2016
DOI: 10.1007/978-3-319-54660-5_52
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Identifying PLM Themes, Trends and Clusters Through Ten Years of Scientific Publications

Abstract: Abstract. PLM encompasses a wide array of expertise, from designing green products to digital factories, with perspectives ranging from an IT standpoint to business strategies, encompassing products, processes and services. Hence, identifying the contours of PLM as a science through the themes, trends and clusters of its scientific literature is very challenging. At the same time, being able to portray PLM will benefit the PLM community, including researchers and practitioners, and should help foresee its futu… Show more

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Cited by 5 publications
(8 citation statements)
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“…From their work, it can be concluded, that new topics such as BIM (building information modelling) or IoT (internet of things) are emerging. However, the later study also shows that the major topics mentioned by author keywords remain the same over the past 10 years [3].…”
Section: ! Related Researchmentioning
confidence: 78%
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“…From their work, it can be concluded, that new topics such as BIM (building information modelling) or IoT (internet of things) are emerging. However, the later study also shows that the major topics mentioned by author keywords remain the same over the past 10 years [3].…”
Section: ! Related Researchmentioning
confidence: 78%
“…Furthermore, it is important to better understand the values of PLM capabilities. These were as far as possible aligned with the keywords preferably chosen by other authors [3], but bundled into clusters which are explained in Table 2.…”
Section: Target Historymentioning
confidence: 99%
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“…The visualisation of communities of keywords reveals the structure of the domain better than just the count, degree or similar measures of keywords. In this paper, the PLM communities are revealed by filtering the network of keywords according to the weight of their network edges, rather than by filtering on the keywords' degrees, as done by Nyffenegger et al (2016). Hence, the PLM core cluster was obtained first by filtering data so as to show edges with a weight of 4 or more ( Figure 5), thus revealing the main research areas of PLM.…”
Section: Discussionmentioning
confidence: 99%
“…The keyword normalisation process is as explained in Nyffenegger et al (2016). This process includes steps such as:  American English is chosen over Britain English (e.g., 'modelling' is normalised to 'modeling', 'visualisation' to 'visualization', etc.…”
Section: Extract and Transform The Datamentioning
confidence: 99%