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While most companies recognize that, because of increasing competition, they need to look into modern technologies to support their production at every level, many companies also struggle to define a clear path from their current state to the desired outcome.
It doesn’t help that terms such as “predictive maintenance” and “prescriptive maintenance” allow for multiple interpretations and therewith different expectations from stakeholders.
To allow for a common understanding and therefore support decision making, we will use this blog to focus on prescriptive maintenance, break it down into 3 different levels and provide clear examples and use cases for all.
The first level of prescriptive maintenance relates to the use of ready-made and relatively simple scenarios of recommended actions. These actions are taken based on the occurrence of specific conditions, such as availability of spare parts, personnel or backup machines. These scenarios are developed on the basis of expert knowledge and “non-dynamic” data (for example the construction of a machine) and is most often performed at the machine or node level.
This first level does not require the use of advanced AI algorithms.
The second level of prescription, like the first one, comes down to the use of ready-made and relatively simple scenarios of recommended actions. However, in this case they are taken on the basis of complex data analysis. These types of scenarios are developed on the basis of expert knowledge, “non-dynamic” data and “dynamic” off-line data such as vibrations, temperature, pressure.
Level II prescriptions are most often performed at the level of the production process and do require the use of advanced AI algorithms.
The third level of prescriptive maintenance includes the use of dynamic, complex scenarios of recommended actions, which are taken on the basis of complex data analysis. These scenarios are developed on the basis of all available data, in particular online production and business data.
Level III prescriptions are most often performed at the level of the production process and also require the use of advanced AI algorithms.
There are multiple drivers for companies to adopt a prescriptive maintenance approach.
When implemented correctly, Prescriptive Maintenance solutions offer clear and tangible business benefits to not only the Maintenance department, but also Plant Management, and QHSE:
Read also: Why is Condition Monitoring not always enough and why is Predictive Maintenance worth implementing?
$ 18 billion – that’s how much in 2016, according to the National Institute of Standards and Technology of the United States, American entrepreneurs in the discrete manufacturing sector spent on production downtimes due to machine failures. $ 100 billion – that’s the additional cost of their lost sales due to delays and defects as […]
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