Blar i Institutt for vareproduksjon og byggteknikk på forfatter "Martinsen, Kristian"
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Future Manufacturing Systems in Norway – Strategy, Architecture and Framework
Kolla, Sri Sudha Vijay Keshav (Master thesis, 2016-09-29)This study investigates the suitability of Cyber Physical Systems (CPS) in Norwegian manufacturing industries and its implementation. This study explores the research and innovation needs in Norway which will be given as ... -
Generalized approach for multi-response machining process optimization using machine learning and evolutionary algorithms
Ghosh, Tamal; Martinsen, Kristian (Journal article; Peer reviewed, 2019)Contemporary manufacturing processes are substantially complex due to the involvement of a sizable number of correlated process variables. Uncovering the correlations among these variables would be the most demanding task ... -
Geometric Accuracy in Laser- Based Powder Bed Fusion of Polymers: Tolerance optimization by part build orientation
Leirmo, Torbjørn Langedahl (Doctoral theses at NTNU;2022:71, Doctoral thesis, 2022)As Additive Manufacturing (AM) enters the manufacturing industry, the technology must adhere to stringent quality demands in terms of dimensional and geometric accuracy. However, due to substantial differences in how these ... -
Human-Centered Digital Twin Design for Industrial Symbiosis
Chen, Ziyue (Doctoral theses at NTNU;2022:303, Doctoral thesis, 2022)Industrial symbiosis is a pivotal process in realizing the circular economy. Lags and the lack of information-sharing between companies prevents the symbiotic system from working properly. As a potential solution for ... -
Industry 4.0 Closed Loop Tolerance Engineering Maturity Evaluation
Martinsen, Kristian (Chapter, 2019)Closed Loop Tolerance Engineering (CLTE) is introduced as a model of information flow – feed forward and feedback- between functional requirements, tolerance selection, process capabilities and product performance. “Industry ... -
Integration of digital learning in industry 4.0
Tvenge, Nina; Martinsen, Kristian (Journal article; Peer reviewed, 2018)The emerging advances in sensor systems, automation and Information and Communication Technology (ICT) for manufacturing opens new possibilities for lifelong learning utilizing data from production. The data can be source ... -
Joining of dissimilar materials
Martinsen, Kristian; Hu, SJ; Carlson, B.E. (Journal article; Peer reviewed, 2015)Emerging trends in manufacturing such as light weighting, increased performance and functionality increases the use of multi-material, hybrid structures and thus the need for joining of dissimilar materials. The properties ... -
A Learning Approach for Future Competencies in Manufacturing using a Learning Factory
Dahl, Håkon; Tvenge, Nina; Assuad, Carla Susana A; Martinsen, Kristian (Peer reviewed; Journal article, 2023)This paper describes a study on future competence needs in manufacturing and how a learning factory utilising a Connective Model for Didactic Design can be used in teaching and learning of these competencies. The paper ... -
Learning factories as laboratories for socio-technical experiments
Tvenge, Nina; Martinsen, Kristian; Holtskog, Halvor (Journal article; Peer reviewed, 2019)Production systems might be viewed as complex socio-technical systems. A central part of socio-technical systems theory, is that improvements demands joint optimization of both the technological and the social parts of the ... -
Machine Learning Based Heuristic Technique for Multi-response Machining Process
Ghosh, Tamal; Martinsen, Kristian (Peer reviewed; Journal article, 2020)Manufacturing process variables influence the quality of products substantially. It is unquestionably difficult to model the manufacturing processes that include a large number of variables and responses. Development of ... -
Machine Learning of Quality Assurance in Polymer Powder Bed Fusion Additive Manufacturing
Baturynska, Ivanna (Doctoral theses at NTNU;2020:120, Doctoral thesis, 2020)The latest developments in the field of additive manufacturing (AM) have led to the wider use of this technology for the production of end-user products. As a result, more stringent requirements are set to the quality of ... -
Measurement systems to support continues improvements in manufacturing teams
Sagbakken, Terje (Master thesis, 2016-09-29) -
Mechanical performance of thermoplastic elastomers for two-component injection moulding
Persson, Anna-Maria Märta Ruth (Doctoral theses at NTNU, 2022:350, Doctoral thesis, 2022)The thesis is based on studies of the mechanical properties of thermoplastic elastomers (TPEs). A TPE is a soft thermoplastic polymer material with rubber-like properties. Vulcanizate TPEs (TPVs) were selected as the main ... -
Monitoring and Control for Thermoplastics Injection Molding A Review
Ogorodnyk, Olga; Martinsen, Kristian (Journal article; Peer reviewed, 2018)Thermoplastics injection molding has found increasing use in several industry sectors. To achieve high effectivity of the process and desirable quality of the manufactured product, correct and precise parameters setting ... -
A New Fault Identification Method Based on Combined Reconstruction Contribution Plot and Structured Residual
Chen, Bo; Wang, Kesheng; Gao, Xiue; Wang, Yi; Chen, Shifeng; Zhang, Tianshu; Martinsen, Kristian; Ghosh, Tamal (Chapter, 2020)The existing contribution plot-based reconstruction fault identification methods suffer from low identification accuracy and serious trailing effect. In this paper, a new fault identification method is proposed based on a ... -
NSGA III for CNC End Milling Process Optimization
Ghosh, Tamal; Martinsen, Kristian (Peer reviewed; Journal article, 2020)Computer Numerical Controlled (CNC) end milling processes require very complex and expensive experimentations or simulations to measure the overall performance due to the involvement of many process parameters. Such problems ... -
Optimization of Process Parameters for Powder Bed Fusion Additive Manufacturing by Combination of Machine Learning and Finite Element Method: A Conceptual Framework
Baturynska, Ivanna; Semeniuta, Oleksandr; Martinsen, Kristian (Journal article; Peer reviewed, 2018)In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product. ... -
Prediction of geometry deviations in additive manufactured parts: comparison of linear regression with machine learning algorithms
Baturynska, Ivanna; Martinsen, Kristian (Peer reviewed; Journal article, 2020)Dimensional accuracy in additive manufacturing (AM) is still an issue compared with the tolerances for injection molding. In order to make AM suitable for the medical, aerospace, and automotive industries, geometry variations ... -
Prediction of Width and Thickness of Injection Molded Parts Using Machine Learning Methods
Ogorodnyk, Olga; Lyngstad, Ole Vidar; Larsen, Mats; Martinsen, Kristian (Chapter, 2021)Injection molding is one of the major processes applied for production of thermoplastic products. Thermoplastic materials are used in manufacturing of dozens of products seen in everyday life, such as: car bumpers, children ... -
Proposed framework for flexible de- and remanufacturing systems using cyber-physical systems, additive manufacturing, and digital twins
Assuad, Carla Susana Aqudelo; Leirmo, Torbjørn Langedahl; Martinsen, Kristian (Peer reviewed; Journal article, 2022)Under the circular economy paradigm, de- and remanufacturing systems are more relevant than ever. However, such systems present specific challenges related to the system structure, automation, and recovery of complex ...