Effective Maintenance Management. V. Narayan
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Figure 4.1 Input signal, amplifier, output signal, and feedback loop.
Other control systems follow a similar process, whether the unit in question is a battle tank gun control or a chemical-process control system. Figure 4.1 shows a model illustrating the control mechanism.
Would it not be wonderful to have life without failure? The fewer the failures, the higher the reliability we can enjoy. A good designer tries hard to make the product or service as reliable as possible, within given economic and technical constraints.
A marble rolling along a smooth glass surface may roll on for a long time. However, controlling its movement can be difficult. Similarly, an astronaut doing a space-walk faces a handicap. In the absence of friction or gravity, it is very difficult to navigate, because the only way to do so is to use reaction forces, applying the principle of conservation of momentum. Thus a lack of resistance or opposition may make the process energy-efficient,but control is more difficult. One could extend this approach to explain why democracies are superior to dictatorships, or why market forces are better than price controls. Seen in this context, failures can be useful, as they help identify deviations from expected performance and, hence, the scope for improvement.
Failures are deviations that we can measure, and provide the means to control a process. Resnikoff1 identified the significance of failures when he presented his well-known conundrum. This is the fact that we require information about critical failures to identify the correct maintenance work, the purpose of which is to avoid the same failures. Hence, with perfect maintenance, such critical failures will never take place, so we can never collect the relevant data! The inability to collect the data required for this purpose can stymie any organization attempting to go along the path of continuous improvement.
4.5 CAPABILITY AND EXPECTATION
Every component, equipment, or system has an intrinsic design capability. The bold line in Figure 4.2 shows this graphically.
The demand or expected value may be below this level, shown by the dashed line in Figure 4.2. In this case there should be no problem meeting the demand. However the expectation may be higher than the design capability, as shown by the dotted line in Figure 4.3. In this case, we cannot achieve the expected values on a long-term basis. No amount of maintenance can increase the capability of the equipment to produce continuously above the intrinsic design levels.
Figure 4.2 Normal relationship of demand to capability.
Designers tend to build in some ‘fat,’ stating a level of capability lower than the real value. This is partly due to the use of standard components, some of which are stronger than required, and partly due to built-in safety factors. When we exploit this ‘fat,’ there is a temptation to think that we are able to exceed the design values continuously. The reality is that this capability was always there, but the designers informed us differently.
Figure 4.3 Demand exceeds capability.
Over time, the capability line will droop, due to fouling, wear, fatigue, or chemical attack. When this happens, some maintenance has to be done, to bring the capability up to the design level, as shown in Figure 4.4.
The demand profile may be flat, or as is more common, fluctuating, with peaks and troughs. We cannot meet the expected demand when the two lines intersect, so we need to do some maintenance at this time. Alternatively, we can do the maintenance in anticipation of this situation, as illustrated in Figure 4.5.
Figure 4.4 Maintenance to restore capability.
Figure 4.5 Effect of demand fluctuations on maintenance timing.
The capability line will also exhibit some roughness. Thus, there will be a spread or distribution of values in the case of both the capability line and the demand line. These can be shown as bands of values as shown in Figure 4.6 and its inset. Normally, with smooth demand and capability lines, there is a single point of failure, shown by point B in the inset. With both curves having a band of values, the earliest point of intersection is point A and the latest point C. There is, therefore, a range of points of functional failure. This leads to uncertainty in determining it and the lowest value will normally be chosen, so that we are on the ‘safe side.’
We mentioned incipiency briefly in section 4.1.5. Here we will examine the physical process in greater detail.
At the level of the smallest replaceable component, we will deal with items such as light bulbs, ball bearings, or structural welds. Failure initiation is usually by fatigue or deformation caused by thermal or mechanical stress, or by chemical attack.
Figure 4.6 Effect of fluctuations in demandand capability on the timing of maintenance.
The rate of progression of the failure mechanism is variable, in some cases rapid, in others quite slow. Let us examine one or two common situations where we can observe the progress of the failure.
The first example is of a road that has a small surface defect or unevenness caused by poor finishing. As vehicles pass over this unevenness, the tires enter the depression and then climb up to the original level. This causes an impact load on the road as well as on the vehicle suspension. The effect of this impact on the road is to damage it further, causing a deeper depression. The next truck gets a bigger bump, and causes even more damage to the road. If we do not carry out repairs, the depression eventually becomes a pothole, making it unsafe to drive on this section of the road.