{"publication_status":"published","article_number":"e14","doi":"10.1017/s0890060421000408","abstract":[{"text":"The successful planning of future product generations requires reliable insights into the actual products’ problems and potentials for improvement. A valuable source for these insights is the product use phase. In practice, product planners are often forced to work with assumptions and speculations as insights from the use phase are insufficiently identified and documented. A new opportunity to address this problem arises from the ongoing digitalization that enables products to generate and collect data during their utilization. Analyzing these data could enable their manufacturers to generate and exploit insights concerning product performance and user behavior, revealing problems and potentials for improvement. However, research on analyzing use phase data in product planning of manufacturing companies is scarce. Therefore, we conducted an exploratory interview study with decision-makers of eight manufacturing companies. The result of this paper is a detailed description of the potentials and challenges that the interviewees associated with analyzing use phase data in product planning. The potentials explain the intended purpose and generic application examples. The challenges concern the products, the data, the customers, the implementation, and the employees. By gathering the potentials and challenges through expert interviews, our study structures the topic from the perspective of the potential users and shows the needs for future research.","lang":"eng"}],"keyword":["Artificial Intelligence","Industrial and Manufacturing Engineering"],"date_created":"2022-03-02T19:23:18Z","language":[{"iso":"eng"}],"type":"journal_article","date_updated":"2022-10-19T12:29:54Z","publication":"Artificial Intelligence for Engineering Design, Analysis and Manufacturing","status":"public","intvolume":"        36","year":"2022","publisher":"Cambridge University Press (CUP)","author":[{"last_name":"Meyer","id":"77201","full_name":"Meyer, Maurice","first_name":"Maurice","orcid":"0000-0003-0606-7321"},{"full_name":"Fichtler, Timm","id":"66731","last_name":"Fichtler","first_name":"Timm"},{"full_name":"Koldewey, Christian","last_name":"Koldewey","id":"43136","orcid":"https://orcid.org/0000-0001-7992-6399","first_name":"Christian"},{"last_name":"Dumitrescu","id":"16190","full_name":"Dumitrescu, Roman","first_name":"Roman"}],"_id":"30193","title":"Potentials and challenges of analyzing use phase data in product planning of manufacturing companies","department":[{"_id":"563"}],"publication_identifier":{"issn":["0890-0604","1469-1760"]},"volume":36,"user_id":"15782","citation":{"ieee":"M. Meyer, T. Fichtler, C. Koldewey, and R. Dumitrescu, “Potentials and challenges of analyzing use phase data in product planning of manufacturing companies,” <i>Artificial Intelligence for Engineering Design, Analysis and Manufacturing</i>, vol. 36, Art. no. e14, 2022, doi: <a href=\"https://doi.org/10.1017/s0890060421000408\">10.1017/s0890060421000408</a>.","ama":"Meyer M, Fichtler T, Koldewey C, Dumitrescu R. Potentials and challenges of analyzing use phase data in product planning of manufacturing companies. <i>Artificial Intelligence for Engineering Design, Analysis and Manufacturing</i>. 2022;36. doi:<a href=\"https://doi.org/10.1017/s0890060421000408\">10.1017/s0890060421000408</a>","mla":"Meyer, Maurice, et al. “Potentials and Challenges of Analyzing Use Phase Data in Product Planning of Manufacturing Companies.” <i>Artificial Intelligence for Engineering Design, Analysis and Manufacturing</i>, vol. 36, e14, Cambridge University Press (CUP), 2022, doi:<a href=\"https://doi.org/10.1017/s0890060421000408\">10.1017/s0890060421000408</a>.","apa":"Meyer, M., Fichtler, T., Koldewey, C., &#38; Dumitrescu, R. (2022). Potentials and challenges of analyzing use phase data in product planning of manufacturing companies. <i>Artificial Intelligence for Engineering Design, Analysis and Manufacturing</i>, <i>36</i>, Article e14. <a href=\"https://doi.org/10.1017/s0890060421000408\">https://doi.org/10.1017/s0890060421000408</a>","bibtex":"@article{Meyer_Fichtler_Koldewey_Dumitrescu_2022, title={Potentials and challenges of analyzing use phase data in product planning of manufacturing companies}, volume={36}, DOI={<a href=\"https://doi.org/10.1017/s0890060421000408\">10.1017/s0890060421000408</a>}, number={e14}, journal={Artificial Intelligence for Engineering Design, Analysis and Manufacturing}, publisher={Cambridge University Press (CUP)}, author={Meyer, Maurice and Fichtler, Timm and Koldewey, Christian and Dumitrescu, Roman}, year={2022} }","short":"M. Meyer, T. Fichtler, C. Koldewey, R. Dumitrescu, Artificial Intelligence for Engineering Design, Analysis and Manufacturing 36 (2022).","chicago":"Meyer, Maurice, Timm Fichtler, Christian Koldewey, and Roman Dumitrescu. “Potentials and Challenges of Analyzing Use Phase Data in Product Planning of Manufacturing Companies.” <i>Artificial Intelligence for Engineering Design, Analysis and Manufacturing</i> 36 (2022). <a href=\"https://doi.org/10.1017/s0890060421000408\">https://doi.org/10.1017/s0890060421000408</a>."}}