Can exposure variation be promoted in the shoulder girdle muscles by modifying work pace and inserting pauses during simulated assembly work?

This study investigated the acute effects of changing the work pace and implementing two pause types during an assembly task. Eighteen healthy women performed a simulated task in four different conditions: 1) slow or 2) fast work pace with 3) passive or 4) active pauses every two minutes. The root mean square (RMS) and exposure variation analysis (EVA) from the trapezius and serratus anterior muscles, as well as the rate of perceived exertion (RPE) from the neck-shoulder region, were observed. Decreased RMS and RPE as well as more variable muscle activity (EVA) were observed in the slow work pace compared with the fast one. The pause types had a limited effect, but active pauses resulted in increased RMS of the clavicular trapezius. The findings revealed the importance of work pace in the reduction of perceived exertion and promotion of variation in muscle activation during assembly tasks. However, the pause types had no important effect on the evaluated outcomes.

Performance differences between instructions on paper vs digital glasses for a simple assembly task

OBJECTIVE

Providing instruction for assembly tasks is essential in modern manufacturing industry, as well as in households for customers that buy products to be assembled at home. Recent technological developments might be able to assist in completing an assembly task faster and more accurately. The aim of this study was to evaluate whether performance and usability differs when instructions for an assembly task are presented on digital glasses versus paper.

METHODS

Participants (n = 63) completed one of three versions of an assembly task (between-subject-design) with LEGO® bricks: (1) with paper instruction (P), (2) with text instructions presented stepwise via digital glasses (GT), (3) with stepwise text and auditory instruction (in parallel) on digital glasses (GA). Outcome measures on performance were completion time and errors. Furthermore, usability was measured by the User Experience Questionnaire, the Standardized Usability Questionnaire, the Post-Study Usability Questionnaire, and cognitive processing skills were assessed by the Trail Making Test and different versions of the Eriksen Flanker Task. Analyses were adjusted for the confounding factors age, gender, experience with glasses and LEGO, and problems with instruction.

RESULTS

Findings indicate that task completion was faster with the paper instructions compared to both versions of instruction via digital glasses (GT, GA). We observed no difference in accuracy and usability between the instructions. "Novelty" was rated higher for instructions for both GT and GA, compared to P.

DISCUSSION

Results show that instructions on digital glasses may not always be more effective for assembly than the traditional paper-based instructions. Further studies are necessary to investigate whether effectiveness may depend on task complexity, target group, experience of the user with task and device, and how the information is presented.

Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context

Industrial settings will be characterized by far-reaching production automation brought about by advancements in robotics and artificial intelligence. As a consequence, human assembly workers will need to adapt quickly to new and more complex assembly procedures, which are most likely to increase cognitive workload, or potentially induce overload. Measurement and optimization protocols need to be developed in order to be able to monitor workers' cognitive load. Previous studies have used electroencephalographic (EEG, measuring brain activity) and electrooculographic (EOG, measuring eye movements) signals, using basic computer-based static tasks and without creating an experience of overload. In this study, EEG and EOG data was collected of 46 participants performing an ecologically valid assembly task while inducing three levels of cognitive load (low, high and overload). The lower individual alpha frequency (IAF) was identified as a promising marker for discriminating between different levels of cognitive load and overload.

Cobot selection using hybrid AHP-TOPSIS based multi-criteria decision making technique for fuel filter assembly process

The choice of a suitable collaborative robot (cobot) for a real-time industrial process is one of the obstacles to effective robot implementation in terms of energy and cost. The cobot selection process for an application have become more complex due to increasing sophisticated features and capabilities in cobots offered by the manufacturers. The paper presents a hybrid Multi-Criteria Decision-Making (MCDM) technique based on Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches for selecting cobots for fuel filter assembly operation. The product design methodology, manufacturing method, and associated cost are directly influencing the decision on cobot selection. The most appropriate robot to accomplish the desired task at the lowest possible cost and capability can be selected by AHP with prospective criterion weight for subsequent processing. The TOPSIS approach orders alternatives based on the prominence of criteria. A diesel fuel filter assembly process case was considered for validating the proposed technique of cobot selection process. An expert knowledge base was generated for 12 advocated cobots and the best cobot was selected using the proposed hybrid MCDM technique.

Biomechanical analysis on neurotypical and autism spectrum disorder people during human-cobot interaction

Biomechanical analysis is essential for assessing subjects interacting with robotic setups and platforms. However, in industrial scenarios, workers' biomechanics are assessed mainly through questionnaires and scales which provide limited objectivity. Very few studies analyzed the biomechanics of workers in multiple sessions, and no study assessed diverse populations of workers. Therefore, we collected tracking data from 14 neurotypical and 7 participants with autism spectrum disorder (ASD) performing assembly tasks in a lab-based industrial collaborative workcell. Human tracking data were acquired by an Azure Kinect and elaborated with a biomechanical model that allowed to compute human kinematics and dynamics. The biomechanics of neurotypical and ASD operators were compared across two working sessions. Both neurotypical and people characterized by ASD decreased torque and power in the second session with respect to the first one, indicating adaptation to the working activity. Interestingly, ASD people expended more energy than neurotypical, suggesting a higher risk of fatigue. Overall, ASD people performed similarly to neurotypical people from a biomechanical point of view. In this study, we showed a protocol for multisession biomechanical monitoring of workers during industrial human-robot collaboration tasks that can be employed in real scenarios and with ASD workers. This approach can be useful in human-robot collaboration to design minimum-fatigue collaborative tasks, support physical health, and improve ergonomics for workers.