Scenic Acoustic & Vibration Engineering Ltd TEL: +44(0)1229 871171
Condition Based Maintenance (CBM)

CBM is the process of monitoring the condition parameters in machinery in order to identify a significant change which is indicative of a developing fault or failure. It is a major component of a predictive maintenance toolbox and forms the foundations for any preventative maintenance management system. The use of CBM allows maintenance to be scheduled, or other actions to be taken to prevent failure, and to mitigate the consequences of failure. Condition monitoring has a unique benefit in that conditions that would shorten the normal lifespan of a machine can be addressed before they develop into a major failure. Early identification of faults help to maintain the optimum life cycle for your machinery. CBM techniques are normally used on rotating and reciprocating equipment such as pumps, electric motors, internal combustion engines, and presses. Stationary plant such as pipes, beams, vessels and structures can be periodically inspected using non-destructive testing techniques such as ultra-sonic crack detection and magnetic dye penetration. Fit for service (FFS) evaluations are also used for stationary plant equipment such as steam boilers, piping and heat exchangers.

Condition Monitoring Technology

The following list includes the main condition monitoring techniques applied in the industrial and transportation sectors:

- Vibration condition monitoring and diagnostics
- Lubricant analysis
- Acoustic emission (shock pulse)
- Infrared thermography
- Ultrasound emission
- Motor Condition Monitoring and Motor current signature analysis (MCSA)
- Reciprocation Testing (engines and reciprocating compressors)

Most CM technologies are standardized by ASTM and ISO

- Rotating and Reciprocating Equipment
- Visual Inspection
- Thermal Imaging
- Oil Analysis
- Ultrasound
- Performance monitoring
- Performance analysis

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The Criticality Index

The Criticality Index is often used to determine the degree of condition monitoring on a given machine taking into account the machines purpose, redundancy (i.e. if the machine fails, is there a standby machine which can take over), cost of repair, downtime impacts, health, safety and environment issues and a number of other key factors. The criticality index puts all machines into one of three categories:

1.Critical machinery - Machines that are vital to the plant or process and without which the plant or process cannot function. Machines in this category include the steam or gas turbines in a power plant, crude oil export pumps on an oil rig or the cracker in an oil refinery. With critical machinery being at the heart of the process it is seen to require full on-line condition monitoring to continually record as much data from the machine as possible regardless of cost and is often specified by the plant insurance. Measurements such as loads, pressures, temperatures, casing vibration and displacement, shaft axial and radial displacement, speed and differential expansion are taken where possible. These values are often fed back into a machinery management software package which is capable of trending the historical data and providing the operators with information such as condition and performance data. This data can be used to predict faults and provide useful diagnosis of developing faults prior to failure.

2.Essential Machinery - Units that are a key part of the process, but if there is a failure, the process still continues. Redundant units (if available) fall into this realm. Testing and control of these units is also essential to maintain alternative plans should Critical Machinery fail.

3.General purpose or balance of plant machines - These are the machines that make up the remainder of the plant and normally monitored using a handheld data collector as mentioned previously to periodically create a picture of the health of the machine.

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Scenic Acoustic & Vibration Engineering Ltd, 41 Clarence Road, Barrow-in-Furness, Cumbria, England, UK. LA14 9RT
Tel: 01229 871171 Mobile 07855 253 458

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