Digitalization of Musculoskeletal Risk Assessment in a Robotic-Assisted Assembly Workstation

Abstract

The ergonomic assessment of adopted working postures is essential for avoiding musculoskeletal risk factors in manufacturing contexts. Several observational methods based on external analyst observations are available; however, they are relatively subjective and suffer low repeatability. Over the past decade, the digitalization of this assessment has received high research interest. Robotic applications have the potential to lighten workers’ workload and improve working conditions. Therefore, this work presents a musculoskeletal risk assessment before and after robotic implementation in an assembly workstation. We also emphasize the importance of using novel and non-intrusive technologies for musculoskeletal risk assessment. A kinematic study was conducted using inertial motion units (IMU) in a convenience sample of two workers during their normal performance of assembly work cycles. The musculoskeletal risk was estimated according to a semi-automated solution, called the Rapid Upper Limb Assessment (RULA) report. Based on previous musculoskeletal problems reported by the company, the assessment centered on the kinematic analysis of functional wrist movements (flexion/extension, ulnar/radial deviation, and pronation/supination). The results of the RULA report showed a reduction in musculoskeletal risk using robotic-assisted assembly. Regarding the kinematic analysis of the wrist during robotic-assisted tasks, a significant posture improvement of 20–45% was registered (considering the angular deviations relative to the neutral wrist position). The results obtained by direct measurements simultaneously reflect the workload and individual characteristics. The current study highlights the importance of an in-field instrumented assessment of musculoskeletal risk and the limitations of the system applied (e.g., unsuitable for tracking the motion of small joints, such as the fingers).

Transparency as a Means to Analyse the Impact of Inertial Sensors on Users during the Occupational Ergonomic Assessment: A Systematic Review

“…The analysed works focused on several industries. Among the 17 studies, the most represented sector (n = 6; 35%) was industrial manufacturing and manual material handling tasks [ 53 , 56 , 62 , 63 , 67 , 68 ]. Four (n = 4; 24%) were dedicated to the dental sector [ 54 , 57 , 60 , 64 ], and another four (n = 4; 24%) to surgery [ 55 , 58 , 65 , 69 ].…”

“…Regarding the general objective of the included articles, six (n = 6; 35%) addressed the development and presentation of systems based on inertial systems to analyse one or more ergonomic indices [ 53 , 55 , 57 , 61 , 66 , 67 ]. Another six studies (n = 6; 35%) designed their intervention based on an ergonomic risk comparison between different workstations or workstation implementations [ 56 , 58 , 59 , 60 , 64 , 65 ]. Finally, three works were dedicated to analysing ergonomic risk in a specific industry or task [ 54 , 68 , 69 ], and two others analysed the accuracy and reliability of this technology for workplace ergonomic assessment [ 62 , 63 ].…”

“…Firstly, in relation to the sensors used in each analysed study, the vast majority (n = 13; 77%) used the Xsens MVN system. Of these, most (n = 11) set up all sensors (i.e., 17 MTw sensors) including the MVN system [ 53 , 54 , 57 , 59 , 60 , 61 , 62 , 63 , 64 , 66 , 69 ], and only two used 11 [ 56 ] and 3 [ 55 ] MTw sensors, respectively, from the Xsens MVN system. On the other hand, in only four cases [ 58 , 65 , 67 , 68 ] was the Xsens MVN system not used, a different inertial sensor system being employed in its place.…”

“…On the other hand, seven studies (n = 7; 41%) used video recording as a reference when contrasting the data [ 53 , 54 , 55 , 61 , 66 , 68 , 69 ]. Finally, two studies (n = 2; 12%) required the use of goniometers (bi-axial SG65, Biometrics Ltd., Newport) on the back of the hand due to sensor system limitations [ 67 , 68 ], and seven studies (n = 7; 41%) did not implement any combination with inertial technology [ 56 , 57 , 58 , 59 , 60 , 64 , 65 ].…”

“…Thirdly, the vast majority of the studies (n = 14; 82%) used protocols focused on analysing the upper body [ 54 , 55 , 56 , 57 , 58 , 59 , 60 , 62 , 63 , 64 , 65 , 67 , 68 , 69 ]. Only three studies (n = 3; 18%) analysed the entire body [ 53 , 61 , 66 ].…”