## 3 Functional Resonance Analysis Method (FRAM)  
FRAM [3] is a systemic analysis method that is used to describe the activities of a complex socio-technical system. This method considers the non-linear nature of the system performance rather than build a sequential cause-effect model of events over time [40]. FRAM enables the analysis from past events of a complex system, such as an accident investigation, safety management, and complexity management up to possible future events as a risk assessment [41]. The main purpose of FRAM is to build a model of the functions of a system that describes how performance variability may occur in the work-as-done (WAD) and how the effects may spread through the system. Regarding the graphical appearance of a FRAM model, for professionals who have never seen it, it seems a complex structure, which it is not. Indeed, the outcome analysis is not an algorithmic process, but rather the representation of the non-linear relationship among users working together [42]. FRAM has been extensively applied to the understanding and identification of variability and resilience in complex systems in several domains, such as aviation [43; 44; 45], construction [46; 47], manufacturing [48], environmental [49], healthcare [50; 51], the oil industry [42; 52; 53], and the maritime industry [54]. Other FRAM's applications are found in extensive mappings, such as in [41; 55]. This methodology is based on four principles [3]:  
* Equivalence of successes and failures: Failures and successes occur in the same way, i.e., everyday work variability;
* Principle of approximate adjustments: Work-as-done (WAD) never completely correspond to work-as-imagined (WAI). Workers typically adjust their performance to suit existing conditions. * Principle of emergence: The performance variability of a function is rarely large enough to serve as the only cause of an effect or even to constitute a malfunction. Acceptable and unacceptable results are emergent rather than resultant phenomena, as they cannot be explained just by a cause-effect relationship of the operation of specific components or parts. * Functional resonance: This latter principle states that the variability of a function may combine with the variability from another function, which causes a functional resonance with a difficult prognosis and significant uncomfortable management. Where it has become a utility to the organizations, the identification of functional resonance phenomena is cited as an instrument to locate management demands, including specific actions. In this case, losses in maintenance quality, delay, or incorrect maintenance are some depictions of undesirable effects. To build a FRAM model, it is necessary to follow four steps, established by [PERSON] [3]. The first step is the identification and description of the functions, which can be human, technological, or organizational, depending on the nature of the function in the system. This step seeks to describe how the work is done every day, highlighting how the functions interplay with each other, rather than to build an overall flowchart or a function's structure. FRAM and IDEF0 are similar in terms of decomposing the system functions by using the four aspects of input, output, control, and resources. FRAM extends the number of aspects to include preconditions and a specific aspect representing temporal constraints [29]. The graphic representation of a function is a hexagon, consisting of one output and five inputs. Each vertex of this hexagon is identified as one of the six aspects [3]:  
* Input (I): what triggers the function or what is processed or transformed by the function;
* Output (O): what is the result of the function, it can be either a state change or a specific product;
* Precondition (P): mandatory conditions that must exist before the function can be performed;
* Resource (R): what the function needs or must consume when it is carried out to produce the result (the output);
* Control (C): what controls and monitors the function to match the desired output.