###### Abstract  
Research on flexible unit systems (FUS) with the context of descriptive, predictive, and prescriptive analysis have remarkably progressed in recent times, being now reinforced in the current Industry 4.0 era with the increased focus on integration of distributed and digitalized systems. In the existing literature, most of the work focused on the individual contributions of the above mentioned three analyses. Moreover, the current literature is unclear with respect to the integration of degradation and upgradation models for FUS. In this paper, a systematic literature review on degradation, residual life distribution, workload adjustment strategy, upgradation, and predictive maintenance as major performance measures to investigate the performance of the FUS has been considered. In order to identify the key issues and research gaps in the existing literature, the 59 most relevant papers from 2009 to 2020 have been sorted and analyzed. Finally, we identify promising research opportunities that could expand the scope and depth of FUS.  
flexible unit systems; degradation; residual life distribution; workload strategy; upgradation; predictive maintenance +
Footnote †: journal: _Future Internet_  
To improve the health status of the system and to make the manufacturing functions effective and efficient, system-level health monitoring is new thinking to which nowadays researchers are paying attention. Therefore, the degradation rate at the system level is of the highest priority. Studies have shown that manufacturing systems are subjected to degradation both with age and usage, including wear, cracking, and fatigue, among others; whereas the residual life of a machine was characterized as remaining useful till its level of degradation arrives at a predefined failure threshold [12]. Real-time production data from complex systems produce a huge variety and volume of data. Handling this kind of data-intensive system with conventional statistical tools may be insufficient when firms seek to strategically conceal the data [13]. Hence, there is a need for advanced analytics such as descriptive, predictive, and prescriptive analytics to analyze the machine's historical data to improve the efficiency of the system by knowing the health condition at every stage.  
Given this scenario, towards summarizing the status of present research and to stimulate the future investigations, the main aim of this paper is to carry out a Systematic Literature Review (SLR) with respect to the degradation and upgradation models for FUS. Hence, a review of manufacturing systems in the context of three analytics has been considered, particularly with flexibility as a key common word. The analysis of the reviewed literature enabled us to develop a comprehensive conceptualization as shown in (Figure 1). It is the conceptualization that was used to classify the findings and it was also referenced for future research.  
The paper is structured as follows. In Section 2, a detailed research methodology is used, which follows SLR's five-step approach. Effectiveness of degradation and upgradation models on the FUS and findings have been presented in Section 3. Discussion and  
Figure 1: Framework addressing the topics affecting flexible unit systems (FUS).  
Future research agenda is explained in Section 4. Conclusions and future work directions are pointed out in Section 5.