Wire Harness Assembly Process Supported by a Collaborative Robot: A Case Study Focus on Ergonomics

Abstract

Products and assets are becoming increasingly “smart”, e.g., mechatronic, electronic, or cyber-physical. In the lack of fully reliable wireless solutions, extensive wiring and wire bundling into wire harnesses are needed. This has manufacturing implications, leading to increasingly complex wire harness assembly processes, where numerous components, connectors, and cables are assembled, connecting critical and non-critical electric and electronic systems in smart products and assets. Thus, wire harnesses demand is rapidly rising in most industries, requiring human or robotic work. Often, required work tasks are repetitive and physically demanding, while still needing people for quality reasons. An attractive solution would therefore be humans collaborating with robots. Unfortunately, there are very few scientific studies on automation solutions using collaborative robots (cobots) for wire harness assembly process tasks to increase process productivity and improve work ergonomics. Furthermore, wire harness assembly process tasks are presently carried out 90% manually in this industry, causing serious ergonomic problems for assembly workers who perform such tasks daily. The challenge is reducing the ergonomic risks currently present in many established wire harness assembly processes while improving production time and quality. This paper presents an early prototype and simulation to integrate a cobot into a wire harness assembly process, primarily for work ergonomic improvements. The use of a cobot is specifically proposed to reduce ergonomic risks for wire harness assembly workers. Two methodologies: RULA and JSI were used to evaluate the ergonomics of the task of cable tie collocation. The real-world case study results illustrate the validation of a cobot which significantly reduced non-ergonomic postures in the task of placing cable ties in the wire harnesses assembly process studied. An ergonomic analysis without the cobot (the actual process) was conducted, based on RULA and JSI methodologies, presenting the highest possible scores in both evaluations, which calls for urgent changes in the current wire harness assembly process task studied. Then, the same analysis was performed with the cobot, obtaining significant reductions in the ergonomic risks of the task at hand to acceptable values.

Development of a Neuroergonomic Assessment for the Evaluation of Mental Workload in an Industrial Human–Robot Interaction Assembly Task: A Comparative Case Study

“…This has brought to the analysis and study of HRI solutions to let the operators work alongside robots. Thus, the study of the mental workload in HRI is pivotal [60]. However, the method to apply wireless, real-time, objective measurements such as EEG in industrial HRI tasks to define the mental workload in terms of brainwave activity is still at the beginning [52].…”

“…The designed task recalled the wire-harnessing activities carried out in manufacturing workplaces. The selection of this task, recalling the wire-harness assembly tasks, came from a lack of research studies regarding the neuroergonomic analysis of these activities with the involvement of supportive technologies, such as robots [60]. During the experiments, the temperature was maintained at 23 ± 1.5 °C.…”

Collaborative robots in manufacturing and assembly systems: literature review and future research agenda

“…After several framework studies, Gil-Vilda et al (2017) evaluated the performance of a real collaborative assembly line in a comparative case study. Other examples include Wang et al (2019), D'Souza et al (2020, Inoue et al (2021), Sordan et al (2021), andNavas-Reascos et al, (2022a) with different performance criteria. Simulation was the next methodology used in this class (Malik et al, 2020Thomas et al, 2018;Zhu et al, 2022).…”

“…This includes not only laboratory testing with human and cobot participants, but also real-world case studies and practical applications that provide a more realistic view of how cobots are impacting the manufacturing industry. Currently, only three studies (i.e., Gil-Vilda et al, 2017;Navas-Reascos et al, 2022a) provide data that can be used to guide future research, highlighting the need for more robust and inclusive data sets to support the growth and development of cobots in the manufacturing industry.…”

Manipulation Planning for Cable Shape Control

“…Cables, wires, and other deformable linear objects (DLOs) are integral to a wide range of everyday applications, encompassing tasks such as wiring in the automotive industry [1][2][3], belt assembly [4], and surgical suturing [5,6]. However, robotizing the DLOs-related tasks is still an open challenge in the robotics community due to the inherent complexity and the multitude of ways in which DLOs can deform [7].…”