Training simulators for manufacturing processes: Literature review and systematisation of applicability factors

Abstract

Training simulators are fundamental for training in areas, such as aviation, medicine, and the military. While new applications emerge in conjunction with the development of human–machine interface (HMI) technologies, only a few applications for manufacturing processes are used in industrial practice. This study provides a literature review on simulation‐based training in manufacturing processes and applies the definitions of DIN 8580:2003 to structure the research. The identified applications are further analysed regarding their HMI design and the process‐related benefits and limitations that were described within the publications. Although 202 applications were found, most focus on a small number of processes, and the others rarely mature past the prototype stage. The distribution implies that certain process‐specific factors impact the applicability of simulation‐based training in manufacturing processes. In this context, applicability factors are defined as characteristics of the original training process that affect the training adversely and that can be avoided or reduced in a training simulation. A systematisation of these applicability factors is developed as a step towards a process analysis methodology.

VR and AR virtual welding for psychomotor skills: a systematic review

“…In Knoke et al [ 27 ], the authors classified the training simulators into several manufacturing processes: primary shaping, forming, separating, joining, coating and finishing, and changing material properties. The welding training was classified under the joining process.…”

“… Augmented Reality (AR) 7 [ 1 , 5 , 20 , 29 , 34 , 41 , 42 ] 3. Review articles of VR or AR welding training workshops 5 [ 3 , 27 , 30 , 31 , 36 ] TOTAL 42

Fig. 5 Stacked bar chart of the number of studies by types of welding training workshop and year, excluding the review papers

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Research on Virtual Human Motion Control Based on Computer-Assisted Multimedia Simulation

“…BSHA (Burandt–Schultetushand–Arman analysis) obtains the maximum allowable load that the arm system can bear by analyzing the human body's one-handed snatch work, and compares it with the actual load to reach the conclusion whether the one-handed operation is safe. Among them, there are four main factors that affect the results of BSHA analysis, that is, human factors, work-related parameters, load-related parameters, and actual load size [ 10 ]: Human factors include workers' gender, age, and training level, and they determine the coefficient P 1 (male = 1.0, female or male and female = −0.65), T lim (25∼65 years old, coefficient is 0.80∼0.65), and P 2 (average level = 1.0, better = 1.2, good = 1.4). Job-related parameters include job type (dynamic or static), 4 aspects of working frequency and time, and arm position.…”

Robust Assembly Assistance Using Informed Tree Search with Markov Chains

“…The article concludes that "product clustering, modularization, delayed product differentiation, mixed-model assembly, and reconfigurable assembly systems" are essential for competitive assembly operation in mass customization and that augmented and virtual reality technologies are the key enabling technologies for supporting the operator. Worker assistance systems are analyzed in [10] from a manufacturing process perspective, covering more than 200 applications. The study revealed that most applications are for assembly processes, followed by cutting, welding, disassembly, and coating from the liquid state manufacturing process.…”