Lesson Notes By Weeks and Term v5 - Grade 12

Lesson Video

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Performance objectives

• Explain predictive maintenance and compare it to other types.
• Describe techniques like vibration analysis, oil analysis, and thermography.
• Interpret basic vibration analysis data.
• Outline the pros and cons of a predictive maintenance program.
• Perform a basic cost-benefit analysis.

Lesson summary

This week, we delve deeper into the crucial world of industrial machines and the strategies we use to keep them running smoothly. Imagine the manufacturing plants in Gauteng, the mines in Limpopo, or the food processing factories across the Western Cape – all rely on complex machinery. When these machines break down, production grinds to a halt, leading to financial losses, job insecurity, and potential disruptions in the supply of essential goods. Effective maintenance is not just a technical skill; it's vital for the South African economy and the well-being of our communities.

Lesson notes

This week’s focus is on Predictive Maintenance. Let's compare it with other types of maintenance: Reactive Maintenance (Run-to-Failure): This is the most basic approach. You only fix the machine after it breaks down. It's cheap in the short term but can lead to costly downtime and potential safety hazards. Think of a kombi taxi only being serviced when it is completely broken down on the side of the road – inconvenient, expensive, and potentially dangerous.

Preventative Maintenance (Time-Based): This involves performing maintenance at regular intervals, regardless of the machine's actual condition. This is better than reactive maintenance but can lead to unnecessary work if a machine is still in good condition. An example is a car being serviced every 10,000km, whether it needs it or not.

Predictive Maintenance (Condition-Based): This uses data and analysis to predict when a machine is likely to fail. Maintenance is then performed just before the failure occurs, minimizing downtime and unnecessary work. It's like a doctor using tests to diagnose a potential illness before symptoms appear. This is the most sophisticated approach.

Predictive Maintenance Techniques: Let’s explore some common techniques: Vibration Analysis: How it works: Sensors (accelerometers) are attached to machines to measure vibration levels. Changes in vibration frequency and amplitude can indicate specific faults, such as imbalance, misalignment, bearing wear, or looseness.

Explanation: Every machine vibrates. A healthy machine vibrates in a characteristic pattern. When something is wrong, that pattern changes. Vibration analysis looks for these changes. The amplitude of the vibration tells you how severe the problem is, and the frequency tells you what the problem is. For example, high-frequency vibration could indicate bearing damage, while low-frequency vibration might indicate imbalance.

Example: Imagine a ceiling fan that starts to wobble excessively. Vibration analysis can pinpoint whether the wobble is due to an unbalanced blade or a loose motor mount.

Oil Analysis: How it works: Oil samples are taken from machines and analyzed for contaminants (e.g., metal particles, water), viscosity, and acidity. High levels of metal particles indicate wear, while changes in viscosity and acidity can indicate oil degradation.

Explanation: Oil acts as a lubricant and coolant in many machines. As parts wear, tiny metal particles are released into the oil. By analyzing these particles, we can determine which parts are wearing and how quickly.

Example: In a mining truck, oil analysis can detect early signs of engine wear, allowing mechanics to schedule repairs before a catastrophic engine failure occurs. Think about the cost saving of preventing a breakdown in a huge mining truck versus reacting after it is too late.

Thermography (Infrared Thermography): How it works: An infrared camera is used to measure the temperature of machine components. Hotspots can indicate problems such as friction, electrical faults, or insulation breakdown.

Explanation: Heat is a byproduct of friction and electrical resistance. By measuring the temperature of different parts of a machine, we can identify areas where excessive heat is being generated.

Example: Thermography can be used to detect loose electrical connections in a distribution board. A loose connection creates resistance, which generates heat that can be easily seen with an infrared camera. This can prevent electrical fires and equipment damage.

Ultrasonic Testing: How it works: Ultrasonic sensors are used to detect high-frequency sound waves that are inaudible to the human ear. These sounds can indicate leaks, cavitation, or electrical arcing.

Explanation: As fluids or gases flow through small openings or as electrical current jumps across gaps, they generate ultrasonic sounds. Identifying these sounds helps to locate the source of the issue.

Example: Detecting steam leaks in a power plant. Steam leaks are often invisible to the naked eye but generate a distinct ultrasonic sound that can be detected with specialized equipment. Cost-Benefit Analysis

Example: Let's say a machine costs R50,000 to repair after a breakdown. The downtime costs R10,000 per day, and the breakdown takes 3 days to fix. The total cost of a breakdown is therefore R50,000 + (3 * R10,000) = R80,

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0. Implementing a predictive maintenance program costs R20,000 per year and reduces the probability of a breakdown from 20% to 5%. Without predictive maintenance, the expected annual cost of breakdowns is 0.20 * R80,000 = R16,

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0. With predictive maintenance, the expected annual cost of breakdowns is 0.05 * R80,000 = R4,

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0. The savings from predictive maintenance are R16,000 - R4,000 = R12,000 per year. The net benefit of predictive maintenance is R12,000 (savings) - R20,000 (cost) = -R8,

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0. In this scenario, the initial predictive maintenance program is not cost effective.