## 3 The Proposed PHM System
### Stakeholders' Expectations and Requirements Definition  
According to [10], the first step for the stakeholders' expectations and requirements definition is to identify the stakeholders. In the present study, the stakeholders are the industrial machine producers. They are interested in the implementation of a PHM methodology for machines installed at their clients' plants since it is an opportunity for offering a full maintenance service to their clients, for optimizing the spare part-supplying process, and improving the machine design phase. Besides, machinery users could benefit from a PHM system since they can reduce maintenance investments and improve productivity and availability.  
Stakeholders requirements, collected through interviews conducted with several machinery producers operating in the North of Italy, can be summarized as follows:  
1. A PHM system should allow the simultaneous monitoring of machines distributed worldwide. Producers want to gather relevant data from installed equipment to expand their knowledge about the machinery's behavior during the actual functioning. In addition, the remote monitoring of the health conditions of machinery would avoid inspections; hence, the scheduling of maintenance interventions and the spare parts management are improved. This requirement implies building a proper infrastructure for real-time data collection, transfer, and analysis.
2. A PHM system should be able to detect novel behaviors and learn from new incoming data. Machine producers do not have sufficient data for training ML models because of the scarce possibility to conduct tests in their plants. The main issue is the lack of knowledge of all possible working conditions. Besides, many components fail after years of functioning, making it difficult for the real-time application of pre-built prognostic models.
3. A PHM system should allow the collection of the data in a more structured way. Even if machine producers can obtain historical data from their clients, these data are not easy to process since the label (e.g., health status, implemented setting, and so on) is hardly available and signals often present uncomprehensive trends. Low-frequency data, e.g., the setting of the machinery, and event-data, e.g., the tuning made by operators or the anomalies that occurred during the machine functioning, should be collected together with high-frequency data. Hence, data are automatically labeled, and every event affecting the trend of collected data is recorded, speeding up the data pre-processing step.
4. A PHM system should accomplish various functions based on a specific component, which means that functions should be performed separately depending on the analysis goal. A complex machine consists of many elements, e.g., suckers, or sub-systems, e.g., an extruder, for which various analyses may be helpful. For example, an extruder's screw degrades over time, and the goal is to predict its RUL. Instead, the detachment of a sucker happens suddenly. Thus, the goal is to detect the anomaly. Hence, the real-time analysis should consider these two components separately to understand the problem's cause and, if possible, let the machine operator intervene as soon as possible. However, as long as these two components work simultaneously under the same operating conditions, machine producers are also interested in how the anomalies or failures affect each other, considering a given working condition.
5. A PHM system should allow the CM data integration with historical data usually recorded in an external database (e.g., Computerized Maintenance Management System--CMMS), collecting work orders, spare parts management, and other information to develop a whole maintenance program. For machine producers that want to provide their clients with full-service maintenance, this is extremely important for internal optimization.  
Table 1 shows the elements of the framework and architectures that can address each requirement. In the following sub-sections, each element will be investigated in detail.