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Journal of Intelligent Manufacturing
Erschienen in: Journal of Intelligent Manufacturing 7/2020

07.02.2018

Data-driven customer requirements discernment in the product lifecycle management via intuitionistic fuzzy sets and electroencephalogram

verfasst von: Shanhe Lou, Yixiong Feng, Hao Zheng, Yicong Gao, Jianrong Tan

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 7/2020

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Abstract

Large amount of data are collected through the product lifecycle management, and the benefits of big data analytics permeate the entire manufacturing value chain. However, the existing methods pay little attention to the analysis of customer requirements data in the beginning of life period. Thus, a data-driven approach for customer requirements discernment is proposed in this paper. It not only manages the vagueness in the semantic expression level using the intuitionistic fuzzy sets, but also adopts the electroencephalogram data as endogenous neural indicators to handle the vagueness in the neurocognitive level. An experimental research integrated with the Kano model is developed to record the EEG data which inherently interpret customers’ psychological states. Benefit from the data mining method, the effect of customer requirements on psychological response can be investigated using the EEG data. Taking the data of initial requirement importance, performance realization levels and customers’ psychological states into consideration, three novel adjusting models are established to acquire the comprehensive importance of each requirement. A case study is conducted to illustrate the feasibility of the approach proposed in this paper.
Vorheriger Artikel Hypernetwork-based manufacturing service scheduling for distributed and collaborative manufacturing operations towards smart manufacturing
Nächster Artikel Blockchain-based business process management (BPM) framework for service composition in industry 4.0

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Metadaten
Titel
Data-driven customer requirements discernment in the product lifecycle management via intuitionistic fuzzy sets and electroencephalogram
verfasst von
Shanhe Lou
Yixiong Feng
Hao Zheng
Yicong Gao
Jianrong Tan
Publikationsdatum
07.02.2018
Verlag
Springer US
Erschienen in
Journal of Intelligent Manufacturing / Ausgabe 7/2020
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI
https://doi.org/10.1007/s10845-018-1395-x

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