The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The analysis of historical time series data that reflects equipment failures is becoming increasingly important in maintenance policies in manufacturing plant. This paper presents a novel methodology to use auto-regressive moving average (ARMA) model for device down time forecasting based on transformed historical data. The 8 orders moving average method was adopted to obtain mean stationary time...
The analysis of historical time series data that reflects equipment failures is becoming increasingly important in maintenance policies in manufacturing plant. In this paper, we propose a two-level hierarchical modeling framework whose higher level is a model for trend prediction, while whose lower level is a model for residual prediction. Solving the lower level problem is the main focus of this...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.