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  • 1.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Prerequisites that support the fuzzy front end of manufacturing technology development2017In: 24th EurOMA conference EurOMA17, 2017Conference paper (Refereed)
    Abstract [en]

    The overall purpose of this paper is to explore the prerequisites that support the fuzzy front end of manufacturing technology development. An exploratory multiple embedded case study has been conducted at a Swedish manufacturing company in the manufacturing industry. By studying four pilot plants’ organisational structure and way of working, this paper contributes with an increased understanding regarding how the fuzzy front end of manufacturing technology development can be supported. This paper describes how a technology roadmap, the usage of master processes and a supportive organisational structure can support the fuzzy front end of new manufacturing technology development.

  • 2.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Eskilstuna.
    Supporting pre-development of new manufacturing technologies2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    In today’s tough industrial environment, efficient development of new products and new manufacturing solutions is necessary to stay competitive on a global market. Manufacturing companies use substantial money and development resources to develop new products. However, the resources spent on finding and implementing emerging manufacturing technologies are much more limited. This is often the case even though it is well known that a way of competing on a global market is through the introduction of new manufacturing technologies that can improve product quality as well as contribute to reducing manufacturing time, resulting in reduced product price and in the end increased profit.

    When introducing new manufacturing technologies, different challenges arise such as lack of knowledge, involvement of an external equipment supplier, etc. In addition, time-to-volume is critical when introducing new manufacturing technologies in a manufacturing context. To be able to have a fast ramp-up, manufacturing technology needs to be mature enough and at the same time meet all requirements. Efficient introduction of new manufacturing technologies requires that pre-development activities have been performed in advance.

    Previous research in this area highlights a lack of knowledge and solutions regarding pre-development of new manufacturing technologies. Such pre-development is important in order to have a successful introduction, fast time-to-volume and production system development. Based on these challenges, the objective of the research presented in this thesis is to develop support for pre-development of new manufacturing technologies.

    The research is based on literature reviews and three empirical case studies, carried out over a two-year period of time. The first empirical case study was an exploratory case study in the manufacturing industry. The purpose of that research study was to identify critical factors forcing manufacturing companies to improve the development of manufacturing technologies.

    The second study was a longitudinal embedded case study in the manufacturing industry with the purpose of identifying factors that affect evaluation of new manufacturing technologies during new product development. Particular attention was given to the product development process and how it has affected the evaluation of new manufacturing technologies.

    Finally, the third study was a single case study in the manufacturing industry with the purpose of analysing and discussing the assessment of the maturity level of a manufacturing technology.

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  • 3.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering. Eskilstuna.
    The fuzzy front end of manufacturing technology development: Exploring the link between the known and the unknown2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    It is well known that a way of competing on a global market is through the introduction of new manufacturing technologies in the production system that can improve product quality as well as contribute to reducing manufacturing time, reduced product price and in the end increased profits. Manufacturing companies that develop and introduce new manufacturing technologies can differentiate themselves from others and thus achieve increased competitiveness.

    The fuzzy front end of manufacturing technology development is characterized by a high degree of technology uncertainty and challenges due to the lack of access to relevant knowledge, lack of a structured development process, and enough resources that are working with development of new manufacturing technologies.

    In the literature only a few empirical studies that explore the fuzzy front end of manufacturing technology development can be found. Prior research highlights that little is actually known about what should be done in the fuzzy front end of manufacturing technology development projects, and thus more research is needed. Supporting the fuzzy front end of manufacturing technology development is important to facilitate a successful introduction of new manufacturing technologies, fast time-to-volume and long-term production system development.

    Based on the above-mentioned importance of developing new manufacturing technology, the objective of the research presented in this thesis is to explore the fuzzy front end of manufacturing technology development. In order to fulfil the objective, empirical data were collected from five case studies conducted in the manufacturing industry. During the empirical studies four important parts were studied: organising, knowledge development, collaboration and the development process.

    The main findings revealed that development of new manufacturing technology is often conducted in collaboration with external partners and many ad hoc decisions are taken due to lack of a predefined development process for the fuzzy front end of manufacturing technology development. In addition, in the fuzzy front end access to relevant manufacturing knowledge is important and knowledge needs to be developed in order to reduce technology uncertainty.

    In order to support the fuzzy front end of manufacturing technology development projects, a supporting framework has been developed. The proposed framework is an elaboration of results from the research questions addressed and can be used as a guideline to overcome the challenges observed in the fuzzy front end of manufacturing technology development projects. The framework is built on two important dimensions for innovations, degree of technology uncertainty and degree of novelty. The critical factors identified in the analysis are embedded in the proposed framework as central parts in the fuzzy front end of manufacturing technology development.

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  • 4.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Badasjane, Viktoria
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Sauter, Barrett
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Differing Views of the Meaning of Digital Transformation in Manufacturing Industry2022In: Advances in Transdisciplinary Engineering, IOS Press BV , 2022, Vol. 21, p. 331-340Conference paper (Refereed)
    Abstract [en]

    In the literature there is no consensus regarding the meaning of the term digital transformation. Therefore, the purpose of this paper is to explore the differing views of the meaning of digital transformation. A case study has been conducted in collaboration with four Swedish manufacturing companies. The results shows that digital transformation can have different meaning within a company and the main challenge when performing digital transformation is knowledge. This study is the first investigation in a research project focusing on coordination of digital transformation. Therefore, is the underlaying goal to identify how the participating companies in the research project describe digital transformation in comparison with the literature. The research intention is not to define digital transformation rather to explore differing views of digital transformation and highlighting similarities and difference in comparison with the literature reviewed. The findings are practically relevant for manufacturing companies by highlighting differing views of digital transformation and in the creation of a common language within a company. 

  • 5.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Evaluation of Advanced Manufacturing Technology during New Product Development2014In: The 21st EurOMA Conference EurOMA 2014, Palermo, Italy, 2014Conference paper (Refereed)
    Abstract [en]

    The purpose of this paper is to identify factors that affect evaluation of advanced manufacturing technology (AMT) during new product development (NPD). Particular attention is given to the new product development process and how it has affected the acquisition and evaluation process of AMT. An embedded case study has been conducted at a large Swedish manufacturing company, consisting of semi structured interviews, document analysis, and passive observations. This paper identifies seven factors that affect the evaluation of AMT during NPD and which can be classified into three categories: NPD project, AMT acquisition project and the internal organization.

  • 6.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jackson, M.
    Jönköping University.
    The fuzzy front end of manufacturing technology development2019In: International Journal of Manufacturing Technology and Management (IJMTM), ISSN 1368-2148, E-ISSN 1741-5195, Vol. 33, no 5, p. 285-302Article in journal (Refereed)
    Abstract [en]

    The fuzzy front end of product development has been studied extensively in previous research, while the fuzzy front end of manufacturing technology development has been largely neglected despite its importance. Only a few empirical studies that examine the fuzzy front end of manufacturing technology development can be found, which have been primarily carried out in the process industry. Therefore, the overall purpose of this paper is to explore the fuzzy front end of manufacturing technology development. Based on three case studies carried out in the manufacturing industry, the findings of the current research highlight key activities in the fuzzy front end of manufacturing technology development and suggest that the fuzzy front end has four sub-phases with overlapping development activities.

  • 7.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jackson, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    FACTORS AFFECTING DEVELOPMENT OF PRODUCTION TECHNOLOGIES IN A MACHINING ENVIRONMENT2014In: Tools and Methods of Competitive Engineering 2014 TMCE 2014, 2014Conference paper (Refereed)
    Abstract [en]

    The purpose of this paper is to identify critical factors forcing manufacturing companies to improve the development of production technology in a machining environment. The focus in the paper is on industrial challenges within product design and production system development when introducing new products in a machining environment. Particular attention is given to the product development process and the production equipment acquisition process. A single case study is presented, consisting of interviews, observations, document studies and an analysis of a large Swedish manufacturing company. The case study company is characterized by advanced production technology, high mechanization and high automation level. In parallel with the case study a literature review was conducted in order to identify state-of-the-art methods/models for efficient design and product introduction within a production system. The paper identifies a gap in the current way of working within the case company as well as challenges regarding the development of production technology. Based on the study, the need for future research has been identified including the need of developing an improved working support for efficient production technology development when industrializing new products.

  • 8.
    Ahlskog, Mats
    et al.
    Mälardalens högskola, Innovation och produktrealisering.
    Bruch, Jessica
    Mälardalens högskola, Innovation och produktrealisering.
    Jackson, Mats
    Mälardalens högskola, Innovation och produktrealisering.
    Factors affecting development of production technologies in a machining environment2014In: Tools and Methods of Competitive Engineering 2014 TMCE 2014, Tools and Methods of Competitive Engineering (TMCE) , 2014Conference paper (Refereed)
    Abstract [en]

    The purpose of this paper is to identify critical factors forcing manufacturing companies to improve the development of production technology in a machining environment. The focus in the paper is on industrial challenges within product design and production system development when introducing new products in a machining environment. Particular attention is given to the product development process and the production equipment acquisition process. A single case study is presented, consisting of interviews, observations, document studies and an analysis of a large Swedish manufacturing company. The case study company is characterized by advanced production technology, high mechanization and high automation level. In parallel with the case study a literature review was conducted in order to identify state-of-the-art methods/models for efficient design and product introduction within a production system. The paper identifies a gap in the current way of working within the case company as well as challenges regarding the development of production technology. Based on the study, the need for future research has been identified including the need of developing an improved working support for efficient production technology development when industrializing new products.

  • 9.
    Ahlskog, Mats
    et al.
    Mälardalens högskola, Innovation och produktrealisering.
    Bruch, Jessica
    Mälardalens högskola, Innovation och produktrealisering.
    Jackson, Mats
    Mälardalens högskola, Innovation och produktrealisering.
    Joint Development of a Manufacturing Technology: A Longitudinal Case Study within the Manufacturing Industry2015In: 22nd International Annual EurOMA Conference EurOMA15, 2015Conference paper (Refereed)
    Abstract [en]

    In order to compete within the manufacturing industry, there is a need to acquire and develop new manufacturing technologies to differentiate the company from others. Therefore, the purpose of this paper is to analyse factors affecting development of a manufacturing technology in a joint development project with an equipment supplier. A longitudinal case study has been conducted at a Swedish manufacturing company and the collaboration between a manufacturing company and an equipment supplier has been studied. The findings reveal that tacit knowledge and good equipment supplier relationship are highly important factors that facilitate development of a manufacturing technology.

  • 10.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jackson, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Joint Development of a Manufacturing Technology: A Longitudinal Case Study within the Manufacturing Industry2015In: 22nd International Annual EurOMA Conference EurOMA15, 2015Conference paper (Refereed)
    Abstract [en]

    In order to compete within the manufacturing industry, there is a need to acquire and develop new manufacturing technologies to differentiate the company from others. Therefore, the purpose of this paper is to analyse factors affecting development of a manufacturing technology in a joint development project with an equipment supplier. A longitudinal case study has been conducted at a Swedish manufacturing company and the collaboration between a manufacturing company and an equipment supplier has been studied. The findings reveal that tacit knowledge and good equipment supplier relationship are highly important factors that facilitate development of a manufacturing technology.

  • 11.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Sch Innovat Design & Engn, Eskilstuna, Sweden..
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Malardalen Univ, Sch Innovat Design & Engn, Dept Prod Realizat, Eskilstuna, Sweden..
    Jackson, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Malardalen Univ, Sch Innovat Design & Engn, Eskilstuna, Sweden..
    Knowledge integration in manufacturing technology development2017In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786, Vol. 28, no 8, p. 1035-1054Article in journal (Refereed)
    Abstract [en]

    Purpose - The purpose of this paper is to identify and analyze knowledge integration in manufacturing technology development projects required to build competitive advantages. Design/methodology/approach - A longitudinal case study has been conducted at a Swedish manufacturing company by following a manufacturing technology development project in real time during a two-year period. Findings - The results show that three different knowledge integration processes exist when developing unique manufacturing technology: processes for capturing, for joint learning, and for absorb learning. The findings of the current research suggest that the three knowledge integration processes are highly interrelated with each knowledge integration process affecting the other two. Research limitations/implications - The major limitation of the research is primarily associated with the single case, which limits generalizability outside the context that was studied. Practical implications - The findings are particularly relevant to manufacturing engineers working with the development of new manufacturing technologies. By using relevant knowledge integration processes and capabilities required to integrate the knowledge in manufacturing technology development projects, companies can improve design and organize the development of manufacturing technology. Originality/value - Previous research has merely noted that knowledge integration is required in the development of unique manufacturing technology, but without explaining how and in what way. This paper's contribution is the identification and analysis of three knowledge integration processes that contribute to the building of competitive advantages by developing unique manufacturing technology and new knowledge.

  • 12.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jackson, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Managing early manufacturing technology development – phases and key activities2016In: 23rd EurOMA conference EUROMA 2016, 2016Conference paper (Refereed)
    Abstract [en]

    In order to compete within the manufacturing industry, there is a need to acquire and develop new manufacturing technologies to differentiate the company from others. This paper builds on extant operations management and innovation management literature with the focus on how to managing early manufacturing technology development. A multiple case study has been conducted at a Swedish manufacturing company in the automotive industry and our paper proposes a conceptual process for early manufacturing technology development and the key activities therein. The findings are relevant for managers working with long-term development and the paper concludes by discussing implications and research limitations.

  • 13.
    Ahlskog, Mats
    et al.
    Mälardalens högskola, Innovation och produktrealisering.
    Bruch, Jessica
    Mälardalens högskola, Innovation och produktrealisering.
    Jackson, Mats
    Mälardalens högskola, Innovation och produktrealisering.
    Managing early manufacturing technology development phases and key activities2016In: 23rd EurOMA conference EUROMA 2016, International Annual EurOMA Conference, 2016Conference paper (Refereed)
    Abstract [en]

    In order to compete within the manufacturing industry, there is a need to acquire and develop new manufacturing technologies to differentiate the company from others. This paper builds on extant operations management and innovation management literature with the focus on how to managing early manufacturing technology development. A multiple case study has been conducted at a Swedish manufacturing company in the automotive industry and our paper proposes a conceptual process for early manufacturing technology development and the key activities therein. The findings are relevant for managers working with long-term development and the paper concludes by discussing implications and research limitations.

  • 14.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Badasjane, Viktorija
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Sauter, Barrett
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Approaching digital transformation in the manufacturing industry challenges and differing views2023In: International Journal of Manufacturing Research, ISSN 1750-0591, no 4, p. 415-433Article in journal (Refereed)
    Abstract [en]

    In order to support manufacturing companies in their digital transformation, challenges and views of the term 'digital transformation' need to be identified since digital transformation is considered a source of competitive advantages. Therefore, this paper aims to explore the challenges and differing views of digital transformation in the manufacturing industry. A case study was conducted in collaboration with four Swedish manufacturing companies. The results were then mapped into categories of three dimensions (people, process and technology), indicating that digital transformation can have different meanings within a company. We conclude that the term 'digitalisation' is more frequently used in the manufacturing industry than 'digital transformation' and identified challenges relate to lack of best practice for digital transformation, degree of standardisation and therefore affects the workload and limits the possibilities of transferring technical solutions between factories. Our findings are relevant to operations managers and other interested in digital transformation. 

  • 15.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Badasjane, Viktorija
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Sauter, Barrett
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Paradoxes in the Digital Transformation of Production Systems2024In: Advances in Transdisciplinary Engineering, IOS Press BV , 2024, Vol. 52, p. 244-255Conference paper (Refereed)
    Abstract [en]

    Digital transformation of production systems is a challenging task that demands radical responses from existing organizations. During the digital transformation of productions systems tensions occur that need to be managed and the purpose of this paper is to identify paradoxes in the digital transformation of production systems. Paradox theory has been applied as an analytical framework when identifying digital transformation paradoxes and tensions. A case study has been conducted and two manufacturing companies’ digitalization projects have been studied and analyzed in combination with data from workshops around digital transformation. The results were mapped into four types of paradoxes: organizing, performing, belonging, and learning. We conclude that the identified tensions are intertwined, and a major tension is the degree of standardization of technologies (standardization vs customization) and a more agile way of working (learning by doing vs learning before) doing is a trend within the digital transformation of production system. Our findings are relevant to operations managers and others interested in tensions during the digital transformation of production systems.

  • 16.
    Ahlskog, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jackson, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Manufacturing Technology Readiness Assessment2015Conference paper (Other academic)
    Abstract [en]

    The purpose of this paper is to analyze and discuss how the MRL scale can support the assessment of a manufacturing technology’s maturity level. A single case study within the manufacturing industry has been conducted investigating the use of a MRL scale. An assessment of MRL 4 has been studied.

  • 17.
    Ahlskog, Mats
    et al.
    Mälardalens högskola, Innovation och produktrealisering.
    Jackson, Mats
    Mälardalens högskola, Innovation och produktrealisering.
    Bruch, Jessica
    Mälardalens högskola, Innovation och produktrealisering.
    Manufacturing Technology Readiness Assessment2015Conference paper (Other academic)
    Abstract [en]

    The purpose of this paper is to analyze and discuss how the MRL scale can support the assessment of a manufacturing technology’s maturity level. A single case study within the manufacturing industry has been conducted investigating the use of a MRL scale. An assessment of MRL 4 has been studied.

  • 18.
    Andersson, Tim
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. ASSA ABLOY.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Olsson, Tomas
    RISE Research Institutes of Sweden, Västerås, 72212, Sweden.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Sample size prediction for anomaly detection in locks2023In: Procedia CIRP, Elsevier B.V. , 2023, p. 870-874Conference paper (Refereed)
    Abstract [en]

    Artificial intelligence in manufacturing systems is currently most used for quality control and predictive maintenance. In the lock industry, quality control of final assembled cylinder lock is still done by hand, wearing out the operators' wrists and introducing subjectivity which negatively affects reliability. Studies have shown that quality control can be automated using machine-learning to analyse torque measurements from the locks. The resulting performance of the approach depends on the dimensionality and size of the training dataset but unfortunately, the process of gathering data can be expensive so the amount collected data should therefore be minimized with respect to an acceptable performance measure. The dimensionality can be reduced with a method called Principal Component Analysis and the training dataset size can be estimated by repeated testing of the algorithms with smaller datasets of different sizes, which then can be used to extrapolate the expected performance for larger datasets. The purpose of this study is to evaluate the state-of-the-art methods to predict and minimize the needed sample size for commonly used machine-learning algorithms to reach an acceptable anomaly detection accuracy using torque measurements from locks. The results show that the learning curve with the best fit to the training data does not always give the best predictions. Instead, performance depends on the amount of data used to create the curve and the particular machine-learning algorithm used. Overall, the exponential and power-law functions gave the most reliable predictions and the use of principal component analysis greatly reduced the learning effort for the machine-learning algorithms. With torque measurements from 50-150 locks, we predicted a detection accuracy of over 95% while the current method of using the human tactile sense gives only 16% accuracy.

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  • 19.
    Andersson, Tim
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. ASSA ABLOY.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Olsson, Tomas
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Interpretable ML model for quality control of locks using counterfactual explanations2024Conference paper (Refereed)
    Abstract [en]

    This paper presents an interpretable machinelearning model for anomaly detection in door locks using torque data. The model aims to replace the human tactile sense in the quality control process, reducing repetitive tasks and improving reliability. The model achieved an accuracy of 96%, however, to gain social acceptance and operators' trust, interpretability of the model is crucial. The purpose of this study was to evaluate anapproach that can improve interpretability of anomalousclassifications obtained from an anomaly detection model. Weevaluate four instance-based counterfactual explanators, three of which, employ optimization techniques and one uses, a less complex, weighted nearest neighbor approach, which serve as ourbaseline. The former approaches, leverage a latent representation of the data, using a weighted principal component analysis, improving plausibility of the counter factual explanations andreduces computational cost. The explanations are presentedtogether with the 5-50-95th percentile range of the training data, acting as a frame of reference to improve interpretability. All approaches successfully presented valid and plausible counterfactual explanations. However, instance-based approachesemploying optimization techniques yielded explanations withgreater similarity to the observations and was therefore concluded to be preferable despite the higher execution times (4-16s) compared to the baseline approach (0.1s). The findings of this study hold significant value for the lock industry and can potentially be extended to other industrial settings using timeseries data, serving as a valuable point of departure for further research.

    Download full text (pdf)
    fulltext
  • 20.
    Andersson, Tim
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. ASSA ABLOY.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Olsson, Tomas
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE RESEARCH INSTITUTES OF SWEDEN, Sweden.
    Interpretable ML model for quality control of locks using counterfactual explanations2024Conference paper (Refereed)
    Abstract [en]

    This paper presents an interpretable machinelearning model for anomaly detection in door locks using torque data. The model aims to replace the human tactile sense in the quality control process, reducing repetitive tasks and improving reliability. The model achieved an accuracy of 96%, however, to gain social acceptance and operators' trust, interpretability of the model is crucial. The purpose of this study was to evaluate anapproach that can improve interpretability of anomalousclassifications obtained from an anomaly detection model. Weevaluate four instance-based counterfactual explanators, three of which, employ optimization techniques and one uses, a less complex, weighted nearest neighbor approach, which serve as ourbaseline. The former approaches, leverage a latent representation of the data, using a weighted principal component analysis, improving plausibility of the counter factual explanations andreduces computational cost. The explanations are presentedtogether with the 5-50-95th percentile range of the training data, acting as a frame of reference to improve interpretability. All approaches successfully presented valid and plausible counterfactual explanations. However, instance-based approachesemploying optimization techniques yielded explanations withgreater similarity to the observations and was therefore concluded to be preferable despite the higher execution times (4-16s) compared to the baseline approach (0.1s). The findings of this study hold significant value for the lock industry and can potentially be extended to other industrial settings using timeseries data, serving as a valuable point of departure for further research.

    Download full text (pdf)
    fulltext
  • 21.
    Andersson, Tim
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Olsson, Tomas
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Comparison of Machine Learning’s- and Humans’- Ability to Consistently Classify Anomalies in Cylinder Locks2022In: IFIP Advances in Information and Communication Technology: WG 5.7 International Conference on Advances in Production Management Systems, APMS 2022, Springer Science and Business Media Deutschland GmbH , 2022, p. 27-34Conference paper (Refereed)
    Abstract [en]

    Historically, cylinder locks’ quality has been tested manually by human operators after full assembly. The frequency and the characteristics of the testing procedure for these locks wear the operators’ wrists and lead to varying results of the quality control. The consistency in the quality control is an important factor for the expected lifetime of the locks which is why the industry seeks an automated solution. This study evaluates how consistently the operators can classify a collection of locks, using their tactile sense, compared to a more objective approach, using torque measurements and Machine Learning (ML). These locks were deliberately chosen because they are prone to get inconsistent classifications, which means that there is no ground truth of how to classify them. The ML algorithms were therefore evaluated with two different labeling approaches, one based on the results from the operators, using their tactile sense to classify into ‘working’ or ‘faulty’ locks, and a second approach by letting an unsupervised learner create two clusters of the data which were then labeled by an expert using visual inspection of the torque diagrams. The results show that an ML-solution, trained with the second approach, can classify mechanical anomalies, based on torque data, more consistently compared to operators, using their tactile sense. These findings are a crucial milestone for the further development of a fully automated test procedure that has the potential to increase the reliability of the quality control and remove an injury-prone task from the operators.

  • 22.
    Badasjane, Viktoria
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Challenges with coordination of technology development and transfer of Industry 4.0 technologies in IMNs2020In: Advances in Transdisciplinary Engineering, Volume 13, 2020, p. 637-648Conference paper (Refereed)
    Abstract [en]

    Within an international manufacturing network (IMN), one particular factory, called the lead factory is responsible for development of new products, processes and technologies as well as transferring these to the subsidiaries within the IMN. These responsibilities require coordination, which is found difficult even in the best-performing companies due to its complexity. When the responsibility for development of Industry 4.0 technologies are included such as cyber-physical systems and Internet of Things the complexity increases further. Therefore, the aim of this paper is to identify what are the challenges with coordination of technology development and transfer of Industry 4.0 technologies in IMNs. Accordingly, a real-time embedded case study was carried out with six manufacturing companies. One major finding is that development of Industry 4.0 technologies does not fit the current way of organizing technology development at lead factories. Another finding is that several of the identified challenges connected to technology development can be derived from a lack of a long-term strategy ensuring competence for future needs.

  • 23.
    Badasjane, Viktoria
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Enablers for coordination of digital transformation in international manufacturing networks2021In: 28th EurOMA Conference EurOMA, 2021, 2021Conference paper (Refereed)
    Abstract [en]

    The digital transformation of International Manufacturing Networks (IMNs) has been identified as a complex undertaking that requires coordination. However, knowledge about coordination in this context is lacking.  The purpose of this paper is to explore enablers for the coordination of digital transformation in IMNs. To this effect, a case study was conducted with a manufacturing company in the heavy vehicle industry. The most prominent enabler is identified as establishing an organisational structure around the digital transformation that ensures coordination and promotes collaboration across the IMN. Future research could moreover compare enablers across multiple cases.

  • 24.
    Badasjane, Viktoria
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Coordination of Digital Transformation in International Manufacturing Networks—Challenges and Coping Mechanisms from an Organizational Perspective2022In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 4, article id 2204Article in journal (Refereed)
    Abstract [en]

    Coordinating the digital transformation of globally dispersed factories within international manufacturing networks has become a critical issue for competitiveness, yet there has been limited attention paid to this issue in previous research. Therefore, the purpose of this paper is to, from an organizational perspective, explore the challenges in coordinating the digital transformation in an international manufacturing network and the coping mechanisms to overcome those challenges. A case study is conducted in a manufacturing company within the heavy vehicle industry, thus contributing to the limited empirical research covering coordination of digital transformation. The data is analyzed through organizational structure and design theory, and the findings are mapped into four core dimensions: differentiation, integration, centralization, and formalization. The results show 15 challenges and 11 coping mechanisms for coordination of digital transformation in international manufacturing networks, identifying the significance of the coordination uncertainty within the formalization dimension that is particularly exposed to the changes induced by digital transformation. The findings include the need for a coordination-oriented organizational structure that incorporates how and where coordination can be actualized. The research implications contribute with new insights by providing a detailed description of the created organizational structure and, in contrast to previous research, focuses specifically on the coordination aspect of digital transformation in an international manufacturing network. 

  • 25.
    Badasjane, Viktorija
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Sauter, Barrett
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Adapting the organisational structure for coordinating the digital transformation2023In: 30th EurOMA conference, EurOMA23, 2023Conference paper (Refereed)
    Abstract [en]

    Factories within International Manufacturing Networks (IMNs) need coordination to harness globalization’s potential. Simultaneously, adding additional complexity, they seek to coordinate digital transformation across the IMNs, requiring a holistic view encompassing the organizational structure. The purpose of this paper is to identify how manufacturing companies adapt the organizational structures of their IMNs to coordinate digital transformation. Through a multiple case study of four manufacturing companies, the results show new or adapted functional units, roles and interfaces. The findings describe and exemplify global and local functional units, boundary spanner roles, and formal and informal interfaces created for coordinating digital transformation in IMNs.

  • 26.
    Bucaioni, Alessio
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Flammini, Francesco
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Towards Model-Based Performability Evaluation of Production Systems2020In: Work-in-progress at IEEE International Conference on Emerging Technologies and Factory Automation WIP@ETFA, 2020, p. 1085-1088Conference paper (Refereed)
    Abstract [en]

    Future smart factories will be increasingly required to predict expected performance and dependability metrics related to their production processes. Domain-specific metrics include overall equipment effectiveness that measures production system availability/uptime, performance/speed and output quality. In this work-in-progress paper, we take initial steps towards a model-based approach to evaluate production-specific metrics using domain-specific languages, model transformations and stochastic modelling formalism

  • 27.
    Fattouh, Anas
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Chirumalla, Koteshwar
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Behnam, Moris
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hatvani, Leo
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Remote integration of advanced manufacturing technologies into production systems: integration processes, key challenges and mitigation actions2023In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786Article in journal (Refereed)
    Abstract [en]

    The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

    Design/methodology/approach: The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

    Findings: By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

    Practical implications: The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

    Originality/value: The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

  • 28.
    Leberruyer, Nicolas
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Afshar, Sara Zargari
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Enabling an AI-Based Defect Detection Approach to Facilitate Zero Defect Manufacturing2023In: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures / [ed] Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D, 2023, p. 643-649Conference paper (Refereed)
    Abstract [en]

    Artificial Intelligence (AI) has proven effective in assisting manufacturing companies to achieve Zero Defect Manufacturing. However, certain products may have quality characteristics that are challenging to verify in a manufacturing facility. This could be due to several factors, including the product’s complexity, a lack of available data or information, or the need for specialized testing or analysis. Prior research on using AI for challenging quality detection is limited. Therefore, the purpose of this article is to identify the enablers that contributed to the development of an AI-based defect detection approach in an industrial setting. A case study was conducted at a transmission axle assembly factory where an end-of-line defect detection test was being developed with the help of vibration sensors. This study demonstrates that it was possible to rapidly acquire domain expertise by experimenting, which contributed to the identification of important features to characterize defects. A regression model simulating the normal vibration behavior of transmission axles was created and could be used to detect anomalies by evaluating the deviation of new products compared to the model. The approach could be validated by creating an axle with a built-in defect. Five enablers were considered key to this development.

  • 29.
    Leberruyer, Nicolas
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Volvo Construction Equipment, Eskilstuna, Sweden.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Afshar, Sara Zargari
    Volvo Construction Equipment, Eskilstuna, Sweden.
    Toward Zero Defect Manufacturing with the support of Artificial Intelligence—Insights from an industrial application2023In: Computers in industry (Print), ISSN 0166-3615, E-ISSN 1872-6194, Vol. 147, article id 103877Article in journal (Refereed)
    Abstract [en]

    The Zero Defect Manufacturing (ZDM) concept combined with Artificial Intelligence (AI), a key enabling technology, opens up new opportunities for improved quality management and advanced problem-solving. However, there is a lack of applied research in industrial plants that would allow for the widespread deployment of this framework. Thus, the purpose of this article was to apply AI in an industrial application in order to develop application insights and identify the necessary prerequisites for achieving ZDM. A case study was done at a Swedish manufacturing plant to evaluate the implementation of a defect-detection strategy on products prone to misclassification and on an imbalanced data set with very few defects. A semi-supervised learning approach was used to learn which vibration properties differentiate confirmed defects from approved products. This method enabled the calculation of a defect similarity ratio that was used to predict how similar newly manufactured products are to defective products. This study identified four prerequisites and four insights critical for the development of an AI solution supporting ZDM. The key finding demonstrates how well traditional and innovative quality methods complement one another. The results highlight the importance of starting data science projects quickly to ensure data quality and allow a ZDM detection strategy to build knowledge to allow for the development of more proactive strategies, such as the prediction and prevention of defects. 

  • 30.
    Sannö, Anna
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Integrating knowledge for manufacturing technology development2019In: International Journal of Product Development, ISSN 1477-9056, E-ISSN 1741-8178, Vol. 23, p. 65-83Article in journal (Refereed)
    Abstract [en]

    The manufacturing industry of today is constantly challenged with new requirements that have to be fulfilled in order to stay competitive on both the short term and the longer term. These new requirements can trigger the need to develop the technology in production. With technology development come uncertainties which can be reduced by integrating new knowledge in the organisation. The overall purpose of this paper is to explain empirically how knowledge integration can be managed in order to reduce the uncertainty of manufacturing technology development while balancing resources towards the short-term production needs. The findings of the current research highlight collaboration, specialist competence and a systematic approach considering the setting, which needs to be managed when conducting manufacturing technology development during full production.

  • 31.
    Sannö, Anna
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jackson, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Fundin, Anders
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. IPR (Innovation and Product Realisation).
    A co-creating research approach when exploring episodic change for sustainable operations2016Conference paper (Refereed)
    Abstract [en]

    Industry is a key player in the transition to a sustainable society and academia can support this transition by conducting relevant research and transferring knowledge to practice. This paper complements operations management methods by presenting a co-creative approach on two levels; a model on a conceptual level and the operationalisation of this model when supporting a sustainable operations change project. By building on trust and relationships, finding common problems and make funding and resources available, the paper presents how gaps of knowledge can be overcome in the collaborative research work between academia and practice.

  • 32.
    Sauter, Barrett
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Granlund, Anna
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Badasjane, Viktorija
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ahlskog, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bruch, Jessica
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    What Not to Do: VR Implementation Teams and the Barriers That Inhibit Them2024In: Advances in Transdisciplinary Engineering, IOS Press BV , 2024, Vol. 52, p. 453-463Conference paper (Refereed)
    Abstract [en]

    Implementation of VR into NPD processes requires a coordinated effort from within the manufacturing organization. However, the knowledge to carry this out successfully is still quite limited within research as well as within manufacturing organizations, leading to failed pilot projects and a waste of resources. Therefore, the purpose of this paper is to identify barriers that inhibit VR implementation. A multiple case study has been carried out focusing on two VR implementation attempts within a single manufacturing site. The results identify four specific roles and their responsibilities within the VR implementation teams: Key driver, gatekeeper, key user, and general user. The results further identify the barriers experienced within the VR implementation attempts.

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