| 书目名称 | Statistics for Innovation | | 副标题 | Statistical Design o | | 编辑 | Pasquale Erto | | 视频video | | | 图书封面 |  | | 描述 | 4. 1. 1 ImportanceofComputerSimulation The importance of experimenting for quality improvement and innovation of pr- ucts and processes is now very well known: “experimenting” means to implement signi?cant and intentional changes with the aim of obtaining useful information. In particular, the majority of industrial experiments have two goals: • To quantify the dependence of one or more observable response variables on a group of input factors in the design or the manufacturing of a product, in order to forecast the behavior of the system in a reliable way. • To identify the level settings for the inputs (design parameters) that are capable of optimizing the response. The set of rules that govern experiments for technological improvement in a ph- ical set-up are now comprehensively labeled “DoE. ” In recent years, the use of - perimentation in engineering design has received renewed momentum through the utilization of computer experiments (see Sacks et al. 1989, Santner et al. 2003), which has been steadily growing in the last two decades. These experimentsare run on a computer code implementing a simulation model of a physical system of int- est. This enables us to explore the com | | 出版日期 | Book 2009 | | 关键词 | Computer experiments; Design for Innovation; Innovation; Quality engineering; Reliability; Robust design; | | 版次 | 1 | | doi | https://doi.org/10.1007/978-88-470-0815-1 | | isbn_softcover | 978-88-470-0814-4 | | isbn_ebook | 978-88-470-0815-1 | | copyright | Springer-Verlag Milan 2009 |
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发表于 2025-3-21 19:55:31
