## 2 Literature Review
### Human Reliability Analysis: Origins and Applications in Assembly Systems  
According to [PERSON] [54], the essence of human reliability analysis (HRA) is the prediction and mitigation of error to optimize safety, reliability and productivity. HRA's main focus is the identification of sources of human error and the quantification of the likelihood of such errors [55]. Over the years, the discipline of HRA has proposed several techniques [56; 57], which stem from the need to quantify human error for probabilistic safety analysis (PSA) in the nuclear sector [58; 59]. Other industries where HRA has been applied include aerospace, offshore oil extraction and chemical processing, all of them safety-critical domains [60; 61]. Human reliability analysis represents the intersection of reliability engineering and human factors research [62]. Reliability engineering seeks to predict overall system reliability based on system configuration and probabilistic estimates of component failures [63]. According to [PERSON] et al. [55], human factors research provides the empirical basis to support predicting human performance in HRA. In practical terms, human performance is predicted by calculating human error probability (HEP). Mathematically, human error is treated as the failure of a technical component. However, some HRA techniques focus on human error identification rather than the calculation of human error probabilities [64; 65]. Failure mode and effects analysis (FMEA) is a well-established reliability engineering technique used to assess vulnerabilities in a system proactively [66]. It has been used in manufacturing and manual work [67]. Quality function deployment (QFD), a quality research technique, has also been used to redesign product functionality to reduce complexity in assembly [68]. Despite these examples, a recent literature review by [PERSON] et al. [16] concluded that: \"a prospective analysis of human reliability in the manual assembly systems until now has been neglected in the literature and few papers investigated the range of human error and the type of errors that occur in this field\". However, this conclusion is based on a rather small number of relevant documents, i.e., 20 peer-reviewed papers published in English between 2005 and 2017. Authors from manufacturing powerhouses like Germany, France and Japan, who published in their native languages, were not considered. While non-exhaustive, Table 1 shows additional developments and applications of HRA to manufacturing and manual assembly. Broadly speaking, there are two main approaches to human reliability in manual assembly: the development of context-specific techniques [37; 69; 70] and the application of classic HRA techniques with or without modifications [6; 15; 71]. Context-specific methods are expected to provide more precision in the calculation of HEP, but they are more resource-intensive. For example, methods time and quality measurement (MTQM), developed in Germany, requires in-depth knowledge of predetermined motion time systems (PMTS) and high investments in training time and money [72]. Little information about context-specific techniques is available, which hinders replication of the analysis process. On the other hand, classic HRA techniques like THERP (technique for human error rate prediction), HEART (human error assessment and reduction technique) or SHERPA (systematic human error reduction and prediction approach) are well represented in the literature and enough information is available to carry out an analysis. Furthermore, the importance of obtaining a precise final value of HEP depends on the intended final use of this numerical value. [PERSON] and [PERSON] [73] used assembly specific databases as part of MTQM, to calculate precise estimates of HEP. This is necessary because HEP values are used as part of a production planning tool to conduct cost-benefit analysis. More recently, [PERSON] et al. [74] proposed an intervention framework for the analysis of human error in manual assembly.