Developing Data-Driven QFD: A Systemic Approach to Employing Product Manuals and Customer Reviews
Despite the importance of data analytics, quality function deployment (QFD) development remains both qualitative and expert-driven. Although some studies have been conducted on data-driven QFD, most have relied solely on quantifying customer requirements, neglecting the quantification of engineering...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10849565/ |
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| Summary: | Despite the importance of data analytics, quality function deployment (QFD) development remains both qualitative and expert-driven. Although some studies have been conducted on data-driven QFD, most have relied solely on quantifying customer requirements, neglecting the quantification of engineering characteristics from a data-driven approach. This study aims to develop a new approach to data-driven QFD using customer reviews and product manuals. Through an in-depth investigation of the product manual structure, this study suggests a systematic method for extracting engineering characteristics and interpreting data-driven QFD. The results are expected to provide practical guidelines for the QFD literature as well as product planning practice by suggesting a systematic framework for developing a data-driven approach and holistic approach. Furthermore, this study aims to ensure a more comprehensive understanding of customer needs and engineering capabilities, thereby enhancing the overall effectiveness of QFD in product development. |
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| ISSN: | 2169-3536 |