Intro Energy transition and climate neutrality

Before we get to the topic of “towards condition-based maintenance”, here is a higher-level digression. Namely, discussions about climate neutrality have reached a new evolutionary stage. This means that nations are actually addressing it extensively politically. Whereby it is also clear that the competence of political intentions is not reflected in the feasibility of time and technology. However, and this encourages me in this discussion, companies are extremely technologically involved in change. Not to show their charity, of course, but to develop growth-oriented and profitable business models from it. Be it decentralised and renewable energies, e-mobility or the complex issues of a smart grid.

The motivation of towards condition-based maintenance

One thing is certain about all climate neutrality projects: we need a lot more electrical energy. This means that in addition to the many known decentralised generators, other types and systems will also be added to a) ensure security of supply and b) protect against a blackout. For both, for example, the VDE ETG ITG technical committee is currently discussing modern and flexible cellular energy systems.

But the focus is not only on the supply of more energy, but also on the reduction of existing consumption. All this in order to improve the CO2 footprint. ISO50001 helps to achieve this, and in Germany, among other countries, it formally calls for energy saving with subsidies. And this is precisely where the topic of “towards condition-based maintenance” comes in. Incidentally, it could also be called “future-oriented maintenance”. You can read why here.

Why maintenance at all?

Here I briefly explain why maintenance makes sense at all. Of course, I make no claim to completeness, as with all the other paragraphs.

  • To guarantee production reliability and avoid breakdowns as far as possible
  • Extend the service life of the equipment
  • Improve cycle times and thus efficiency
  • Ensure the quality of products
  • Not to impair downstream components
  • etc.

Some key basic problems in maintenance

Already with predictive maintenance, the topic begins to struggle with itself. Namely with the aspect of “looking ahead”. It is often the case that you cannot see inside a system or a machine. Unless the hydraulic oil is already dripping onto the floor. As Mr Pirmin Cavelti of Gubser Service put it: “You can’t really see inside. And just from holding your hand on it, like a glass ball, it doesn’t necessarily get better.”

And why the idea of towards condition-based maintenance?

Manufacturing companies in particular can sing a song especially well: Shortage of skilled workers. Finding suitable personnel for demanding technical and manual jobs is becoming more and more of a tragedy. While these types of professions are attractive in principle, they naturally do not correspond to trendy studies or ITC careers. Furthermore, it has been observed for a long time that plants are being pushed to the limit more and more. One exception would be compressors – but we’ll get to that later.

For the sake of simplicity, I will list a few more reasons that may favour the topic of “condition-based maintenance”:

  • Scarcity of resources for wear material due to the current COVID shortage
  • Maintenance is shown as a pure cost factor in the P&L and not seen as a benefit
  • Lack of or inadequate maintenance strategies
  • Rapidly increasing digitalisation in all areas
  • CO2 reduction with national energy strategies
  • Measures versus results (lack of “fitness coach”)
  • Reduced cost budgets to secure and increase margins
  • Demand for more documentation and evidence
  • Trend towards number orientation and balancing in “extra-monetary” areas
  • etc.

Possible solution parameters for condition-based maintenance

If we now look at examples of motors that are used to drive something or to generate something, we can draw on informative parameters. These already indicate the current “state of health” of a drive system. These would be, as always not conclusive, as follows:

  • Temperature
  • Vibration
  • Cavitation
  • Electrical quantities
  • Ultrasonic
  • Humidity
  • Existing historical values
  • etc.

If these parameters are now considered in a permanent context, i.e. as a whole, completely new insights can be gained. Specifically, we already know the individual parameters that make up a “normal” operation. If you now apply various limits and threshold values to all parameters, you can visualise the state of the system in a short time and, if necessary, intervene at an early stage. Or vice versa. Instead of intervening at intervals, you can see the actual state, whether it would be necessary at all.

Temperature and ultrasonic as important indicators

The temperature on motors, bearings, etc. as well as the measured ultrasound in dB on bearings, shafts, gears, etc. provide important information. For example, the ultrasound value changes upwards, i.e. it becomes louder, targeted and dosed lubrication measures can be carried out. If the dB value is reduced, the lubrication has a positive effect. Does the value increases during lubrication, overlubrication could be the cause. If the dB value continues to increase permanently, this could indicate a defect in the near future, which could also be seen as a symptom in the rising temperature.

Electrical values as very useful additional information

Here, you as a maintenance engineer and operator have the opportunity to save energy by intervening at an early stage. This can be seen very quickly by recording the electrical characteristic curves. With their help, increased and reduced KW/h can be expressed immediately in money and CO2. In addition, trends can be derived from the electrical parameters, such as when which power consumption takes place, which efficiency levels the motors have and how they change, etc. Even grid-specific phenomena would become visible, e.g. harmonics, transients during switch-ons or switch-offs, interruptions, etc. Furthermore, you would already be able to find out in which load behaviour your drives usually are. This is particularly interesting for compressors whose (non-)generated compressed air costs the operator enormous amounts of money.

And now imagine that all this would be integrated into an energy monitoring system in your company – i.e. absolutely scalable for all company areas and their infrastructure. Not only for maintenance.

What could such a system look like?

To simplify matters, I’ll let pictures speak for themselves here.

Towards condition-based maintenanceTowards condition-based maintenance with gears

Towards condition-based maintenance at bearings

Barriers to condition-based maintenance?

In the interest of fairness, however, we should also address the elements that are less favourable to the issue of “condition-based maintenance”. These would be as follows:

  • Saving energy means technical as well as HR-intensive initial effort and requires investment
  • Investments have to be approved and are anchored in the annual budget
  • Electricity costs (KW/h) are too cheap in many countries ≠ Energy saving
  • Repairs are usually not investments and easier to approve (forced investment)
  • Predictive maintenance at time intervals is easy and can be planned well
  • etc.

Conclusion of condition-based maintenance?

In summary, we can say that the topic of condition-based maintenance can generate the following benefits:

  • Matching motors to drives (efficiency)
    Damage detection
  • From predictive maintenance to condition-oriented and thus future-oriented maintenance
  • Recognising if and when problems are imminent
  • Maintenance is only carried out when the condition indicates the need for it
  • Logbooks, documents and records are automatically digitised.
  • Automatically contributes to CO2 reduction
  • ISO50001 compliant
  • PEX and OPEX are automatically reduced
  • The whole system is scalable – ROI is fast.
  • There is no need for a maintenance strategy for the objects in question, as this is automated
  • Sustainability and resource conservation are positively influenced
  • The data can be balanced
  • etc.
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