5.3 Failure Analysis

The Sheerness Generating Station, a large power plant, has process and machine health data feeding into the DCS and plant historian database continuously from thousands of field sensing elements. This session is a case study of project at the plant that utilized ‘cloud’ technology to stream data about plant performance and initial equipment failures not yet notified by the Alarm Management System, to technical experts, who analyzed the information and communicated the findings back to the plant for further troubleshooting, validation and correction. The session will describe the data security and connectivity issues, the communication protocols and the benefits observed. If you are considering changes in the collection, analysis, and reporting of your own plant performance and equipment health, this session will be useful.

In this session you will learn about faster identification of defects at all stages of the asset life cycle, and about clearer and more effective mechanisms for preventing equipment defects at each stage in cycle. In addition you will discover how organizations implement better triggering mechanisms for initiating root cause analysis and integrate a business process and information linkages model. You will have a better understanding of different root cause analysis techniques, as well as data inputs and outputs for defect elimination.

The decision making grid (DMG) is a model that classifies maintenance approaches and then help in the selection of the maintenance strategy based on evidence produced from the data collected in Computerised Maintenance Management Systems (CMMS) or Enterprise Resource Planning (ERP)Systems. In this paper we demonstrate three phases for a successful implementation of the DMG model.