Assessment Of Technology And Economic Benefits Of Reciprocating Machine Condition Monitoring And Diagnostic Systems.
Abstract
The ongoing trend toward automation of the oil, gas, and chemical industry has significantly changed the entire industry. Digital control systems utilizing advanced computer technologies are installed to manage integrated production units. Corporate consolidations and globalization movements have forced reductions in operations staff and maintenance personnel. These changes require plant managers to implement more effective and efficient means to maintain or even increase productivity while protecting critical equipment with fewer resources. Rapid development in sensor and computer technology has led to “smart” monitoring and diagnostic systems to effectively evaluate the condition of the critical production equipment continuously in real-time. Condition monitoring systems for rotating (centrifugal and reciprocating) equipment, in particular, have become much more sophisticated in recent years affording users an intelligent means of extending maintenance cycles, increasing performance, and improving plant safety. But, during the evaluation process of the investment decision, it is far easier to calculate the capital cost associated with installing any given system than it is to derive a realistic rate of return analysis. With a variety of proven systems now available, it is up to design and facility engineers to be able to understand and effectively present the clear benefits and advantages that affect the bottom line of the business. This paper describes specific methods to calculate and clarify the costs and benefits of condition-based online diagnostic system’s rotating equipment. It delivers practical ways to estimate results and relate them to economic figures upon which to bases sound investment decisions.
Description
LecturePg. 69-74
Subject
TurbomachinesCollections
Citation
Gaechter, Robert (2002). Assessment Of Technology And Economic Benefits Of Reciprocating Machine Condition Monitoring And Diagnostic Systems.. Texas A&M University. Turbomachinery Laboratories. Available electronically from https : / /hdl .handle .net /1969 .1 /163321.