Applying an Adapted Data Mining Methodology (DMME) to a Tribological Optimisation Problem

Bitrus, Samuel; Velkavrh, Igor; Rigger, Eugen

doi:10.1007/978-3-658-32182-6_7

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…Since for theoretical calculations of coefficient of friction, information about the contact area is required as well, possible collaborations in this regard will be established to see if the proposed methodology can enable a more accurate match between experiments and theory. In this sense, applying data science and data mining methodologies (Bitrus et al, 2021) will be considered as well.…”

Section: Discussionmentioning

confidence: 99%

A Holistic Approach Towards Surface Topography Analyses for Ice Tribology Applications

et al. 2021

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A surface texture can be subdivided into three categories based on the magnitude of its wavelengths, i.e., macro-geometrical form, waviness, and roughness (from largest to smallest). Together, these components define how a surface will interact with the opposing surface. In most ice tribology studies, <2% of the entire sample surface is topographically analyzed. Although such a small percentage of the entire surface area generally provides statistically relevant information, the missing information about the texture complexity on a larger scale might reduce the possibility of accurately explaining the resulting tribological behavior. The purpose of this study was to review the existing surface measurement methods related to ice tribology and to present a holistic approach towards surface topography measurements for ice tribology applications. With the holistic surface measurement approach, the entire sample surfaces are scanned, and the measured data is analyzed on different magnitude levels. The discussed approach was applied to sandblasted steel samples which were afterward tested on two different ice tribometers. The experimental results showed that additional information about the sample surface topography enabled a better understanding of the ice friction mechanisms and allowed for a more straightforward correlation between the sample surface topography and its ice friction response.

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Section: Discussionmentioning

confidence: 99%

A Holistic Approach Towards Surface Topography Analyses for Ice Tribology Applications

et al. 2021

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“…Therefore, methods have been proposed to extend CRISP-DM for the applicability in engineering (Huber et al, 2019;Rädler and Rigger, 2020;Stanula et al, 2018) by better align with the requirements in the specific domain, e.g. extension of the data understanding to gather knowing about tribological experiments (Bitrus et al, 2020). Similarly, methods to develop support for the engineering design by applying design automation (Rigger, Lutz, et al, 2019;Verhagen et al, 2015) or digital twins (Lu et al, 2020;Miller et al, 2018) are proposed in the literature.…”

Section: Related Workmentioning

confidence: 99%

“…The focus is on the exchange of data between the physical product and the digital twin. (Grieves and Vickers, 2017) To foster the integration of digital engineering in design practice, methods have been proposed in the context of design automation (Curran et al, 2010;Zheng et al, 2012) and data science (Bitrus et al, 2020;Rädler and Rigger, 2020;Wiemer et al, 2019). Design automation studies show that the potential and the opportunities in industry are still not entirely reflected (Rigger and Vosgien, 2018).…”

Section: Introductionmentioning

confidence: 99%

A Survey on the Challenges Hindering the Application of Data Science, Digital Twins and Design Automation in Engineering Practice

Rädler

Rigger²

2022

Proc. Des. Soc.

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Digital Engineering is an emerging trend and aims to support engineering design by integrating computational technologies like design automation, data science, digital twins, and product lifecycle management. To enable alignment of industrial practice with state of the art, an industrial survey is conducted to capture the status and identify obstacles that hinder implementation in the industry. The results show companies struggle with missing know-how and available experts. Future work should elaborate on methods that facilitate the integration of Digital Engineering in design practice.

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Tribo-informatics approaches in tribology research: A review

Yin

Xing²,

et al. 2022

Friction

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Tribology research mainly focuses on the friction, wear, and lubrication between interacting surfaces. With the continuous increase in the industrialization of human society, tribology research objects have become increasingly extensive. Tribology research methods have also gone through the stages of empirical science based on phenomena, theoretical science based on models, and computational science based on simulations. Tribology research has a strong engineering background. Owing to the intense coupling characteristics of tribology, tribological information includes subject information related to mathematics, physics, chemistry, materials, machinery, etc. Constantly emerging data and models are the basis for the development of tribology. The development of information technology has provided new and more efficient methods for generating, collecting, processing, and analyzing tribological data. As a result, the concept of “tribo-informatics (triboinformatics)” has been introduced. In this paper, guided by the framework of tribo-informatics, the application of tribo-informatics methods in tribology is reviewed. This article aims to provide helpful guidance for efficient and scientific tribology research using tribo-informatics approaches.

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Applying an Adapted Data Mining Methodology (DMME) to a Tribological Optimisation Problem

Cited by 5 publications

References 16 publications

A Holistic Approach Towards Surface Topography Analyses for Ice Tribology Applications

A Holistic Approach Towards Surface Topography Analyses for Ice Tribology Applications

A Survey on the Challenges Hindering the Application of Data Science, Digital Twins and Design Automation in Engineering Practice

Tribo-informatics approaches in tribology research: A review

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