As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Control and supervisory systems have become an important pillar for Automation with the advancement and development of Industry 4.0. These systems are used to reconcile field data with operator analysis, and they are responsible for supporting to the monitoring, analysis, controlling and management of the industrial process. Knowing this, the use of regulations, recommendations and indicators are needed. In this context, Supervisory Control and Data Acquisition (SCADA) systems use factory floor information as an input to alarm management systems in order to control and maintain the plant under operation. The failure event is the consequence of an alarm that has been suppressed or disregarded by the operator, but since the alarm system has been designed in a recommended manner, this occurrence should be displayed and recorded in the event log. Therefore, this record of failures can be analyzed, extracting knowledge of it (quantitative knowledge) and reconciling with the tacit knowledge of the operator (qualitative knowledge) in order to make a better and more clear understanding of the process for an accurate decision making, aiming the reestablishment of the production. However, few systems have the capacity to treat quali-quanti information in parallel and, therefore, the purpose of this paper is to present a model that reconciles such knowledge with a focus on the prioritization of the alarms according to the alarm management regulation ISA SP 18.2. In this context, mining and data analysis tools, and multi-criteria decision making methods are used to elucidate this problematization.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.