A5031447417- Manufacturing Process and Optimization
- Design Education and Practice
- Product Development and Customization
- Additive Manufacturing and 3D Printing Technologies
- Additive Manufacturing Materials and Processes
- Systems Engineering Methodologies and Applications
- Technology Assessment and Management
- Software Engineering Techniques and Practices
- Sustainable Supply Chain Management
- Digital Transformation in Industry
- Software Engineering Research
- Creativity in Education and Neuroscience
- Simulation Techniques and Applications
- Advanced Software Engineering Methodologies
- Industrial Vision Systems and Defect Detection
- University-Industry-Government Innovation Models
- BIM and Construction Integration
- Advanced Multi-Objective Optimization Algorithms
- Environmental Impact and Sustainability
- Service and Product Innovation
- Semantic Web and Ontologies
- Process Optimization and Integration
- Materials Engineering and Processing
- Business Process Modeling and Analysis
- AI-based Problem Solving and Planning
Tampere University
2015-2024
Tampere University of Applied Sciences
2018-2023
Naval Postgraduate School
2018
Aalto University
2008-2015
Université de technologie de belfort-montbéliard
2014
University of Helsinki
2007-2011
Tampere University
2003-2009
University of Technology
2006
Instituts Universitaires de Technologie
2003
Abstract This paper presents a roadmap to the application of AI techniques and big data (BD) for different modelling, design, monitoring, manufacturing operation purposes superconducting applications. To help superconductivity researchers, engineers, manufacturers understand viability using BD as future solutions challenges in superconductivity, series short articles are presented outline some potential applications solutions. These futuristic routes their materials/technologies considered...
Additive manufacturing (AM) continues to rise in popularity due its various advantages over traditional processes. AM interests industry, but achieving repeatable production quality remains problematic for many technologies. Thus, modeling different process variables using machine learning can be highly beneficial creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers make informed decisions about their products...
The material extrusion process (MEX), also known as the fused filament fabrication process, has attracted attention in manufacturing industry. A major obstacle to further application of technology is lack mechanical strength due weak interlayer and poor coalescence between adjacent beads. Understanding effect printing parameters on beads a step toward improvement process. In this study, novel two-phase flow numerical simulation approach coupled with heat transfer been applied high-viscosity...
Additive manufacturing (AM) is expanding the capabilities. However, quality of AM produced parts dependent on a number machine, geometry and process parameters. The variability these parameters affects drastically therefore standardized processes harmonized methodologies need to be developed characterize technology for end use applications enable manufacturing. This research proposes composite methodology integrating Taguchi Design Experiments, multi-objective optimization statistical...
This study proposes a methodology for detecting anomalies in the manufacturing industry using self-supervised representation learning approach based on deep generative models. The challenge arises from limited availability of data defective products compared with normal data, leading to degradation performance models owing imbalances. To address this limitation, we propose process that leverages Gramian angular field transform time-series into images, applies StyleGAN image augmentation...
A future circular collider (FCC) with a center-of-mass energy of 100 TeV and circumference around km, or an upgrade the LHC (HE-LHC) to 27 require bending magnets providing 16 T in 50-mm aperture. Several development programs for these magnets, based on Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn technology, are being pursued Europe U.S. In programs, cos-theta, block-type, common-coil, canted-cos-theta explored; first model...
The material extrusion process is one of the most popular additive manufacturing processes. presence porosity in MEX printed parts, which ultimately deteriorates mechanical properties, main drawbacks process. structure related to shape adjacent beads and overlapping during deposition. Due deposition nature process, cannot be entirely removed from parts. Understanding influence parameters on rheological properties crucial improving quality final product. In this study, two-phase-flow...
Today, one of the major challenges in full-vehicle model creation is to get domain models from different experts while detecting any potential inconsistency problem before Integration, Verification, Validation, and Qualification phase. To overcome such challenges, conceptual design phase has been adapted current development process. For that, system engineers start define most relevant architecture by respecting quality time constraints. Next, simulation architects delivered a more formal...
Abstract Functional modeling is an analytical approach to design problems that widely taught in certain academic communities but not often used by practitioners. This can be applied multiple ways formalize the understanding of systems, support synthesis development a new product, or analysis and improvement existing systems incrementally. The type usage depends on objectives are targeted. categorized into two key groups: discovering totally solution, improving one. article proposes use...
Abstract An intelligent manufacturing paradigm requires material systems, and design engineering to be better connected. Surrogate models are used couple product-design choices with process variables hence, connect capture knowledge embed intelligence in the system. Later, optimisation-driven provides ability enhance human cognitive abilities decision-making complex systems. This research proposes a multidisciplinary optimisation problem explore exploit interactions between different...
For effective human–robot collaborative assembly, it is paramount to view both robots and humans as autonomous entities in that they can communicate, undertake different roles, not be bound pre-planned routines task sequences. However, with very few exceptions, most of recent research assumes static pre-defined roles during collaboration centralised architectures devoid runtime communication influence responsibility execution. Furthermore, from an information system standpoint, lack the...
This article presents the dimensional analysis conceptual modeling (DACM) framework, intended as a mechanism for lifecycle systems engineering. DACM is novel computer-aided method originally developed military projects, but it's now available other applications, too. The framework powerful approach specifying, discovering, validating, and reusing building blocks well analyzing system behavior in early development stages. based on combined with causal graphs to represent interactions...
Modeling and simulation for additive manufacturing (AM) is commonly used in industry. Nevertheless, a central issue remaining the integration of different models focusing on objectives targeting levels details. The objective this work to increase prediction capability characteristics performances additively manufactured parts co-design processes. paper contributes field research by integrating part's performance model technology process into single early integrated model. uses dimensional...
Alloy steels are commonly used in many industrial and consumer products to take advantage of their strength, ductility, toughness properties. In addition, machinability weldability performance make alloy suitable for a range manufacturing operations. The advent additive technologies, such as wire arc (WAAM), has enabled welding into complex customized near net-shape products. However, the functional reliability as-built WAAM is often uncertain due lack understanding effects process...
Abstract The quality of requirements is fundamental in engineering projects. Requirements are usually expressed partly or totally a natural language (NL) format and come from different documents. Their qualities difficult to analyze manually, especially when hundreds thousands them have be considered. assistance software tools becoming necessity. In this article, the goal was develop set metrics supported by NL processing (NLP) methods supporting types analysis dependencies between...
Abstract The scope of this research is to characterize and optimize the vibration-assisted ball burnishing additively manufactured 18% Nickel Maraging steel for tooling applications. We evaluate suitability as an alternative method post-process tool steel. To do so, we assessed a single pass post-processing technique enhance surface roughness, micro-hardness, residual stress state. Results show that ultrasonic after age hardening functionalizes surfaces applications creating beneficial...
Abstract Additive manufacturing has been presented as a novel and competitive method to achieve unprecedented part shapes material complexities. Though this holds true in niche markets, the economic viability of additive for large-scale industrial production is still question. Companies often struggle justify their investment due challenges integration such technologies into mainstream production. First, most exhibit relatively low rate when compared with traditional processes. Second, there...
The "hierarchical and linear model of innovation" (HLMI) is often used to describe how innovations are produced. HLMI presents several shortcomings one possible way overcoming them consider from a system perspective. In order achieve this, this article uses Kline Rosenberg's chain-linked (CLM, 1985) as starting point builds up on it, proposing an improvement rendering CLM more coherent with its systemic bases. proposed suggests conceiving innovation systems associations building blocks using...
Key performance indicators (KPIs) are used to monitor and improve manufacturing performance. A plethora of KPIs currently in use, with others continually being developed meet organizational needs. However, obtaining the optimum KPI values at different levels is challenging due complex interactions between decisions, variables, desired targets. Bayesian network characterize interrelationships selected KPIs. For an additive case, it shown that approach enables appropriate value estimation for...