Data analysis approach with artificial neural networks is believed to significantly improve the comprehensibility of the evaluated cause-and-effect relationships studying PSS concepts in a cross-functional team and thereby assisting the difficult and resource-demanding negotiations process at the conceptual stage of the design.

Background: Traditionally, assessing the degree of ossification in the epiphyseal plate for growth plate development relies on manual evaluation, which can be inefficient due to the complexities of the distal femoral epiphysis anatomy. Existing methods lack efficient detection techniques.

Method: This study proposes an AI-based decision support system, designed within a product-service system (PSS) framework, to automate ossification assessment and detection of the distal femoral epiphysis in knee magnetic resonance imaging (MRI) data. The system leverages advanced machine learning techniques, specifically two Convolutional Neural Networks (CNNs), combined with computer vision techniques. This intelligent system analyzes MRI slices to predict the optimal slice for analysis and identify variations in the degree of ossification within individual datasets.

Results: The proposed method's effectiveness is demonstrated using a set of T2-weighted gradient echo grayscale knee MRI data. The system successfully detects the complex anatomy of the distal femoral epiphysis, revealing variations in the degree of ossification ranging from completely closed/open to fully open/closed regions.

Conclusions: This study presents a robust and efficient AI-based method, integrated within a PSS framework, for measuring the degree of ossification in the distal femoral epiphysis. This approach automates ossification assessment, providing valuable insights for clinical decision-making by clinicians and forensic practitioners. The PSS framework ensures seamless integration of the AI technology into existing workflows.

A manufacturing company’s unique intellectual capital is to a large extent built on experience from its own product development and manufacturing processes. Thus, methods and tools to utilize and benefit from this experience in an efficient way have an impact on a company’s ability to stay competitive and advance on the global market. Knowledge Based Engineering (KBE) is an engineering methodology to capture engineering knowledge systematically into the design system. Hence, KBE tools are considered to support experience re-use and improve engineering activities. This paper presents the results from a study where the objective was to investigate the support for experience re-use in KBE applications in an aerospace company. A proposed framework is presented to analyze the capturing and use of experience in a company’s processes identifying gaps and propose improvements. The study revealed weaknesses in the process steps for experience feedback which can be used to improve KBE applications further.

The paper explores the implementation process of an innovation measuring system prototype to support a heavy machinery multinational company to secure their innovative capability. In general,companies recognize the importance of becoming innovative to become, or remain, competitive on a global market. The case company decided to pilot a metric system that corresponds to the crucial factors to secure innovative capability and work with the stepwise improvement based on the assessment results.

The methods are based on design-research approach and participatory action research. Interviews, surveys and observation were used, as well as, workshops were conducted to develop and follow up the implementation innovation measuring system.

The findings explore topics and open questions related to metric selection, purpose and use of the selected indicators, as well as challenges related to the implementation of the metric system. Some of the conclusions question the viability of measuring project teams, as well as, it suggests the need for further research to clarify whether team metrics need to be develop in parallel to organizational ones.

Companies are constantly being pressured to innovate in order to stay competitive in the short run and have new offerings in the long run. One way of boosting innovation is to develop idea support systems that go beyond the traditional methods and tools. Through a qualitative study, this paper explores the lessons learned from developing an online platform for idea generation, and discusses it in terms of innovation process, climate, and capabilities. The results show that the platform itself is not enough for innovation. The structure and work processes around the platform are as important, which implies the need to design processes and procedures that allow an idea to develop, providing, focus, idea feedback and role clarity.

Literature points out the need for companies to innovate continuously. Such need requires that companies develop capacities to exploit and improve current work as well as to develop and explore more radical opportunities. This paper is a case study that investigates the innovation capabilities of a multinational manufacturing company by interviewing a group that is mandate to support the development of those capabilities. The data was collected by semi-structured interviews, which were based on the categories of a framework previously developed. The findings speak about the importance of setting clear processes for continuation and implementation of ideas, adequate allocation of resources and management support. The discussion and conclusion are about the importance of the integration of efforts in different organizational levels and some of the future challenges integrating the innovation efforts into a natural way of working.

A basic principle for Needfinding [Faste, 1987; Patnaik & Becker, 1999] is that designers and engineers should interact directly with users to get direct insights into the user domain. Needfinding is not a new phenomena, it is almost forty years ago since the process was adopted at Stanford University’s product design program [Patnaik & Becker, 1999]. As the name, Need-finding, implies, this is an intertwined approach to find needs which are not readily articulated by users. The application of a Needfinding process offers qualitative methods to make those needs visible early on in product development. In fact, the process has become more interesting during recent time, since qualitative methods have gained more acceptance outside the academic realm [ibid.].The word qualitative indicates that what are sought for are qualities such as people’s experiences, what they perceive or interpret into a situation [Miles & Huberman, 1994; Patton, 2002]. Such data is contextually dependent, i.e., it must be generated in the context in which the phenomena occur. Besides context, people’s activities, behaviours and goals are important to observe and learn from. The objectives, for applying Needfinding, are to make the identification of needs and design a seamless effort, as well as an interest to identify opportunities to innovations. Needs last longer than any solution [Patnaik & Becker, 1999], since they are grounded in people’s activities. The solution and product that might meet such needs change over time. One example is how to store computer data, the products which satisfy the need has changed from, e.g., punch cards, magnetic tape, floppy discs [ibid.] to USB-flash memories. A guiding methodology in Needfinding is a flexible process, which is adapted to the task at hand [Kelley, 2001]. Such a process is conveyed in a few basic steps and, builds on a ‘philosophy’ which permeates all activities in order to adapt the process according to the project. Therefore, the designer’s ability to rely on such a process depends on familiarity with a number of methods for observations and interviews, as well as an aptitude for socio-technical skills. Hence, the purpose in this paper is to present and reflect on methods used in a running development project to identify needs in a product development project. This is done to contribute to the advancement of a need driven product development process. The disposition of this paper is as follows. First, our approach in studying the need identification activities is presented. Second, a theoretical frame for need identification and design is presented, i.e., Needfinding [Patnaik & Becker, 1999]. Third, the practice of finding needs is outlined and discussed.

The paper presents a discussion about gaps and opportunities for cross-pollination between Value Driven Design and Lean Product Service Development to promote the use of value-driven method and tools since the preliminary design stages. In particular the paper discusses how methods and tools developed in Value Driven Design have the potential to be applied in the preliminary design stage in the context of Lean Product Service Development. The paper concludes by defining a research area on Value Innovation method and tools for preliminary Lean Product Service Development.

Emerging from an industrial case study in the aerospace industry, the paper proposes an approach to evaluate sub- system technology concepts from a life cycle perspective. The approach is composed by 5 main phases that aims to drive product designers towards more value-oriented design decisions. It is shown how different life cycle alternatives, such as the selling of a Product-Service-System instead of a traditional product, deeply impact the value of design alternatives. The described approach has been developed in collaboration with industrial partners and represents a potential instrument to enhance value-driven product design.

The paper presents a literature review about data mining applications in Product/Service-Systems (PSS) design. A systematic literature review, combined with snowballing techniques, has been run to identify relevant contributions in the area. The analysis has focused on the categorization of the contributions according to their impact on the PSS design process and according to their theoretical or empirical nature. A picture of the different research achievements for each stage of the PSS design process have been drawn, identifying the research gaps in respect to the challenges of PSS design. Based on the analysis the paper proposes a set of research questions for each PSS design stage with the intent of facilitating the application of data mining techniques in PSS design, and ultimately push forward the state of the art.

The paper presents a study run to verify the applicability of data mining algorithms as

decision support in early design stages of a product development project. The paper

describes a two-stage scenario providing the rationale for the application of data science in

engineering design. Furthermore, it describes a demonstrator showing how data can be fed

back to the early design stages and can be used to populate models to reduce uncertainty in

decision making. A wheel loader for constructions works is the reference product for the

demonstration. Data mining is applied on a dataset built on machine performances and

contextual and environmental data. The demonstrator focuses on the estimation of the fuel

consumption of alternative design concepts and estimates the performance variations given

different contextual variable. Finally, a way of visualizing the results of the data analysis in

relation to the tested and expected performances is presented.

The paper presents a Model-Driven approach for Product-Service System (PSS) Design promoting an increased digitalization of the PSS design process based on the combination of data-driven design (DDD) activities and value-driven design (VDD) methods. The approach is the results of an 8-year long research profile named (omitted for blind review) featuring the collaboration between (omitted for blind review) and nine industrial companies, in the field of PSS Design. It combines VDD models and the supporting data-driven activities in the frame of PSS design and aligns with the product value stream and the knowledge value stream in the product innovation process as described by Kennedy et al. (2008). The paper provides a high-level overview of the approach describing the different stages and activities, and provides references to external scientific contributions for more exhaustive descriptions of the research rationale and validity. The approach is meant to ultimately drive the development and implementation of a simulation environment for cross-functional and multi-disciplinary decision making in PSS, named Model-Driven Decision Arena, describe in the concluding part of the paper.

The aim of the paper is to present an approach for the multidisciplinary evaluation of alternative modular concepts in preliminary design with the intent of enhancing engineers’ capability to simulate alternative scenarios with different design configurations, so to derive decisions about the most valuable design concepts to further develop. The research contribution is novel in the way that it expands the Set-Based-Engineering approach by addressing the “servitization” challenge in two ways: firstly by the use of value models and sustainability models as decision making support, making possible a preliminary assessment of the value contribution and of the sustainability performances of a design concept;secondly, by the use of functional modelling modules and configurable systems elements for platform-based design, to manage the  complex relationships within and between parts of the platform throughout the lifecycle. The paper presents the main features of the approach and introduces an industrial case concerning the development of a module component for an aircraft engine in which the approach is applied for demonstration. The paper finally elaborates on the benefits and implications of the approach in the design process.

The paper presents an approach, based on the development of digital twins, to support the transition toward electromobility and autonomy in the mining industry, by supporting the design space exploration of future operational scenarios based on different construction equipment and mining site configurations. With such an intent, the paper presents an approach combining systems and systems-of-systems simulations to run trade-off analysis based on different product-service systems (PSS) configurations. Additionally, the paper integrates the "operational context"variables in PSS design simulations to create a digital twin of a "mining operational scenario"customizable for the specific configurations of each mine. The paper exemplifies the proposed approach by contextualizing in a reference mining site describing how the multi-dimensional simulations have enabled PSS trade-off analysis and PSS sensitivity analyses, and how operational context variables are integrated into the digital twin of the operational scenario. © 2022 The Authors.

In recent times a service-dominant logic is permeating the design of complex systems. However, in spite of their appeal, initiatives such as Product Service Systems (PSS) have not become mainstream, and methods are lacking to support this transition. This paper argues that methodological guidance, as well as tools for decision support, may be found in the research field of Value Driven Design (VDD), which originates in the realm of Systems Engineering. The paper objective is to elaborate on gaps and opportunities for cross-pollination between VDD and PSS. The results of a systematic review of methods and tools for design decision support highlight the opportunity for introducing optimization models derived from VDD in the PSS design process, while the latter can enrich VDD research with a more qualitative value assessment logic. The paper summarizes this integration in a methodological approach, and exemplifies its application in case studies mainly from the aerospace and road construction equipment sector.

Designing and implementing a Knowledge Management System (KMS) in a Virtual Enterprise is a labour intensive and risky task. Solution prototypes (Pilots) are usually built to verify system effectiveness prior to final implementation. The paper proposes a methodology to guide this Pilot specifications definition process. These guidelines support engineers and knowledge experts in collaboratively defining functionalities, services, software components and performance indicators of the prototype. The methodology has been conceived and applied within the European project VIVACE, to support the development of a Knowledge Enabled Engineering (KEE) system in the aeronautical domain.

The emerging industrial business partnerships, which feature cross-functional and cross-company development efforts, raise the barrier for the establishment of effective knowledge sharing practices in the larger organization. This chapter aims to highlight the role of knowledge as a key enabler for effective engineering activities in the light of such emerging enterprise collaboration models. Knowledge Enabled Engineering (KEE) is presented as an approach to enhance the extended organization’s capability to establish effective collaboration among its parts, in spite of different organizational structures, technologies or processes. KEE is analysed in its constituent parts, highlighting areas, methods and tools that are particularly interesting for leveraging companies’ knowledge sharing capabilities.

The main aim of this paper is to present a methodology developed within the European Project VIVACE to guide the design and implementation of a Knowledge Enabled Engineering (KEE) system in a Virtual Enterprise. The proposed methodology tries to overcome some of the limitations which characterise traditional methods for Target Cascading, promoting a more collaborative and iterative approach to derive system specifications (in terms of advanced knowledge functionalities) from initial high-level targets. Social and behavioural aspects of Knowledge Management play a crucial role when many different users, knowledge experts, and process owners are involved in the Knowledge Management System (KMS) development. A well designed methodology is needed, therefore, to enhance communication and information sharing among design teams, to promote requirements merging and to take care both of the technological and behavioural aspects of the implementation. Initial business targets have been step-by-step decomposed into a set of sub-problems (Service Requirements, Knowledge Issues, and Knowledge Challenges) in the form of simple sentences in natural language. Then Quality Function Deployment (QFD) matrixes have been used to identify the set of functionalities to be implemented in the system, addressing the most important knowledge-related problems outlined in the cascading activity.

The aim of the paper is to discuss the rising potential of social software to increase the knowledge management capabilities of virtual product development teams. It presents six fundamental transitions, elaborated from the empirical findings, which justify the rise of a more bottom-up, social creation and sharing of engineering knowledge in the virtual organisation. The study suggests that traditional engineering knowledge management approaches alone are not sufficient to support development activities in the virtual organisation, and that such teams display an increasing demand for social, comparatively lightweight and remixable platforms for bottom-up, social creation and sharing of knowledge.

In Product Service Systems development, understanding the customer use of goods is vital, since the product per se is not sold but rather the performance it brings to the purchaser in terms of added value. Moving away from offering just a product or service to become a provider of "integrated solutions" implies inevitable changes in the interaction with the customer as well as in the way knowledge is managed and shared in the cross company environment. The main aim of this paper is, on one hand, to provide examples of how Product-Service Systems raise the demand on such cross-functional knowledge sharing; on the other hand it aims to point out a set of requirements for the successful development of Knowledge Enabled Engineering systems able to support a PSS paradigm in a Virtual Enterprise context.

In PSS design, hardware and service developers often have different objectives. Lacking to communicate and negotiate them across boundaries might lead to solutions unable to generate market shares and long-term profitability. This paper aims to contribute to the definition of ‘boundary objects’ that facilitate the sharing of knowledge between members of cross-functional teams engaged in PSS conceptual design activities. Empirical data are gathered from three case studies in the Swedish manufacturing industry to reveal how servitization affects early stage design decision-making, and how hardware vs. service trade-offs are negotiated and solved. The analysis of the findings points to four main trends to be considered when designing such objects in the realm of PSS. These are: an underlying model-based logic, the use of metrics based on customer value, the ability to quickly generate and assess scenarios, the use of non linear relationships to map PSS features vs. customer value.

The actual product ownership often remains with the manufacturer as functional (total care) products emerge in aerospace business agreements. The business risk is then transferred to the manufacturer why downstream knowledge needs to be available in the concept phase to consider all product life cycle aspects. The aim of this work is to study how a multidisciplinary design tool can be used to embed downstream processes for conceptual design and evaluation allowing simulation of life cycle properties. A knowledge enabled engineering approach was used to capture the engineering activities for design and evaluation of jet engine component flanges. For every design change, cost of manufacturing operations, maintenance and performance aspects can be directly assessed. The design tool assures that the engineering activities are performed accordingly to company design specification which creates a better control over the process quality. It also creates a better understanding enabling the engineers to optimize the concept in real time from an overall product life cycle view. The new tool will be the base for optimize the total product system and will be used not only between companies but also between product development departments in large global companies.

Privacy-invasive software, loosely labeled spyware, is an increasingly common problem for today’s computer users, one to which there is no absolute cure. Most of the privacy-invasive software are positioned in a legal gray zone, as the user accepts the malicious behaviour when agreeing to the End User License Agreement. This paper proposes the use of a specialized reputation system to gather and share information regarding software behaviour between community users. A client application helps guide the user at the point of executing software on the local computer, displaying other users’ feedback about the expected behaviour of the software. We discuss important aspects to consider when constructing such a system, and propose possible solutions. Based on the observations made, we implemented a client/server based proof-of-concept tool, which allowed us to demonstrate how such a system would work. We also compare this solution to other, more conventional, protection methods such as anti-virus and anti-spyware software.

The un-sustainable course of our societies is the greatest threat humanity has ever confronted. The biophysical systems upon which we are totally dependent have not been challenged by human activities at the global scale before and our impacts upon those planetary systems, as well as upon our social systems, cannot be adequately addressed by ad hoc solutions. Science and leadership will be required to address this threat and transform our current societies into sustainable societies. This Special Volume presents an evolving, yet increasingly cohesive, science-based perspective on leadership towards sustainability. Examples of crucial, overall questions addressed by authors of articles in this Special Volume are: How can science help to clarify sustainability as a foundational platform for success for society's core institutions (e.g. business, governance and education), and how can this platform inform envisioning, planning, monitoring, communication and decision making to accelerate the needed transitions? The conceptual framing of sustainable development in this Special Volume is based upon the logic that it is only if we can define sustainability in a scientifically solid way, as a frame for any vision, that we can analyze current situations in relation to such sustainable visions, and design strategies to close the gap to such visions. In moving from current situations towards possible sustainable futures, specific support in the form of leadership concepts, methods, tools, and requirements are also essential, i.e. given clarity around what needs to be achieved, effective leadership then requires knowing how to achieve it. Both the what and the how questions are addressed in this Special Volume. The research described provides a foundation for moving from ad hoc activities to systemic, systematic and strategic transitions towards sustainability. © 2016 Elsevier Ltd

Systematic leadership towards sustainability implies utilization of systems thinking for step-wise approaches to transformative changes towards sustainable societies. This ‘call-for-papers’ (CfPs) for a Special Volume of the Journal of Cleaner Production is focused upon what types of research are needed for us to make the necessary local, regional, national and global changes. This CfPs is for anyone who wishes to address these challenges seriously, that is, to utilize essential aspects of leadership to contribute strategically to the transition towards sustainable societies. To successfully address these challenges, people from different sectors and disciplines must work together in a coordinated and efficient way. We wish to explore the question: What support do such transformative endeavors require and how can science contribute?

The objective of this paper is to discuss how Knowledge Enabled Engineering, when combined with simulation methods is a development step for product development processes, engineering design methods and evaluation support systems. The paper opens the discussion on how these approaches, i.e. work methods, simulation support and Knowledge Enabled Engineering (KEE) methods affects best practice in engineering design (ED) by adding synthesis support to the already existing analysis support. In the presented work the authors discuss the actual state of industrial applications, with challenges and opportunities, at Volvo Car Corporation, automotive manufacturer, and Volvo Aero Corporation, jet engine component manufacturer, both operating in Sweden.

In recent years there has been a growing interest among product development organizations to capitalize on engineering knowledge as their core competitive advantage for innovation. Capturing, storing, retrieval, sharing and reusing of engineering knowledge from a wide range of enterprise memory systems have become crucial activities of knowledge management practice in competitive organizations. In light of a changing and dynamic enterprise definition, including a move towards Product-Service System (PSS) development, this paper discusses some of the limitations of current enterprise systems in reusing engineering knowledge across functional and corporate boundaries. Further, the paper illustrates how Web 2.0-based collaborative technologies can leverage cross-functional knowledge for new PSS development projects through an open, bottom-up, and collective sense-making approach to knowledge management.

Ubiquitous and pervasive computing holds great potential in the domain of Product-Service Systems to introduce a model-driven paradigm for decision support. Data-driven design is often discussed as a critical enabler for developing simulation models that comprehensively explore the PSS design space for complex systems, linking of performances to customer and provider value. Emerging from the findings of two empirical studies conducted in collaboration with multinational manufacturing companies in the business-to-business market, this paper defines a data-driven framework to support engineering teams in exploring, early in the design process, the available design space for Product-Service Systems from a value perspective. Verification activities show that the framework and modeling approach is considered to fill a gap when it comes to stimulating value discussions across functions and organizational roles, as well as to grow a clearer picture of how different disciplines contribute to the creation of value for new solutions.

The pantograph-catenary system is a critical component for trains required to run at higher speeds. The pantograph often includes nonlinear characteristics and the scope of this work is to investigate if nonlinear dynamic phenomena can occur in an existing design. A model of a pantograph suspension subsystem has been developed according to physical parameter values of the head suspension of the Schunk WBL88/X2 pantograph, providing electric power to the Swedish high-speed train X2. Studies of the system response for different force excitation show both harmonic, subharmonic and chaotic behaviour for the investigated parameter regions.

Modelling and simulation of the dynamic behaviour of catenary-pantograph interaction is an important part when assessing the capability of a current collection system for railway traffic. The large variation in infrastructure characteristics in different countries and railway companies, different types of traffic, designs of pantographs etc. makes it almost impossible to develop a final simulation model of such a system. Instead, it would be favourable to have a tool that has the ability to set up models of such systems, choose relevant detail of the models, run simulations and finally visualize the results. To make the tool useful for engineers, design experts as well as simulation experts, the functionality of the tool must be worked out. Aspects on computer simulation such as developed models, simulation methods and computer tools are presented. The aim is to develop a scenario that considers different designs, models, solution methods and user levels. The scenario focuses on how to structure the use of simulation of dynamics in catenary-pantograph development. A scenario is sketched built on different user levels, a modular structure and a structure for information management

Designing systems working in health care needs complying with the heterogeneous, overlapping, non-overlapping, competing, or even contradicting requirements expressed by the various actors of the health care complex environment, including regulatory bodies. The unification method introduced in this paper, utilized ontological struc- tures to unify heterogeneous requirements in different levels of ab- straction. Also the weighting and threshold algorithms defined upon the ontology structure allows to both prioritize the requirements and align design resources upon that priority, at the same time to enforce regulatory requirements in an easy, clear and integrated way and reject designs which cannot comply with them. Application of the method introduced in this paper is not limited to health care, but it might be applied in design for any heterogeneous environment.

Background: There are several frameworks that attempt to address the challenges of evaluation of health information systems by offering models, methods, and guidelines about what to evaluate, how to evaluate, and how to report the evaluation results. Model-based evaluation frameworks usually suggest universally applicable evaluation aspects but do not consider case-specific aspects. On the other hand, evaluation frameworks that are case specific, by eliciting user requirements, limit their output to the evaluation aspects suggested by the users in the early phases of system development. In addition, these case-specific approaches extract different sets of evaluation aspects from each case, making it challenging to collectively compare, unify, or aggregate the evaluation of a set of heterogeneous health information systems.

Objectives: The aim of this paper is to find a method capable of suggesting evaluation aspects for a set of one or more health information systems—whether similar or heterogeneous—by organizing, unifying, and aggregating the quality attributes extracted from those systems and from an external evaluation framework.

Methods: On the basis of the available literature in semantic networks and ontologies, a method (called Unified eValuation using Ontology; UVON) was developed that can organize, unify, and aggregate the quality attributes of several health information systems into a tree-style ontology structure. The method was extended to integrate its generated ontology with the evaluation aspects suggested by model-based evaluation frameworks. An approach was developed to extract evaluation aspects from the ontology that also considers evaluation case practicalities such as the maximum number of evaluation aspects to be measured or their required degree of specificity. The method was applied and tested in Future Internet Social and Technological Alignment Research (FI-STAR), a project of 7 cloud-based eHealth applications that were developed and deployed across European Union countries.

Results: The relevance of the evaluation aspects created by the UVON method for the FI-STAR project was validated by the corresponding stakeholders of each case. These evaluation aspects were extracted from a UVON-generated ontology structure that reflects both the internally declared required quality attributes in the 7 eHealth applications of the FI-STAR project and the evaluation aspects recommended by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. The extracted evaluation aspects were used to create questionnaires (for the corresponding patients and health professionals) to evaluate each individual case and the whole of the FI-STAR project.

Conclusions: The UVON method can provide a relevant set of evaluation aspects for a heterogeneous set of health information systems by organizing, unifying, and aggregating the quality attributes through ontological structures. Those quality attributes can be either suggested by evaluation models or elicited from the stakeholders of those systems in the form of system requirements. The method continues to be systematic, context sensitive, and relevant across a heterogeneous set of health information systems.

Background and Objectives

Survey-based evaluation of a system, such as measuring user’s satisfaction or patient-reported outcomes, entails a set of burdens that limits the feasibility, frequency, extendability, and continuity of the evaluation. Automating the evaluation process, that is reducing the burden of evaluators in questionnaire curation or minimizing the need for explicit user attention when collecting their attitudes, can make the evaluation more feasible, repeatable, extendible, continuous, and even flexible for improvement. An automated evaluation process can be enhanced to include features, such as the ability to handle heterogeneity in evaluation cases. Here, we represent the design of a system that makes it possible to have a semi-automated evaluation system. The design is presented and partially implemented in the context of health information systems, but it can be applied to other contexts of information system usages as well.

Method

The system was divided into four components. We followed a design research methodology to design the system, where each component reached a certain level of maturity. Already implemented and validated methods from previous studies were embedded within components, while they were extended with improved automation proposals or new features.

Results

A system was designed, comprised of four major components: Evaluation Aspects Elicitation, User Survey, Benchmark Path Model, and Alternative Metrics Replacement. All components have the essential maturity of identification of the problem, identification of solution objectives, and the overall design. In the overall design, the primary flow, process-entities, data-entities, and events for each component are identified and illustrated. Parts of some components have been already verified and demonstrated in real-world cases.

Conclusion

A system can be developed to minimize human burden, both for the evaluators and respondants, in survey-based evaluation. This system automates finding items to evaluate, creating questionnaire based on those items, surveying the users' attitude about those items, modeling the relations between the evaluation items, and incrementally changing the model to rely on automatically collected metrics, usually implicit indicators, collected from the users, instead of requiring their explicit expression of their attitudes. The system provides the possibility of minimal human burden, frequent repetition, continuity and real-time reporting, incremental upgrades regarding environmental changes, proper handling of heterogeneity, and a higher degree of objectivity.

Background:

Several models suggest how the qualities of a product or service influence user satisfaction. Models, such as the Customer Satisfaction Index (CSI), Technology Acceptance Model (TAM), and Delone and McLean Information Systems Success (D&M IS), demonstrate those relations and have been used in the context of health information systems.

Objective:

We want to investigate which qualities foster greater satisfaction among patient and professional users. In addition, we are interested in knowing to what extent improvement in those qualities can explain user satisfaction and if this makes user satisfaction a proxy indicator of those qualities.

Methods:

The Unified eValuation using ONtology (UVON) method was utilised to construct an ontology of the required qualities for seven e-health applications being developed in the FI-STAR project, a European Union (EU) project in e-health. The e-health applications were deployed across seven EU countries. The ontology included and unified the required qualities of those systems together with the aspects suggested by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. Two similar questionnaires, for 87 patient users and 31 health professional users, were elicited from the ontology. In the questionnaires, user was asked if the system has improved the specified qualities and if the user was satisfied with the system. The results were analysed using Kendall correlation coefficients matrices, incorporating the quality and satisfaction aspects. For the next step, two Partial Least Squares Structural Equation Modelling (PLS-SEM) path models were developed using the quality and satisfaction measure variables and the latent construct variables that were suggested by the UVON method.

Results:

Most of the quality aspects grouped by the UVON method are highly correlated. Strong correlations in each group suggest that the grouped qualities can be measures which reflect a latent quality construct. The PLS-SEM path analysis for the patients reveals that the effectiveness, safety, and efficiency of treatment provided by the system are the most influential qualities in achieving and predicting user satisfaction. For the professional users, effectiveness and affordability are the most influential. The parameters of the PLS-SEM that are calculated allow for the measurement of a user satisfaction index similar to CSI for similar health information systems.

Conclusions:

For both patients and professionals, the effectiveness of systems highly contributes to their satisfaction. Patients care about improvements in safety and efficiency, while professionals care about improvements in the affordability of treatments with health information systems. User satisfaction is reflected more in the users' evaluation of system output and fulfilment of expectations, but slightly less in how far the system is from ideal. Investigating satisfaction scores can be a simple, fast way to infer if the system has improved the abovementioned qualities in treatment and care.

This is a qualitative single case study of a geographically distributed student team that experienced a quite different graduate course, compared to previous year's. This was due to the restrictions placed upon them following coronavirus lockdowns. With already ongoing research, and continuous development of the course, the authors had documented individual reflections and identified patterns and behaviours that seemingly determined the quality of the end result, as well as the students expectations and experiences. Semi-structured interviews, surveys and the author's individual reflection notes were already in place as part of the larger research scope and when the student team during the covid-19 year showed unexpected performance and results, the authors decided to pause the larger research scope and focus on this unique single case and capture those learnings. Not knowing how the Covid-19 situation evolves and leaning on insights from previous years, as well as this unique year, the aim with this paper is to describe the unique Covid-19 year amd share knowledge that can help improve and evolve the development of this longlived collaborative graduate student course, and other similar distributed team contexts.

This research investigates globally dispersed innovation teams involved in explorative projects within an engineering graduate course employing problem-based learning. Utilizing insights from a longitudinal study, the objective is to identify how to enhance both individual learning and team performance, thereby increasing the likelihood of a successful outcome. Initial observations revealed common patterns in learning experiences among the top-performing teams, prompting further investigation into how supporting cohorts might positively influence both team performance and students’ learning experiences throughout the course. In addition to advancing comprehension of innovation team performance, the study introduces two lightweight tools designed as shared visual representations of the team’s exploration journey. These tools can assist supporting cohorts in guiding teams effectively. This research augments the existing body of knowledge surrounding the achievement of breakthrough innovations. It provides understanding about how to facilitate team performance and individual learning within globally dispersed innovation teams undertaking explorative projects. The proposed lightweight tools offer practical solutions to enhance the supporting cohort’s ability to guide and impact team performance and individual learning experiences. This study holds implications for academia and industry, particularly organizations reliant on radical innovation for competitiveness and future-proving. Lastly, the study’s findings could inform the design and delivery of future problem-oriented, project-organized learning-based courses in engineering education.

As large manufacturing incumbents are adopting digital technologies and shifting their business models from selling products to solving problems, through PSS (product-service-system) solutions, their development processes need to shift as well. Organizational ambidexterity, the ability to both explore new opportunities and exploit existing customer offerings, is considered to be crucial to companies’ current and future success. In this study it is observed that a gap between exploration and exploitation work streams lead to promising conceptual PSS solutions never reaching a revenue generating stage. This is because product-centricity along with exploitation-optimized processes and mindsets are not equipped to carry the integrated solutions further, from proven concept to market ready solution. This article summarizes a multiple case study, where systematic innovation engineering work has resulted in promising conceptual PSS solutions never reaching market launch. In addition to the in-depth case studies, leaders of exploration-oriented teams in manufacturing incumbents shared their insights which confirmed that the problem is common across companies and industries, and several roadblocks are general. One of the authors has been responsible for a successful shift from a product-centric to an integrated solution-oriented organization and contributed insights from that experience to this study. The authors suggest that the gap between explore and exploit, and the shift from product-centric to PSS-oriented can be managed through an approach where ambidexterity is infused into the entire organization and exploration is demystified, enabling a transparent and concerted shift.

This paper covers research about how Corporate Innovation Hubs, CIHs, in Silicon Valley are managed and supported by their corporatemotherships and how their likeliness of success can be increased by consciousand proactive management and support. To embrace the cultural difference as a competitive advantage and learning experience is important. Clear intentions,expectations, team constellation, reporting level and finding the right individualas head of the CIH are identified as crucial factors to consider.

This paper discusses views on decision support in product development to identify factors of relevance when designing computer-based decision sup- port for total offers. Providing services in form of physical artefacts of- fered as ‘functions per unit’ is at the heart of total offers. Total offers gain access to possibilities to ‘design in’ value added characteristics into the physical artefact, e.g., maintenance, monitoring, training, remanufacture. Contemporary computer tools seem to be insufficient to support a GO/NO GO decision for total offers. Relevant factors to take into consideration are to support learning and provide the decision makers with insights in a number of plausible ‘what-if’ scenarios to improve the solution space.

In Product-Service Systems development, understanding of the customers' use of goods seems vital, since the product per se is not sold but rather the performance it brings to the customers' processes in terms of added value. This changed business scenario insists on an integration of a service and a product perspectives in early design phases. However, the approaches to understand customers diverge. In this paper, a need matrix, from the economic theory of needs, and a requirement matrix, from the TRIZ methodology, are used to elaborate on integration aspects to understand customer statements. The comparison of these matrixes made the distinct logics apparent, and gave an indication for the necessity of another type of specification for PSS products. Also, the knowledge base for PSS methodologies has to be extended to encompass a part that visualizes non measurable aspects such as needs.

Functional products are understood as a combination of hardware, software and services. Based on interviews with employees in manufacturing firms the notion of functional product development is described. The purpose has been to explore the differences between a service perspective and a core product perspective and highlight changes in the management of product development processes that are motivated by the notion of functional products. Exploring the differences between the two perspectives has identified a gap of how the product is viewed at the business level and technical development levels. The integration of services into the hardware development process in the form of a customised product or product life cycle has been highlighted. Internal and external communication about needs has been identified as useful.

The adaptation of Product/Service-System calls for new development models. On one side this businesses give the manufacturing firm possibilities to redesign, upgrade and replace the discrete device that provides the performance their customers are asking for. On the other side, this new situation has to address aspects that are normally not addressed in early product development, i.e., services. In this chapter, we will elaborate on product and service development processes models, as well as system models to propose a frame of reference for multiple perspectives on PSS development. These perspectives are people, product and process. Also, this chapter puts forward implications for the development of PSS models.

The extension of businesses to incorporate the provision of function as a service in supplement to standalone products is an ongoing movement in manufacturing industry. In short, this means that the development intent should be guided by the need of ‘performance in use’ that the customer wants, e.g. thrust rather than an engine. By this, the established knowledge base challenges the development team. This paper embarks from the assumption that there are three main challenges, i.e. (1) innovation activities, (2) customer data acquisition and (3) the transformation of data into design information. The purpose is to discuss knowledge sharing activities to contribute to product-service innovation. In this study it has been found that contemporary data acquisition activities filter out important dimensions of knowledge. Thus, does not provide a sound base for service provisions.

“Listen closely to your customers, and you are more likely to design products that actually meet or even exceed their needs.”: Such statements have come to dominate company innovation strategies in the last decade, but in reality involving customers in product development is not as straightforward as it sounds. Customers, it is becoming clear, cannot always express their needs adequately. Especially, in the case of innovative products where the starting position by definition includes no existing solution, applying a user-orientated approach is paramount. We argue that techniques for ‘needfinding’ must be the point of departure. This has importance both in terms of methodological issues – how to find customer needs? – and for organizational work – who should be engaged in finding customer needs? In our view, engineers must be involved in identifying and understanding those needs. We have learnt through a series of studies, that structured needfinding by engineers during the earliest phases of product development could better support the process of identifying needs and thereby guide design projects. In this way, two basic problems are overcome. Firstly, identifying needs which are otherwise difficult to articulate becomes possible. Secondly, translation difficulties between customers and engineers are eradicated

In this paper, practical activities of Needfinding - an intertwined approach to identifying needs and to visualizing idea concepts in early design - are described and discussed. This is done primarily to gain an increased understanding of the various representations of user needs that are fed into the fuzzy front-end activities of team-based product innovation projects. The empirical basis comes from a study of an eight-month collaborative product development project, performed under realistic conditions by MSc students in close collaboration with their client. Focusing closely on customers and their needs is encouraged within the conceptual framework of Integrated Product Development and is increasingly highlighted as a key enabler in the design of truly innovative products. Despite the fact that identified customer needs are considered as the initial and primary input into such an innovation process, it can be argued that the design teams do not commonly have a sufficient understanding of customer needs and they do not normally interact with customers in their environment. Besides focusing on measurable aspects of user behaviour and requirements, a traditional approach to identifying and managing customer needs usually includes several interpretive stages before being handed over to the design team. In the context of innovative products, the identification and definition of customers and their needs is a non-trivial and difficult exercise. It involves, we suggest, not only Needfinding but also the definition of ‘those who might need the product’, users and customers to co-evolve iteratively in the early phases of design.

Innovations are crucial to companies’ competitive strength. Functional Product Development (FPD) is a base for a Functional Product Innovation vision, aiming for a new way to design, develop and sell physical products. The purpose in this paper is to discuss relations between the development process for these products, called FPD, and a simulation-driven approach to design these products, called SDD. FPD consider a holistic approach in early design phases. A life-cycle perspective, cross-company collaboration and a focus on stakeholder needs are examples of issues which are part of the wider view on product development. The SDD approach puts forward an integration of simulations to provide support for designers in FPD. The goal is to take the knowledge domains of engineering, business and production into account in the design to provide for the ability to sell ‘functions per unit’. The combination of FPD and SDD is paramount. The influence of needs plays a leading part in FPD and the use of simulations could create a virtual structure to combine and recombine resources and thus, nurture innovations.

The notion of functional products changes the existing relationship between manufacturing companies. The integration of hardware, software and services in functional products calls for close collaboration with companies having complementary skills. When employees from different companies are involved, strategic resources such as knowledge are shared. From an engineering design perspective, knowledge sharing supported by software systems are useful, though it seems like functional product development insists on integrating multifunctional skills and this is likely to affect the design of software systems. The objective in this paper is to explore knowledge sharing challenges between manufacturing companies, striving to create close functional product collaboration, and hence understand aspects in the design of software systems. In this paper the focus is on Knowledge Based Engineering (KBE) systems, these are considered to be internal engineering specific tools, while collaboration and need for knowledge sharing calls for coupled KBE systems between partners. In this context, knowledge sharing challenges within the extended enterprise are recognised to issues about who to trust and what and how to share. This affects how tightly coupled KBE systems can be. In general, this paper contributes to the ongoing discussion concerning collaboration issues in concurrent engineering design, but especially to the overall understanding of what new demands on KBE systems that are motivated by functional product collaboration.