Developing a data analytics toolbox for data-driven product planning: a review and survey methodology
M. Panzner, S. von Enzberg, R. Dumitrescu, Artificial Intelligence for Engineering Design, Analysis and Manufacturing 38 (2024).
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Journal Article
| Published
| English
Author
Panzner, Melina;
von Enzberg, Sebastian;
Dumitrescu, RomanLibreCat
Abstract
<jats:title>Abstract</jats:title>
<jats:p>The application of data analytics to product usage data has the potential to enhance engineering and decision-making in product planning. To achieve this effectively for cyber-physical systems (CPS), it is necessary to possess specialized expertise in technical products, innovation processes, and data analytics. An understanding of the process from domain knowledge to data analysis is of critical importance for the successful completion of projects, even for those without expertise in these areas. In this paper, we set out the foundation for a toolbox for data analytics, which will enable the creation of domain-specific pipelines for product planning. The toolbox includes a morphological box that covers the necessary pipeline components, based on a thorough analysis of literature and practitioner surveys. This comprehensive overview is unique. The toolbox based on it promises to support and enable domain experts and citizen data scientists, enhancing efficiency in product design, speeding up time to market, and shortening innovation cycles.</jats:p>
Publishing Year
Journal Title
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Volume
38
Article Number
e18
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Cite this
Panzner M, von Enzberg S, Dumitrescu R. Developing a data analytics toolbox for data-driven product planning: a review and survey methodology. Artificial Intelligence for Engineering Design, Analysis and Manufacturing. 2024;38. doi:10.1017/s0890060424000209
Panzner, M., von Enzberg, S., & Dumitrescu, R. (2024). Developing a data analytics toolbox for data-driven product planning: a review and survey methodology. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 38, Article e18. https://doi.org/10.1017/s0890060424000209
@article{Panzner_von Enzberg_Dumitrescu_2024, title={Developing a data analytics toolbox for data-driven product planning: a review and survey methodology}, volume={38}, DOI={10.1017/s0890060424000209}, number={e18}, journal={Artificial Intelligence for Engineering Design, Analysis and Manufacturing}, publisher={Cambridge University Press (CUP)}, author={Panzner, Melina and von Enzberg, Sebastian and Dumitrescu, Roman}, year={2024} }
Panzner, Melina, Sebastian von Enzberg, and Roman Dumitrescu. “Developing a Data Analytics Toolbox for Data-Driven Product Planning: A Review and Survey Methodology.” Artificial Intelligence for Engineering Design, Analysis and Manufacturing 38 (2024). https://doi.org/10.1017/s0890060424000209.
M. Panzner, S. von Enzberg, and R. Dumitrescu, “Developing a data analytics toolbox for data-driven product planning: a review and survey methodology,” Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 38, Art. no. e18, 2024, doi: 10.1017/s0890060424000209.
Panzner, Melina, et al. “Developing a Data Analytics Toolbox for Data-Driven Product Planning: A Review and Survey Methodology.” Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 38, e18, Cambridge University Press (CUP), 2024, doi:10.1017/s0890060424000209.