Methoden vergleichen
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| Bayesian Quality Function Deployment× | Quality Function Deployment× | |
|---|---|---|
| Fachgebiet | Versuchsplanung | Versuchsplanung |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | QFD: 1966–1972; Bayesian QFD extensions: 2000s–present | 1966 (Japan); popularised in the West ~1988 |
| Urheber≠ | Yoji Akao (QFD); Bayesian extension developed by multiple researchers including Fung, Tang, and colleagues | Yoji Akao |
| Typ≠ | Probabilistic customer-driven design planning method | Structured quality planning and product design method |
| Wegweisende Quelle≠ | Tang, J., Fung, R. Y. K., Xu, B., & Wang, D. (2002). A new approach to quality function deployment planning with financial consideration. Computers & Operations Research, 29(11), 1447–1463. DOI ↗ | Akao, Y. (Ed.). (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press. ISBN: 978-0915299416 |
| Aliasnamen | Bayesian QFD, Probabilistic QFD, Bayesian House of Quality, Bayesian Voice of the Customer Analysis | QFD, House of Quality, customer-driven engineering, voice of the customer matrix |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | Bayesian Quality Function Deployment (Bayesian QFD) integrates Bayesian probabilistic inference into the classical House of Quality framework to handle uncertainty in customer preference data and relationship matrices. By expressing relationship weights and importance ratings as probability distributions rather than point estimates, it propagates uncertainty through the planning process and yields more defensible engineering prioritization decisions under incomplete or conflicting customer information. | Quality Function Deployment (QFD) is a structured method for translating customer needs — the voice of the customer — into specific technical requirements at every stage of product or service development. Originating in Japan in the 1960s, QFD uses a matrix-based tool called the House of Quality to make customer priorities visible, link them to engineering parameters, expose trade-offs, and maintain focus on what customers actually value throughout the design process. |
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