# The Need for Ecosystem 4.0 to Support Maintenance 4.0: An Aviation Assembly Line Case
## 2 Materials and Methods  
The Smart Prescriptive Maintenance Framework (SPMF), introduced in [PERSON] [9], was developed and tested on a study case to support the introduction of prescriptive maintenance. The present work assembly line presents complex production systems (robots and other equipment), a specific operating environment that provides production requirements or production levels, and a well-defined maintenance capability constituted by maintenance labour, tooling, tribal knowledge and infrastructure suitable for the implementation of the SPMF. The SPMF is built on three domains of interest captured through data fusion methodologies and integrated by artificial intelligence approaches. The SPMF's domains of interest are:  
1. the system's Reliability, Availability, Maintainability and Safety (RAMS) factors;
2. the operating environment in which the system is being deployed;
3. the organization's maintenance capabilities [9]. As restrictions treated in de Mello [3], time is considered during the maintenance schedule that cannot be postponed or anticipated. Cost is also considered, although indirectly, in the restriction that imposes a limit on the available maintenance man-hours and by the objective function, which aims to minimize the maintenance man-hours spent, as presented in Section 3.2. According to [PERSON] [9], although the SPMF was conceived to implement the prescriptive maintenance on a commercial jet fleet, it can be generalized and used to support any complex system. Each domain was selected because it contains essential system information and performance requirements that feed the prescriptive maintenance framework algorithm, so the best group of maintenance actions is defined. Figure 1 presents the framework which unifies ecosystem 4.0 and the SPMF applied to the aviation assembly line. The bottom right box shows the idealized assembly line  
constituted by robots, tools, equipment, workers, and logistics activities. The whole production process and resources are scheduled by the product demand [17]. The framework was built considering the three SPMF's domains previously mentioned:  
1. RAMS information is represented by the technical publications, manuals, specs, maintenance plan, and the data gathered from the condition monitoring;
2. The operating environment and requirements are essentially defined by the production demand, robots, tools, and workforce; and
3. The organization's maintenance capabilities are described by the maintenance resources such as tools, labour available, and maintenance tribal knowledge. Wired or wireless networks and sensors continuously collect temperature, position, humidity, vibration sensors, Radio Frequency Identification (RFID) and internal processes such as built-in-test capabilities, performance, health status and equipment usage. The acquired data sets are successively stored in a centralized big data warehouse. The information is standardized and structured for the simulation and evaluation stage to prescribe and schedule maintenance tasks in real time and keep the assembly line functioning at the required performance through data fusion. The simulation process aims to develop the best maintenance course of action to maximize the Overall Equipment Effectiveness (OEE) and minimize maintenance man-hours while ensuring production level. In the simulation and evaluation stage, all the knowledge-base, parameters, system characteristics, and requirements are considered to generate prescriptive maintenance recommendations. The information considered by the simulation algorithm within the SPMF's framework is listed below:  
* Maintenance manual and maintenance team's \"tribal\" knowledge;
* Equipment condition monitoring to support Prognostics and Health Management, including Remaining Useful Life (RUL) evaluation;
* Available resources such as maintenance labour and tools;
* The maintenance plan, including tasks and their interval; and
* Production demand. Figure 1: SPMF for integrating different Ecosystem 4.0 in the assembly line.