## 4 Results
### Systematic Analysis
#### 4.2.5 Q8  
How Can a Standardized Framework for Digital TPM Be Developed, Based on Existing Research and Industrial Needs?  
The emergence of Industry 4.0 and the increasing digitalization of production environments have profoundly transformed maintenance management approaches. Among the 33 studies analyzed, six of them propose digital TMP frameworks. Despite their different models, they all converge on the idea that a standardized framework for digital TPM must be based on the systemic integration of data collection, advanced analysis, and proactive decision-making while preserving the human and organizational foundations of traditional TPM.  
The first pillar of such a framework is modular structuring in functional layers, widely adopted in several articles. Whether it is the four-layer model proposed by [PERSON] et al. [51], combining acquisition, preprocessing, analysis, and decision support, or the three-part architectures integrating sensors, communication gateways, and the cloud [53; 55], a clear hierarchy is essential to organize information flows and make the system scalable and interoperable. This approach is reinforced by the use of open and accessible tools like Arduino, Raspberry Pi, or ThingSpeak, making solutions feasible even for SMEs with limited resources [74].  
The second key area lies in advanced data exploitation, notably through ARM [51; 63; 67; 74], as well as FMEA [63] and multivariate statistical analyses [67]. These methods allow for the automatic detection of root causes of failures, the prioritization of issues, and the proposal of targeted corrective actions, thus reducing full dependence on human expertise. The combined use of ARM and network analysis, as in the works of [PERSON] and [PERSON] [51; 74], helps map complex relationships between events and OEE factors, facilitating both tactical and strategic decision-making.  
System responsiveness and its ability to support real-time maintenance are also key components of a digital standard. [PERSON] et al., [53; 55] highlights the importance of instant visualization, automatic alerts, and prioritized incident reporting. This enables coordinated involvement across all organizational levels (operators, team leaders, management) and reinforces TPM culture by fully integrating maintenance into daily operations.  
However, these technological systems cannot yield lasting results without the human and organizational integration of TPM principles. All high-performing models reviewed include continuous training, autonomous maintenance, standardized routines, and active operator participation in anomaly detection and resolution. This coexistence of human and digital intelligence is particularly emphasized by [PERSON] et al. [51] and [PERSON] et al. [53; 74], who combine traditional TPM with Industry 4.0 tools in a structured continuous improvement cycle based on the PDCA (Plan-Do-Check-Act) model.  
Lastly, sustainability and flexibility emerge as complementary requirements for any standardized framework. The MMSO approach (Modified MultiStep Outflow) [74] is exemplary in this regard, integrating Lean principles, low-impact and modular technologies, and a strong focus on energy performance.