| 1. |
- Aranda Muñoz, Alvaro, et al.
(författare)
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Co-Designing with AI in Sight
- 2022
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Ingår i: Proceedings of the Design Society. - : Cambridge University Press (CUP). - 2732-527X. ; 2, s. 101-110, s. 101-110
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Tidskriftsartikel (refereegranskat)abstract
- Artificial Intelligence offers a wide variety of capabilities that can potentially address people's needs and desires in their specific contexts. This pilot study presents a collaborative method using a deck of AI cards tested with 58 production, AI, and information science students, and experts from an accessible media agency. The results suggest that, with the support of the method and AI cards, participants can ideate and reach conceptual AI solutions. Such conceptualisations can contribute to a more inclusive integration of AI solutions in society.
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| 2. |
- Aranda Muñoz, Alvaro, et al.
(författare)
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THE KARAKURI CARD DECK: CO-DESIGNING INDUSTRIAL IOT CONCEPTUAL SOLUTIONS
- 2020
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Ingår i: Proceedings of INTERNATIONAL DESIGN CONFERENCE – DESIGN 2020. - : Cambridge University Press (CUP). - 2633-7762. ; 1, s. 807-816
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Konferensbidrag (refereegranskat)abstract
- Novel IoT market solutions and research promise IoT modules that do not require programming or electrical setup, yet shop floor personnel need to face problem solving activities to create technical solutions. This paper introduces the Karakuri card deck and presents a case study composed of four workshop sessions in four manufacturing settings, where shop floor personnel tested the cards as a means of ideating and presenting conceptual IoT solutions in the form of diagrams. The results indicate the validity of the proposed conceptual solutions and suggest prototyping as a next step.
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| 3. |
- Aranda Muñoz, Alvaro, et al.
(författare)
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The Karakuri IoT toolkit : a collaborative solution for ideating and prototyping IoT opportunities
- 2024
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Ingår i: Proceedings of the Design Society. - 2732-527X. ; 4, s. 185-194
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a collaborative solution developed to enable people without prior Internet of Things (IoT) knowledge to ideate, conceptualise, role-play and prototype potential improvements to their work processes and environments. The solution, called the Karakuri IoT toolkit and method, was tested in two workshops with eight production leaders at a Swedish manufacturing company. Outcomes were analysed from the perspectives of materials interaction and instruments of inquiry. Results indicate the solution can help people conceive and prototype improvement ideas at early design stages.
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| 4. |
- Aranda Muñoz, Alvaro, et al.
(författare)
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The Karakuri IoT toolkit : a collaborative solution for ideating and prototyping IoT opportunities
- 2024
-
Ingår i: <em>Proceedings of the Design Society</em>. - : Cambridge University Press. ; 4, s. 185-194
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a collaborative solution developed to enable people without prior Internet of Things (IoT) knowledge to ideate, conceptualise, role-play and prototype potential improvements to their work processes and environments. The solution, called the Karakuri IoT toolkit and method, was tested in two workshops with eight production leaders at a Swedish manufacturing company. Outcomes were analysed from the perspectives of materials interaction and instruments of inquiry. Results indicate the solution can help people conceive and prototype improvement ideas at early design stages.
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| 5. |
- Aranda Muñoz, Alvaro, et al.
(författare)
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TO SUPPORT IOT COLLABORATIVE EXPRESSIVENESS ON THE SHOP FLOOR
- 2021
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Ingår i: Proceedings of the Design Society. - : Cambridge University Press (CUP). - 2732-527X. ; 1, s. 3149-3158
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Tidskriftsartikel (refereegranskat)abstract
- The availability of new research for IoT support and the human-centric perspective of industry 4.0 opens a gap to support operators in unleashing their creativity so they can provide improvements opportunities with IoT technology. This paper presents a case-study carried out in four Swedish manufacturing companies, where four different workshops were facilitated to support operators in the conceptualization of manufacturing improvements with IoT technologies. The empirical material gathered during these workshops has been analyzed in five different reflective sessions and discussed in light of previous research from industry 4.0, operators, and IoT support. Results indicate that operators can collaboratively create conceptual IoT solutions and that expressiveness in communicating their ideas and needs using IoT technology is more relevant than technical aspects and details of their proposed IoT solutions. This technological expressiveness is identified as a necessary skill to be cultivated on the shop floor and can potentially contribute to making a more effective and socially sustainable industrial landscape in the future.
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| 6. |
- Hallmans, Daniel, et al.
(författare)
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Challenges in providing sustainable analytic of system of systems with long life time
- 2021
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Ingår i: 2021 16th International Conference of System of Systems Engineering (SoSE). - 9781665444545 ; , s. 69-74
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Konferensbidrag (refereegranskat)abstract
- Embedded systems are today often self-sufficient systems with limited communication. However, this traditional view of an embedded system is changing rapidly. Embedded systems are nowadays evolving, e.g., an evolution pushed by the increased functional gain introduced with the concept of System of Systems (SoS) that is connecting multiple subsystems to achieve a combined functionality and/or information of a higher value. In such a SoS the subsystems will have to serve a dual purpose in a) the initial purpose that the subsystem was originally designed and deployed for, e.g., control and protection of the physical assets of a critical infrastructure system that could be up and running for 30-40 years, and b) at the same time provide information to a higher-level system for a potential future increase of system functionality as technology matures and/or new opportunities are provided by, e.g., greater analytics capabilities. In this paper, within the context of a “dual purpose use” of a) and b), we bring up three central challenges related to i) information gathering, ii) life-cycle management, and iii) data governance, and we propose directions for solutions to these challenges that need to be evaluated already at design time.
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| 7. |
- Hallmans, D., et al.
(författare)
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Design considerations introducing analytics as a 'dual use' in complex industrial embedded systems
- 2021
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Ingår i: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728129891
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Konferensbidrag (refereegranskat)abstract
- Embedded systems are today often self-sufficient with limited and predefined communication. However, this traditional view of embedded systems is changing through advancements in technologies such as, communication, cloud technologies, and advanced analytics including machine learning. These advancements have increased the benefits of building Systems of Systems (SoS) that can provide a functionality with unique capabilities that none of the included subsystems can accomplish separately. By this gain of functionality the embedded system is evolving towards a 'dual use' purpose11In this paper we define dual usage as a control system having two purposes. In other contexts such as politics, diplomacy and export control, the term 'dual-use' refers to technology that can be used for both peaceful and military aims, e.g., nuclear power technology., The use is dual in the sense that the system still needs to handle its original task, e.g., control and protect of an asset, and it must provide information for creating the SoS. Larger installations, e.g., industry plants, power systems and generation, have in most cases a long expected life-cycle, some up to 30-40 years without significant updates, compared to analytical functions that evolve and change much faster, i.e., requiring new types of data sets from the subsystems, not know at its first deployment. This difference in development cycles calls for new solutions supporting updates related to new requirements inherent in analytical functions. In this paper, within the context of 'dual usage' of systems and subsystems, we analyze the impact on an embedded system, new or legacy, when it is required to provide analytic data with high quality. We compare a reference system, implementing all functions in one CPU core, to three other alternative solutions: a) a multi-core system where we are using a separate core for analytics, b) using a separate analytics CPU and c) analytics functionality located in a separate subsystem. Our conclusion is that the choice of analytics information collection method should to be based on intended usage, along with resulting complexity and cost of updates compared to hardware cost.
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| 8. |
- Luttens, Andreas, et al.
(författare)
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Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses
- 2022
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Ingår i: Journal of the American Chemical Society. - : American Chemical Society (ACS). - 0002-7863 .- 1520-5126. ; 144:7, s. 2905-2920
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Tidskriftsartikel (refereegranskat)abstract
- Drugs targeting SARS-CoV-2 could have saved millions of lives during the COVID-19 pandemic, and it is now crucial to develop inhibitors of coronavirus replication in preparation for future outbreaks. We explored two virtual screening strategies to find inhibitors of the SARS-CoV-2 main protease in ultralarge chemical libraries. First, structure-based docking was used to screen a diverse library of 235 million virtual compounds against the active site. One hundred top-ranked compounds were tested in binding and enzymatic assays. Second, a fragment discovered by crystallographic screening was optimized guided by docking of millions of elaborated molecules and experimental testing of 93 compounds. Three inhibitors were identified in the first library screen, and five of the selected fragment elaborations showed inhibitory effects. Crystal structures of target-inhibitor complexes confirmed docking predictions and guided hit-to-lead optimization, resulting in a noncovalent main protease inhibitor with nanomolar affinity, a promising in vitro pharmacokinetic profile, and broad-spectrum antiviral effect in infected cells.
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| 9. |
- Yamamoto, Yuji, et al.
(författare)
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Practical Aspects of Designing a Human-centred AI System in Manufacturing
- 2024
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Ingår i: Procedia Computer Science. 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023. - : Elsevier B.V.. ; , s. 2626-2638
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Konferensbidrag (refereegranskat)abstract
- An increasing number of manufacturing companies have initiated designing and implementing AI systems in manufacturing, however, with limited success. Within our overarching research objective of establishing a methodology for the development of AI systems in manufacturing with socio-technical system consideration, this paper focuses on the early design phase of the development life cycle and aims to identify factors that are essential in the phase but whose importance has been less addressed in the manufacturing literature. To this aim, a case study was conducted adopting a design science approach. The case company was developing an ML-based anomaly detection system for a casting process. The researcher organised an AI system design workshop where participants from the company used the Human-AI design guidelines created by a leading large software company. The workshop enabled the participants to explore a wide range of design concerns. It, however, caused the confusing experience that they had to deal with too many questions simultaneously without clear guidance. Analysing this negative experience has led to identifying four design issues requiring further attention in the research. An example of these issues is that the interdependency of design decisions on operational procedures, human-machine interfaces, ML models, pre-processing, and input data makes it challenging to design these elements in isolation. The study found that a structured approach to dealing with the identified issues was currently lacking. This paper contributes to the manufacturing research community by addressing key unresolved issues in the research through highlighting practical details of designing AI systems in manufacturing.
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| 10. |
- Yamamoto, Yuji, et al.
(författare)
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Practical Aspects of Designing a Human-centred AI System in Manufacturing
- 2024
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Ingår i: Procedia Computer Science. - : Elsevier B.V.. ; , s. 2626-2638, s. 2626-2638
-
Konferensbidrag (refereegranskat)abstract
- An increasing number of manufacturing companies have initiated designing and implementing AI systems in manufacturing, however, with limited success. Within our overarching research objective of establishing a methodology for the development of AI systems in manufacturing with socio-technical system consideration, this paper focuses on the early design phase of the development life cycle and aims to identify factors that are essential in the phase but whose importance has been less addressed in the manufacturing literature. To this aim, a case study was conducted adopting a design science approach. The case company was developing an ML-based anomaly detection system for a casting process. The researcher organised an AI system design workshop where participants from the company used the Human-AI design guidelines created by a leading large software company. The workshop enabled the participants to explore a wide range of design concerns. It, however, caused the confusing experience that they had to deal with too many questions simultaneously without clear guidance. Analysing this negative experience has led to identifying four design issues requiring further attention in the research. An example of these issues is that the interdependency of design decisions on operational procedures, human-machine interfaces, ML models, pre-processing, and input data makes it challenging to design these elements in isolation. The study found that a structured approach to dealing with the identified issues was currently lacking. This paper contributes to the manufacturing research community by addressing key unresolved issues in the research through highlighting practical details of designing AI systems in manufacturing.
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