1. The NASA-TLX approach to understand workers workload in humanrobot collaborationAljaž Javernik, Borut Buchmeister, Robert Ojsteršek, 2023, original scientific article Abstract: Human-robot collaboration (HRC) is becoming increasingly widespread in today's production systems, as it can contribute to achieving more efficient and flexible production systems. Given the growing importance of HRC, this paper addresses the significance of human workload in HRC. To study workers workload an experiment was conducted using NASA-TLX questionnaire. The experiment featured two scenarios involving the same operation but varying robot motion parameters. Recognizing that individual differences contribute to success of collaboration, the experiment considered worker utilization in relation to robot motion parameters. To ensure the credibility of the experimental results, the robot motion parameters were adjusted to each individual in order to achieve the same conditions and utilization at all participants. Results revealed that worker utilization, in conjunction with robot motion parameters significantly influenced worker workload. The results highlight the need for personalized guidelines in collaborative workplaces that emphasize individual differences in abilities, skills and personalities to increase overall well-being and robot and worker productivity.
Keywords: human-robot collaboration, industry 5.0, collaborative workplace, NASA-TLX, safety awareness, worker well-being, worker workload
Published in DKUM: 10.03.2025; Views: 0; Downloads: 4
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2. Toward optimal robot machining considering the workpiece surface geometry in a task-oriented approachAleš Hace, 2024, original scientific article Abstract: Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot’s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments.periments.
Keywords: robotics, automation, robot machining, workpiece surface polishing, collaborative robot, manipulability, complex surface geometry, motion planning
Published in DKUM: 25.11.2024; Views: 0; Downloads: 0 |
3. Region-based approach for machining time improvement in robot surface finishingTomaž Pušnik, Aleš Hace, 2024, original scientific article Abstract: Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region’s specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region’s optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot’s joint velocities remained within safe operational limits while executing the region-based surface finishing strategy.
Keywords: robot surface finishing, collaborative robot, region-based machining, workpiece optimization, clustering, task-oriented machining, machining time optimization
Published in DKUM: 25.11.2024; Views: 0; Downloads: 16
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4. Personalizing human–robot workplace parameters in human-centered manufacturingRobert Ojsteršek, Borut Buchmeister, Aljaž Javernik, 2024, original scientific article Abstract: This study investigates the relationship between collaborative robot (CR) parameters and worker utilization and system performance in human–robot collaboration (HRC) environments. We investigated whether optimized parameters increase workplace efficiency and whether adapting these parameters to the individual worker improves workplace outcomes. Three experimental scenarios with different CR parameters were analyzed in terms of the setup time, assembly time, finished products, work in process, and worker utilization. The main results show that personalized CR parameters significantly improve efficiency and productivity. The scenario in which CR parameters were tailored to individual workers, balanced the workload, and minimized worker stress, resulting in higher productivity compared to non-people-centric settings. The study shows that personalization reduces cognitive and physical stress, promotes worker well-being, and is consistent with the principles of human-centered manufacturing. Overall, our research supports the adoption of personalized, collaborative workplace parameters, supported by the mathematical model, to optimize employee efficiency and health, contributing to human-centered and efficient HRC environments.
Keywords: human–robot workplace, collaborative workplace, human-centered manufacturing, stress index, modelling, efficiencxy
Published in DKUM: 03.09.2024; Views: 38; Downloads: 17
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5. The impact of changing collaborative workplace parameters on assembly operation efficiencyKlemen Kovič, Aljaž Javernik, Robert Ojsteršek, Iztok Palčič, 2024, original scientific article Abstract: Human–robot collaborative systems bring several benefits in using human and robot capabilities simultaneously. One of the critical questions is the impact of these systems on production process efficiency. The search for high-level efficiency is severely dependent on collaborative robot characteristics and motion parameters, and the ability of humans to adjust to changing circumstances. Therefore, our research analyzes the effect of the changing collaborative robot motion parameters, acoustic parameters and visual factors in a specific assembly operation, where efficiency is measured through operation times. To conduct our study, we designed a digital twin-based model and a laboratory environment experiment in the form of a collaborative workplace. The results show that changing the motion, acoustic and visual parameters of the collaborative workplace impact the assembly process efficiency significantly.
Keywords: collaborative robot, collaborative workplace, digital twin, assembly operation, efficiency
Published in DKUM: 26.02.2024; Views: 301; Downloads: 22
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6. Audio-visual effects of a collaborative robot on worker efficiencyAljaž Javernik, Klemen Kovič, Iztok Palčič, Robert Ojsteršek, 2023, original scientific article Abstract: Collaborative workplaces are increasingly used in production systems. The possibility of
direct collaboration between robots and humans brings many advantages, as it allows the simultaneous use of human and robotic strengths. However, collaboration between a collaborative robot
and a human raises concerns about the safety of the interaction, the impact of the robot on human
health, human efficiency, etc. Additionally, research is unexplored in the field of the collaborative
robot’s audio-visual effects on the worker’s efficiency. Our study results contribute to the field of
studying collaborative robots’ audio-visual effects on the worker’s behavior. In this research, we
analyze the effect of the changing motion parameters of the collaborative robot (speed and acceleration) on the efficiency of the worker and, consequently, on the production process. Based on the
experimental results, we were able to confirm the impact of robot speed and acceleration on the
worker’s efficiency in terms of assembly time. We also concluded that the sound level and presence of
a visual barrier between the worker and robot by themselves have no effect on the worker’s efficiency.
The experimental part of the paper clearly identifies the impact of visualization on work efficiency.
According to the results, the robot’s audio-visual effects play a key role in achieving high efficiency
and, consequently, justifying the implementation of a collaborative workplace.
Keywords: collaborative robot, worker efficiency, motion parameters, visual contact, sound, human-robot symmetry, repeated measures ANOVA
Published in DKUM: 11.12.2023; Views: 332; Downloads: 35
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7. Evaluating robot bin-picking performance based on Box and Blocks TestPrimož Bencak, Darko Hercog, Tone Lerher, 2022, published scientific conference contribution Abstract: The rise of e-commerce, which demands solutions for small order sizes, large product assortment, short delivery times, and variable order quantity has created a need for more advanced warehousing and order-picking systems. The advancements in collaborative robotics have made it possible to automate intralogistics processes, especially the order-picking systems. If the items to be order-picked are stored in small containers, called bins, the process is known as bin-picking. The processes of bin-picking are still mainly manual due to the adaptability, dexterity, and pace of human hands. However, with the emerging technologies, the gap between human and robot dexterity is getting thinner. The integrators of robotic technologies are therefore faced with the challenge of choosing an appropriate robotic system for bin-picking. There is a lack of standardized procedures, which are designed to process such decisions easier. In our research paper, we propose an improved robotic version of the Box and Blocks Test (BBT), which provides a quick evaluation of a complete robotic bin-picking system. Using our improved robot-adapted BBT protocol, we evaluate a sample robotic bin-picking system, consisting of a collaborative robot, a 3D vision system and three types of robotic grippers, comparing the bin-picking performance of each configuration.
Keywords: robotic bin-picking, intralogistics, Box, Blocks Test, vision system, collaborative robot
Published in DKUM: 03.03.2023; Views: 718; Downloads: 77
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