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Product design is crucial for product success. Many approaches can improve product design quality, such as concurrent engineering and design for X. This study focuses on applying product usage information (PUI) during product development. As emerging technologies become widespread, an enormous amount of product-related information is available in the middle of a product’s life, such as customer reviews, condition monitoring, and maintenance data. In recent years, the literature describes the application of data analytics technologies such as machine learning to promote the integration of PUI during product development. However, as of today, PUI is not efficiently exploited in product development. One of the critical issues to achieve this is identifying and integrating task-relevant PUI fit for purposes of different product development tasks. Nevertheless, preparing task-relevant PUI that fits different product development tasks is often ignored. This study addresses this research gap in preparing task-relevant PUI and rectifies the related shortcomings and challenges. By considering the context in which PUI is utilized, this paper presents a systematic procedure to help identify and specify developers’ information needs and propose relevant PUI fitting the actual information needs of their current product development task. We capitalize on an application scenario to demonstrate the applicability of the proposed approach.
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Stored only when both papers are in the corpus — 7 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.