A5007527725- Manufacturing Process and Optimization
- Digital Transformation in Industry
- Additive Manufacturing Materials and Processes
- Additive Manufacturing and 3D Printing Technologies
- Advanced Multi-Objective Optimization Algorithms
- Complex Network Analysis Techniques
- Particle accelerators and beam dynamics
- Particle Accelerators and Free-Electron Lasers
- Superconducting Materials and Applications
- Quality Function Deployment in Product Design
- Green IT and Sustainability
- Advanced Machining and Optimization Techniques
- Multi-Criteria Decision Making
- Flexible and Reconfigurable Manufacturing Systems
Tampere University
2019-2023
Tampere University of Applied Sciences
2019
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...
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...
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...
Digital Twin (DT) is an emerging technology that allows manufacturers to simulate and predict states of complex machine systems during operation. This requires the physical state integrated in a virtual entity, instantaneously. However, if entity uses computationally demanding models like physics-based finite element or data driven prediction models, may become asynchronous with its entity. creates increasing lag between twins, reducing effectiveness Therefore, this article, model reduction...
Increased competitiveness in the manufacturing industry demands optimizing performance at each level of an enterprise. Optimizing terms indicators such as cost requires knowledge cost-inducing variables from product design and manufacturing, optimization these variables. However, number that affect is very high all time intensive computationally difficult. Thus, it important to identify optimize select few have potential for inducing cost. Towards goal, a dimension reduction method combining...
Abstract Achieving predictable, reliable, and cost-effective operations in wire arc additive manufacturing is a key concern during production of complex-shaped functional metallic components for demanding applications, such as those found aerospace automotive industries. A metamodel combining localized submodels the different physical phenomena welding can ensure stable material deposition. Such would necessarily combine from multiple domains, materials science, thermomechanical engineering,...
Digital twin technology is the talking point of academia and industry. When defining a digital twin, new modeling paradigms computational methods are needed. Developments in Internet Things advanced simulation techniques have provided strategies for building complex twins. The virtual entity representation physical entity, such as product or process. This collection computationally knowledge models that embeds all information world. To end, this article proposes graph-based entity. provides...
Digital twins (DTs) are fast becoming an important technology in manufacturing companies for predicting failures of critical assets. However, such a digital is hybrid representation with multiple parameters which need to be monitored predict complex phenomena occurring the asset real time. This high-fidelity model twin makes computation output extensive. Therefore, it necessary develop reduction methods that simplify faster acceptable degree error. Such method was proposed previous studies...