Search for dissertations about: "machine tool dissertation"
Showing result 1 - 5 of 16 swedish dissertations containing the words machine tool dissertation.
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1. Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach
Abstract : Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. READ MORE
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2. Towards enhanced sales and operations planning : Using machine learning for decision support in an engineer-to-order context
Abstract : All companies deal with tactical planning questions and decisions, for example balance demand and supply, to be able to create an acceptable delivery ability without too much inventory or resources/capacities. For that, some companies use Sales and Operations Planning (S&OP) as their tactical planning process. READ MORE
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3. Modelling, Simulation and Optimisation of a Machine Tool
Abstract : To be competitive in today’s global market it is of great importance that product development is done in an effective and efficient way. To enhance functionality, modern products are often so-called mechatronic systems. This puts even higher demands on the product development work due to the complexity of such products. READ MORE
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4. Dynamic Analysis and Modeling of Machine Tool Parts
Abstract : Boring bar vibration during internal turning operations in machine tools is a pronounced problem in the manufacturing industry. Vibration may easily be induced by the workpiece’s material deformation process, due to the bar’s normally slender geometry. READ MORE
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5. Towards Robust and Adaptive Machine Learning : A Fresh Perspective on Evaluation and Adaptation Methodologies in Non-Stationary Environments
Abstract : Machine learning (ML) has become ubiquitous in various disciplines and applications, serving as a powerful tool for developing predictive models to analyze diverse variables of interest. With the advent of the digital era, the proliferation of data has presented numerous opportunities for growth and expansion across various domains. READ MORE