# A Maturity Model Proposal for Industrial Maintenance and Its Application to the Railway Sector
## 3 Results of Domains and Maintenance Strategies Analysis
### Maintenance Strategies  
Figure 3 shows a possible definition of a process or methodology for prescriptive maintenance conditioned by 18 domains of study. Given [PERSON]'s description of the evolution of strategies, it is to be expected that several of the identified domains belong to previous strategies to the prescriptive one.  
Before discussing the relationship between the domains and the maintenance maturity levels, the definition of the different maintenance strategies is provided:  
* Preventive maintenance: such a strategy is acquired to mitigate the consequences of reactive maintenance. Also known as time-based maintenance, this approach helps to prevent asset failures and breakdowns [42]. This type of strategy is based on the maintainer's knowledge of the asset's behavior in the event of failures to which it is subjected. As a result, periodic preventive planning of maintenance activities is obtained considering the necessary resources, the availability of the service and the impact on operations [43].
* Condition-based maintenance: also known as diagnosis-based maintenance, this strategy is based on the detection of anomalies by applying different technologies for asset monitoring and failure diagnosis [2]. With the information obtained from the diagnosis, it is possible to plan activities based on the current state of degradation of the asset, reducing the costs owed to over-maintenance [44].
* Predictive maintenance: also known as prognostic-based maintenance, this strategy performs maintenance scheduling based on observed future trends in asset behavior [45]. It uses available monitoring information, physics-based models, data analysis and uncertainty analysis by applying different techniques to anticipate the degradation of assets. Not only the level of degradation of the defect is taken into account but also the level of deterioration due to its operation conditions [19].
* Prescriptive maintenance: also known as knowledge-based or cognitive maintenance, this strategy is based on optimizing maintenance based on condition predictions by an AI (Artificial Intelligence) engine. The impact that this planning has on service availability, costs and safety is analyzed by decision models to optimize it [29].  
When focusing on the maintenance of an asset, an issue needs to be raised before starting the definition of the strategy. It relates to the asset itself. The type of asset, and above all, the impact the failure of the asset has, needs to be taken into account, as prescriptive maintenance strategies are more related to critical assets.  
In summary, the deployment of preventive maintenance requires the definition of failure modes (FM), inspection reports, a well-defined and time-based plan of activities and a list of resources necessary to carry them out. For condition-based maintenance, the difference from the previous strategy is the addition of asset monitoring and fault diagnosis. In this way, maintenance activities are carried out based on the actual condition of assets. Predictive maintenance is based on obtaining a prognosis of the asset's condition. This way, maintenance activities can be scheduled accordingly, with the support of operational information. Finally, it would only remain to optimize the maintenance procedure and add decision models based on the information available to automate the execution of maintenance. Once the risk analysis, service unavailability and life cycle cost have been formalized, the automation process is more reliable.  
It can be concluded that prescriptive maintenance is a difficult strategy to adopt in a single step. The following section describes a new solution, based on the evolutionary path that [PERSON] proposes for maintenance, to approach this strategy in an additive (constructive) way, focusing on each of the areas to be evolved (asset, asset status and maintenance) and providing guidance for their evolution as part of the so-called Maintenance Maturity Model (M3) proposal.