Influence of Intelligent Boom Control in Forwarders on Performance of Operators

Zemánek, Tomáš; Fiľo, Petr

doi:10.5552/crojfe.2022.965

Cited by 10 publications

(9 citation statements)

References 21 publications

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“…The operators were also very different from each other in terms of length of time in the profession, which ranged from 2 months to 20 years. According to [9,10,48], the skills and experience of the given operator are an important factor in work productivity, but the heart rate while performing this profession was not affected by it. It should be noted that obtaining a sample of respondents whose mutual variability is small is practically impossible, mainly due to the fact that there is a smaller number of operators.…”

Section: Discussionmentioning

confidence: 99%

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Analysis of the Heart Rate of Operators of Forwarding Machines during Work Activities

Sláma,

Mergl,

Pavlíková

2023

Forests

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The aim of this work was to determine the dependence of the heart rate of operators of forwarding machines on the activities performed during the working day within the framework of timber forwarding and to compare individual activities in terms of the level of physical workload. For this purpose, the work shift of operators carrying out timber forwarding was divided into individual activities: driving, maintenance, forwarding, and break. During these work activities, the heart rate of each operator was taken for subsequent evaluation. A portable device, a Garmin smartwatch, was used to measure their heart rate. The results show that the highest pulse rates of the operators occurred during the maintenance of the entrusted machine, while the highest pulse fluctuations were recorded during forwarding. During this activity, the highest heart rate of the entire measurement process was recorded (132.0000 bpm), but also the lowest (42.0000 bpm). Furthermore, it was proven that both the operator and the activity he performs affect the pulse rate. The activities themselves did not differ from each other in only one of the six cases of comparison, specifically, between driving and forwarding.

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Section: Discussionmentioning

confidence: 99%

“…An example is the use of the IBC (Intelligent Boom Control) system, which enables precise, quick, and easy control of the hydraulic crane. According to [48], novice operators experienced a 27% increase in productivity and a 53% reduction in errors in hydraulic crane control when using the IBC system.…”

Section: Discussionmentioning

confidence: 99%

Analysis of the Heart Rate of Operators of Forwarding Machines during Work Activities

Sláma,

Mergl,

Pavlíková

2023

Forests

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“…The study by Zemánek [17] tested the method of boom ends control in forwarders. Intelligent Boom Control (IBC) only partially improves forwarder operator's productivity over standard hydraulic crane control.…”

Section: Analysis Of the Latest Researchmentioning

confidence: 99%

Training simulators for crane operators and drivers

Аkulov¹,

Zhelieznov²,

Zabolotnyi³

et al. 2023

Engineering Today

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The article deals with the use issues of modern information technology for training purposes. In particular, use of simulation modelling to create a learning environment as close as possible to the real working environment. This helps speed up learning, make more practical, learn theoretical issues directly when mastering practical skills, and make the learning process more attractive and interesting for students. Moreover, a virtual working environment can be used for advanced training of employees, to improve their professional skills, master new technologies, train them to work on new and modernized equipment, assess their professional level, restore skills after a long break in the work and pass qualification exams. Information technologies can significantly reduce the cost of material support for training and eliminate dependence on large areas for staff training. To create an interactive virtual learning environment, modern gaming technologies, software modelling or, at least, simulation modelling of physical processes in equipment and the interaction of all components of the working environment, including the actions of the student, are used. It also allows testing employees in extreme working conditions and testing their skills when dealing with nonstandard and emergency situations, without any real danger to the health of students. The proposed solution can be used to train students and trainees, assess professional skills of those already working in the conditions of special training centers and professional retraining colleges.

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“…from remote locations, while having access to better situational awareness with real-time navigation and augmented reality. Other assistance systems, like the Intelligent Boom Control (ICB), are also simplifying the work of operators, thus reducing their cognitive load [7]. Taking advantage of these technological advances, unmanned logging machines are getting closer to reality.…”

Section: Introductionmentioning

confidence: 99%

Instance Segmentation for Autonomous Log Grasping in Forestry Operations

Fortin¹,

Gamache²,

Grondin³

et al. 2022

Preprint

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Wood logs picking is a challenging task to automate. Indeed, logs usually come in cluttered configurations, randomly orientated and overlapping. Recent work on log picking automation usually assume that the logs' pose is known, with little consideration given to the actual perception problem. In this paper, we squarely address the latter, using a datadriven approach. First, we introduce a novel dataset, named TimberSeg 1.0, that is densely annotated, i.e., that includes both bounding boxes and pixel-level mask annotations for logs. This dataset comprises 220 images with 2500 individually segmented logs. Using our dataset, we then compare three neural network architectures on the task of individual logs detection and segmentation; two region-based methods and one attention-based method. Unsurprisingly, our results show that axis-aligned proposals, failing to take into account the directional nature of logs, underperform with 19.03 mAP. A rotation-aware proposal method significantly improve results to 31.83 mAP. More interestingly, a Transformer-based approach, without any inductive bias on rotations, outperformed the two others, achieving a mAP of 57.53 on our dataset. Our use case demonstrates the limitations of region-based approaches for cluttered, elongated objects. It also highlights the potential of attention-based methods on this specific task, as they work directly at the pixel-level. These encouraging results indicate that such a perception system could be used to assist the operators on the short-term, or to fully automate log picking operations in the future.

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Influence of Intelligent Boom Control in Forwarders on Performance of Operators

Cited by 10 publications

References 21 publications

Analysis of the Heart Rate of Operators of Forwarding Machines during Work Activities

Analysis of the Heart Rate of Operators of Forwarding Machines during Work Activities

Training simulators for crane operators and drivers

Instance Segmentation for Autonomous Log Grasping in Forestry Operations

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