✦ LIBER ✦

Sequential monitoring of manufacturing processes: an application of grey forecasting models

✍ Scribed by Li-Lin Ku; Tung-Chen Huang

Publisher: Springer
Year: 2005
Tongue: English
Weight: 185 KB
Volume: 27
Category: Article
ISSN: 0268-3768
DOI: 10.1007/s00170-004-2198-0

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Application of Grey-Markov Model in Fore

Application of Grey-Markov Model in Forecasting Fire Accidents

✍ MAO Zhan-li; SUN Jin-hua 📂 Article 📅 2011 🏛 Elsevier 🌐 English ⚖ 127 KB

Fire accidents are influenced by many complex factors, and it has the characteristic of both randomicity and fluctuation, so a new forecasting model (Grey-Markov model) was established in order to forecast fire accidents effectively in this paper, which has the merits of both GM (1, 1) forecast mode

Rain-fall modeling: An Application of Ba

Rain-fall modeling: An Application of Bayesian forecasting

✍ Migon, Helio S. ;Monteiro, Ana Beatriz S. 📂 Article 📅 1997 🏛 Springer 🌐 English ⚖ 733 KB

Sequential monitoring of low event rates

Sequential monitoring of low event rates: an application in environmental epidemiology

✍ Armand Maul; Jean-Francois Viel 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 203 KB 👁 1 views

A sequential testing procedure for monitoring epidemiological data is considered. The approach is based on a discrete time process of interim analyses using the likelihood ratio as a test statistic. Sampling continues until either some predetermined practical time limit is reached or a decision can

Drug substance manufacture process contr

Drug substance manufacture process control: application of flow injection analysis and HPLC for monitoring an enantiospecific synthesis

✍ K. Chong; T. Loughlin; C. Moeder; H.J. Perpall; R. Thompson; N. Grinberg; G.B. S 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 705 KB

Effective process control can only be achieved through an understanding of the operating issues of the reaction. The development and use of effective and rugged analytical methods is necessary to monitor these parameters. The intent of this paper is to present some key analytical issues encountered

Forecasting Austrian IPOs: An applicatio

Forecasting Austrian IPOs: An application of linear and neural network error-correction models

✍ Christian Haefke; Christian Helmenstein 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 942 KB

In this paper we apply cointegration and Granger-causality analyses to construct linear and neural network error-correction models for an Austrian Initial Public Offerings Index (IPOX,,). We use the significant relationship between the IPOX,, and the Austrian Stock Market Index ATX to forecast the I

Intelligent monitoring and diagnosis of

Intelligent monitoring and diagnosis of manufacturing processes using an integrated approach of KBANN and GA

✍ Jianbo Yu; Lifeng Xi; Xiaojun Zhou 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 938 KB

In many manufacturing processes, some key process parameters (i.e., system inputs) have very strong relationship with the categories (e.g., normal or various faulty products) of finished products (i.e., system outputs). The abnormal changes of these process parameters could result in various categor