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Abstract: Thanks to rapid technological developments in robotics, various automation technologies are being applied in warehouses today. Order picking, as a key process in warehouse operations, has drawn attention in academia and practice for decades. In addition to many studies dedicated to manual and fully automated order picking, efforts have also been made to study semi-automated warehouses in which humans and robots collaborate. However, these studies mostly focused on system efficiency and ignored ergonomic aspects. Order picking was confirmed as a labor-intensive process in an environment in which workers are at a high risk of developing health problems. Therefore, this study addresses the investigation of physical human working conditions in both manual and robot-assisted order picking systems via real-life laboratory experiments and simulation modeling. We used a motion capture system to assess human working postures when working with and without robot assistance. In addition, we estimated the daily workload by applying the energy expenditure concept. Using simulation experiments, we were able to extend the results to various practical scenarios with different design variables, for example warehouse layouts, order sizes, and human-robot team configuration. Our preliminary results reveal that human-robot collaboration can reduce human workload. Posture evaluation also shows a slight improvement.
Keywords: order picking, autonomous mobile robot, human factors, ergonomics, assisted order picking, hybrid order picking, simulation, performance evaluation
Published in DKUM: 21.11.2024; Views: 0; Downloads: 2
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Abstract: Simplicial complexes are mathematical constructions that describe higher-order interactions within the interconnecting elements of a network. Such higher-order interactions become increasingly significant in neuronal networks since biological backgrounds and previous outcomes back them. In light of this, the current research explores a higher-order network of the memristive Rulkov model. To that end, the master stability functions are used to evaluate the synchronization of a network with pure pairwise hybrid (electrical and chemical) synapses alongside a network with two-node electrical and multi-node chemical connections. The findings provide good insight into the impact of incorporating higher-order interaction in a network. Compared to two-node chemical synapses, higher-order interactions adjust the synchronization patterns to lower multi-node chemical coupling parameter values. Furthermore, the effect of altering higher-order coupling parameter value on the dynamics of neurons in the synchronization state is researched. It is also shown how increasing network size can enhance synchronization by lowering the value of coupling parameters whereby synchronization occurs. Except for complete synchronization, cluster synchronization is detected for higher electrical coupling strength values wherein the neurons are out of the completed synchronization state.
Keywords: simplicial complex, higher-order network, memristive Rulkov, synchronization, cluster synchronization
Published in DKUM: 11.09.2024; Views: 37; Downloads: 9
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Abstract: Vision picking empowers users with access to real-time digital order information, while freeing them from handheld radio frequency devices. The smart glasses, as an example of vision picking enabler, provide visual and voice cues to guide order pickers. The glasses mostly also have installed navigation features that can sense the order picker's position in the warehouse. This paper explores picking errors in vision systems with literature review and experimental work in laboratory environment. The results show the effectiveness of applying vision picking systems for the purposes of active error prevention, when they are compared to established methods, such as paper-picking and using cart mounted displays. A serious competitor to vision picking systems are pick-to-light systems. The strong advantage of vision picking system is that most of the errors are detected early in the process and not at the customer's site. The cost of fixing the error is thus minimal. Most errors consequently directly influence order picker's productivity in negative sense. Nonetheless, the distinctive feature of the system is extremely efficient error detection.
Keywords: order picking, storage operations, warehousing, smart glasses, error prevention, inventory management, intralogistics
Published in DKUM: 22.08.2024; Views: 83; Downloads: 4
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Abstract: The logistics sector should strive for sustainability alongside productivity by protecting its order pickers' health and welfare. Existing storage assignment models are mainly based on the criterion of order picking time and, to a lesser extent, the human factor. In the paper, a solution to a storage assignment problem using a multi-objective model based on binary integer linear programing is presented by developing a solution that considers order picking time, energy expenditure and health risk. The Ovako Working Posture Assessment System (OWAS) method was used for health risk assessment. The downside of solely health risk-optimization is that the average order picking time increases by approximately 33 % compared to solely time-optimization. Contrary to this, the developed multi-objective function emphasizing time has proven to be promising in finding a compromise between the optimal order picking time and eliminating work situations with a very-high risk for injuries. Its use increases the time by only 3.8 % compared to solely time-optimization while significantly reducing health risk.
Keywords: productivity, energy expenditure, order picking, order picking system, health risk, OWAS, multi-objective modeling, planning, logistics, ergonomics
Published in DKUM: 13.08.2024; Views: 109; Downloads: 9
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Abstract: The interplay between awareness diffusion and epidemic spreading has been an active topic of research in recent years. Studies have shown that group interactions are an important consideration in contagion processes, and that thus higher-order interactions should be introduced into epidemic modeling. Research has also shown that individual responses to an unfolding epidemic are often strongly heterogeneous. We therefore present a two-layer network model, where the diffusion of awareness unfolds over 2-simplicial complexes in one layer, and the actual epidemic spreading unfolds over pairwise physical contacts in the other layer. The model takes into account individual differences in the degree of acceptance of information and self-protection measures once the epidemic is perceived. We use the micro Markov chain approach to determine the epidemic threshold of the model, which agrees well with the results obtained by Monte Carlo simulations. We show that the synergistic reinforcement due to 2-simplicial complexes in the virtual layer can restrain epidemic spreading by facilitating awareness diffusion, and moreover, that individual heterogeneity in the physical layer can increase the epidemic threshold and decrease the size of epidemic transmission. However, heterogeneity in the perception can also have the opposite effect because it inhibits the diffusion of awareness. Our results reveal the intricate interplay between awareness diffusion and epidemic spreading, and we hope they can help determine effective control measures.
Keywords: higher-order interactions, awareness diffusion, epidemic spreading, multiplex network, social physics
Published in DKUM: 21.06.2024; Views: 163; Downloads: 8
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