| 1. |
- Aeddula, Omsri, 1993-
(author)
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Navigating Data Challenges: AI-Driven Decision Support for Product-Service System Development
- 2024
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Doctoral thesis (other academic/artistic)abstract
- Solution providers are transitioning from product-centric models to service-oriented solutions. This shift has led to the rise of Product-Service Systems (PSS), which offer a holistic approach by integrating physical products with associated services. However, the inherent complexity and collaborative nature of PSS development present a significant challenge: information gathering, analysis, and knowledge building. This is further amplified in the early stages of PSS development due to data challenges such as uncertainty, ambiguity, and complexity. This complicates informed decision-making, potentially leading to the risk of sub-optimal outcomes and impacting the success of final offerings.This research proposes an AI-powered data analysis approach to address these data challenges and augment the decision-making process of PSS development. The focus is on supporting early-stage decision-making, as decisions made at this stage greatly impact the success of final solutions. The research investigates how data can be utilized and visualized to extract actionable insights, ultimately facilitating informed decision-making.The presented research demonstrates that AI-powered data analysis effectively supports informed decision-making in early-stage PSS development. By extracting actionable insights from complex data, handling data limitations, and enabling informed strategic decisions, knowledge sharing, and collaboration are facilitated among stakeholders. Furthermore, integrating AI with visualization tools fosters knowledge building and a deeper understanding of system behavior, ultimately leading to more successful PSS solutions. The efficacy of AI-powered data analysis for handling diverse data types across application domains is demonstrated, potentially leading to benefits such as a deeper understanding of system behavior and proactive solution strategies. These advancements contribute to developing decision support systems specifically for PSS development.Overall, this research demonstrates the efficacy of AI-powered data analysis in overcoming data challenges and empowering decision-makers in early-stage PSS development. This translates to more informed choices, leading to the creation of successful and efficient PSS solutions.
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| 2. |
- Paulson, Fredrik, 1976-
(author)
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Inclusion of sustainability aspects in product development at manufacturing companies
- 2018
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Licentiate thesis (other academic/artistic)abstract
- Due to current consumption and production patterns of products, pressure on already constrained natural resources, an increasing global population, increasing concentrations of greenhouse gases in the atmosphere and reduced access to clean water globally, studying manufacturing companies’ inclusion of sustainability aspects in their product development becomes important.The aim of this thesis is to expand current knowledge on the inclusion of sustainability aspects in product development at manufacturing companies. More specifically, the expansion of current knowledge covers how manufacturing companies include sustainability aspects in product development, the challenges manufacturing companies may face when including sustainability aspects in product development, and the reasons for these challenges.To fulfil this aim, a literature study and a multiple case study were conducted at two international, listed, manufacturing companies in Sweden. Empirical data was collected using semi-structured interviews with two employees at each company and by analyzing the companies’ latest sustainability report.Empirical results include two context-dependent descriptions of how manufacturing companies include sustainability aspects in product development, 21 challenges the companies face, and 14 reasons for those challenges.Conclusions include: (1) the role of conventional methods when including sustainability aspects in product development has been largely ignored in prior research; (2) a company’s product owner influences the inclusion of sustainability aspects in product development, and in product requirements in particular; (3) the following three challenges are proposed incorporated in a comprehensive framework of challenges that has been developed in prior research:Making suppliers fulfil the sustainability requirements that are placed on them. Transforming sustainability aspects, or general goals, into measurable requirements that contribute to reduced environmental impact from products while at the same time contributing to competitive profit.Identifying how to reach economic goals more efficiently with a more sustainable initiative or solution than other initiatives.
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| 3. |
- Aeddula, Omsri, 1993-, et al.
(author)
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AI-driven Ossification Assessment in Knee MRI : A Product-Service System Development for Informed Clinical Decision-Making
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Other publication (other academic/artistic)abstract
- 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.
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| 4. |
- Chowdhery, Syed Azad, 1985-
(author)
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A data-driven approach for Product-Service Systems design : Using data and simulation to understand the value of a new design concept
- 2020
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Licentiate thesis (other academic/artistic)abstract
- Global challenges such as increasingly competitive markets, low-cost competition, shorter lead time demands, and high quality/value output are transforming the business model of the company to focus beyond the performance requirements. In order to meet these challenges, companies are highly concerned with the customer perceived value, which is to connect the product with the customer in a better way and become more proactive to fulfil the customer needs, via function-oriented business models and Product-Service Systems.In literature, the conceptual phase is distinguished as the most critical phase of the product development process. Many authors have recognized the improvement of design in the conceptual phase as the mean to deliver a successful product in the market. At the decision gate, where concepts are selected for further development, the design team needs knowledge/data about the long-term consequences of their early decision, to see how changes in design propagate to the entire lifecycle of the product.The main goal of the thesis is to describe how the design of Product-Service Systems in the conceptual phase can be improved through the use of a data-driven approach. The latter provides an opportunity to enhance decision making and to provide better support at the early development phase. The study highlights how data are managed and used in current industrial setting and indicates the room for improvement with current practices. The thesis further provides guidelines to efficiently use data into the modelling and simulation activities to increase design knowledge. As a result of this study, a data-driven approach emerged to support the early design decision. The thesis presents initial descriptive study findings from the empirical investigations, showing a model-based approach that creates awareness about the value of a new design concept, thus acting as a key enabler to use data in design. This will create a link between the product engineering characteristic to the high-level attributes of customer satisfaction and provider’s long-term profitability. The preliminary results indicate that the application of simulation models to frontload the early design stage creates awareness about how performance can lead to value creation, helping multidisciplinary teams to perform quick trade-off and what-if analysis on design configurations. The proposed framework shows how data from various sources are used through a chain of simulations to understand the entire product lifecycle. The proposed approach holds a potential to improve the key performance indicators for Product-Service Systems development: lead time, design quality, cost and most importantly deliver a value-added product to the customer.
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| 5. |
- Eivazzadeh, Shahryar, 1975-
(author)
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Evaluating Success Factors of Health Information Systems
- 2019
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Doctoral thesis (other academic/artistic)abstract
- Health information systems are our technological response to the growing demand for health care. However, their success in their mission can be challenging due to the complexity of evaluating technological interventions in health care. In the series of studies compiled in this dissertation, we looked at the evaluation of these systems. We focused on the evaluation of factors that lead to success, where success is indicated by user satisfaction and can be induced by both intervention-specific and individual-specific factors.Study 1 developed a method, called UVON, to elicit and organise the user-demanded qualities in the outcomes of the health information system intervention. Through the application of the UVON method in the FI-STAR project, an EU project which developed and deployed seven e-health applications in seven member countries, ten categories of quality and their subcategories were identified. These qualities formed two questionnaires, specific to the patient and health professional users. Through the questionnaires, the patients and health-professionals users evaluated and graded both the occurrence of those demanded qualities in the project outcomes and their general satisfaction.Study 2 analysed the survey results to find out which of those ten qualities have the highest impact on satisfaction or can predict it better. Two partial least squares structural equation modelling (PLS-SEM) models were constructed, for the patient and health professionals, based on the Unified eValuation using ONtology (UVON) and survey outputs. The models showed that effectiveness is an important quality in creating satisfaction for both user groups. Besides, affordability for the health professionals and efficiency plus safety for the patients were the most influential. A satisfaction index is also introduced for simple and fast inferring of the changes in the outcome qualities.Study 5 recruited outputs and learnings from studies 1 and 2 to design a system that partially automates the process of evaluating success factors in health information systems, making it continuous and real-time, and replacing hard-to-run surveys with automatically captured indicators and analytics.Study 3 focused on individual-specific factors in using health information systems, particularly the technophilia personality trait. A short six-items instrument, called TechPH, was designed to measure technophilia in users, tuned for older users. The study recruited empirical data from the Swedish National Study on Aging and Care (SNAC) project. Two factors, labelled techAnxiety and techEnthusiams, are identified by the factor analysis method. A TechPH score was introduced as a scalar measurement of technophilia.Study 4 elicited and discussed the ethical challenges of evaluating and researching health information systems. Both a scoping review and a novel systematic postulation approach were recruited to identify twenty ethical challenges. The identified ethical challenges were discussed and mapped into a three-dimensional space of evaluation stages, demanded qualities, and major involving entities (stakeholder and artefacts), which fosters further postulation of ethical challenges.
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| 6. |
- Elfsberg, Jenny, 1973-
(author)
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Innovation Engineering in Practice : Bridging Exploration and Exploitation in Large Manufacturing Incumbents
- 2023
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Doctoral thesis (other academic/artistic)abstract
- This thesis discusses how large manufacturing incumbent companies potentially can ensure their longevity and future-proof themselves by infusing ambidexterity throughout their organizations. Ambidextrous companies are equipped to achieve success in both current and future business environments, providing valued solutions to customers today and in the future. While these companies often excel at making incremental improvements to existing products, business, and operational models, they lack the skill set necessary for exploring new ways of creating value for customers, and commonly fail to bring promising breakthrough innovations from proven concept to revenue generation. To address these challenges, this thesis proposes a methodology consisting of four foundational principles for strengthening the innovation capacity of large manufacturing incumbents. The term "innovation engineering" is introduced and described to distinctly differentiate exploration-oriented work from exploitation-oriented work and demystify the exploration process and skills. The thesis also presents the concept of "intentional PSS design" as an approach to incorporate future aspirations and current capabilities into an evolutionary design process, connecting current limitations with future anticipated possibilities.The thesis proposes tools for leaders and coaches to support innovation engineering teams in their exploration journeys and bridge the gap between exploration and exploitation. The overall aim of the research is to future-proof large manufacturing incumbents by providing understanding about common challenges and possibilities, a framework for strengthened innovation capacity, incorporating the innovation engineering skills as core competencies, and the innovation engineering process as equally important to and diametrically different from the exploitation process.The research aims to increase awareness and knowledge about innovation engineering and enable infused ambidexterity so that large manufacturing incumbents can find their ways to adapt to a changing environment and reinvention of their ways to meet customer needs. The thesis also proposes ways to bridge between exploration and exploitation to enable a company-wide transition from a product-selling to problem-solving enterprise. By doing so, large manufacturing companies might prolong their lifespan and contribute solving
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| 7. |
- Flyborg, Johan, et al.
(author)
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Results of objective brushing data recorded from a powered toothbrush used by elderly individuals with mild cognitive impairment related to values for oral health
- 2024
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In: Clinical Oral Investigations. - : Springer Nature. - 1432-6981 .- 1436-3771. ; 28:1
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Journal article (peer-reviewed)abstract
- Objectives: The study aimed to investigate how the objective use of a powered toothbrush in frequency and duration affects plaque index, bleeding on probing, and periodontal pocket depth ≥ 4 mm in elderly individuals with MCI. A second aim was to compare the objective results with the participants’ self-estimated brush use.Materials and methods: Objective brush usage data was extracted from the participants’ powered toothbrushes and related to the oral health variables plaque index, bleeding on probing, and periodontal pocket depth ≥ 4 mm. Furthermore, the objective usage data was compared with the participants’ self-reported brush usage reported in a questionnaire at baseline and 6- and 12-month examination.Results: Out of a screened sample of 213 individuals, 170 fulfilled the 12-month visit. The principal findings are that despite the objective values registered for frequency and duration being lower than the recommended and less than the instructed, using powered toothbrushes after instruction and information led to improved values for PI, BOP, and PPD ≥ 4 mm in the group of elderly with MIC.Conclusions: Despite lower brush frequency and duration than the generally recommended, using a powered toothbrush improved oral health. The objective brush data recorded from the powered toothbrush correlates poorly with the self-estimated brush use.Clinical relevance: Using objective brush data can become one of the factors in the collaboration to preserve and improve oral health in older people with mild cognitive impairment. Trial registration: ClinicalTrials.gov Identifier: NCT05941611, retrospectively registered 11/07/2023.
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| 8. |
- Aeddula, Omsri, 1993-, et al.
(author)
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A Solution with Bluetooth Low Energy Technology to Support Oral Healthcare Decisions for improving Oral Hygiene
- 2021
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In: ACM International Conference Proceeding Series. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450389846 ; , s. 134-139
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Conference paper (peer-reviewed)abstract
- 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
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| 9. |
- Aeddula, Omsri, 1993-
(author)
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Data-Driven Decision Support Systems for Product Development - A Data Exploration Study Using Machine Learning
- 2021
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Licentiate thesis (other academic/artistic)abstract
- Modern product development is a complex chain of events and decisions. The ongoing digital transformation of society, increasing demands in innovative solutions puts pressure on organizations to maintain, or increase competitiveness. As a consequence, a major challenge in the product development is the search for information, analysis, and the build of knowledge. This is even more challenging when the design element comprises complex structural hierarchy and limited data generation capabilities. This challenge is even more pronounced in the conceptual stage of product development where information is scarce, vague, and potentially conflicting. The ability to conduct exploration of high-level useful information using a machine learning approach in the conceptual design stage would hence enhance be of importance to support the design decision-makers, where the decisions made at this stage impact the success of overall product development process.The thesis aims to investigate the conceptual stage of product development, proposing methods and tools in order to support the decision-making process by the building of data-driven decision support systems. The study highlights how the data can be utilized and visualized to extract useful information in design exploration studies at the conceptual stage of product development. The ability to build data-driven decision support systems in the early phases facilitates more informed decisions.The thesis presents initial descriptive study findings from the empirical studies, showing the capabilities of the machine learning approaches in extracting useful information, and building data-driven decision support systems. The thesis initially describes how the linear regression model and artificial neural networks extract useful information in design exploration, providing support for the decision-makers to understand the consequences of the design choices through cause-and-effect relationships on a detailed level. Furthermore, the presented approach also provides input to a novel visualization construct intended to enhance comprehensibility within cross-functional design teams. The thesis further studies how the data can be augmented and analyzed to extract the necessary information from an existing design element to support the decision-making process in an oral healthcare context.
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| 10. |
- Barlo, Alexander, M.Sc. Eng. 1994-
(author)
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Failure Prediction of Complex Load Cases in Sheet Metal Forming : Emphasis on Non-Linear Strain Paths, Stretch-Bending and Edge Effects
- 2023
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Licentiate thesis (other academic/artistic)abstract
- With the increased focus on reducing carbon emissions in today’s society, several industries have to overcome new challenges, where especially the automotive industry is under a lot of scrutiny to deliver improved and more environmentally friendly products. To meet the demands from customers and optimize vehicles aerodynamically, new cars often contain complex body geometries, together with advanced materials that are introduced to reduce the total vehicle weight. With the introduction of the complex body components and advanced materials,one area in the automotive industry that has to overcome these challenges is manufacturing engineering, and in particular the departments working with the sheet metal forming process. In this process complex body component geometries can lead to non-linear strain paths and stretch bending load cases, and newly introduced advanced materials can be prone to exhibit behaviour of edge cracks not observed in conventional sheet metals. This thesis takes it onset in the challenges seen in industry today with predicting failure of the three complex load cases: Non-Linear Strain Paths, Stretch-Bending,and Edge Cracks. Through Finite Element simulation attempts are made to accurately predict failure caused by aforementioned load cases in industrial components or experimental setups in an effort to develop post-processing methods that are applicable to all cases.
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