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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: With the introduction of Lean Warehousing, we are committed to using lean principles for more efficient warehousing operations, which are performed with quality and safety. Manual order picking, on which the paper is focused, is currently considered the most unfriendly to humans because, in the long run, it contributes to the appearance of musculoskeletal disorders. We record not only the increase in the average age of employees in warehouses but also in the number and duration of sick leave due to back and muscle pain. This paper explores the possibility of productive work while preventing order pickers from Work-Related Musculoskeletal Disorders. Using a laboratory experiment, we determine retrieval times for units with different characteristics and study required postures by guidelines of Revised NIOSH Lifting Equation. The final goal is to create a bi-objective assignment model.
Keywords: warehousing, order picking, ergonomics, intralogistics, lean logistics, manual order picking, productivity, revised NIOSH lifting equation, warehousing, work-related musculoskeletal disorders
Published in DKUM: 13.06.2024; Views: 105; Downloads: 8
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Abstract: Warehousing is one of the most important activities in the supply chain, enabling competitive advantage. Effective management of warehousing processes is, therefore, crucial for achieving minimal costs, maximum efficiency, and overall customer satisfaction. Warehouse Management Systems (WMS) are the first steps towards organizing these processes; however, due to the human factor involved, information on products, vehicles and workers may be missing, corrupt, or misleading. In this paper, a cost-effective Indoor Positioning System (IPS) based on Bluetooth Low Energy (BLE) technology is presented for use in Intralogistics that works automatically, and therefore minimizes the possibility of acquiring incorrect data. The proposed IPS solution is intended to be used for supervising order-picker movements, movement of packages between workstations, and tracking other mobile devices in a manually operated warehouse. Only data that are accurate, reliable and represent the actual state of the system, are useful for detailed material flow analysis and optimization in Intralogistics. Using the developed solution, IPS technology is leveraged to enhance the manually operated warehouse operational efficiency in Intralogistics. Due to the hardware independence, the developed software solution can be used with virtually any BLE supported beacons and receivers. The results of IPS testing in laboratory/office settings show that up to 98% of passings are detected successfully with time delays between approach and detection of less than 0.5 s.
Keywords: warehousing, indoor positioning systems, bluetooth low energy, particle swarm optimization, nature–inspired algorithm, intralogistics
Published in DKUM: 17.08.2023; Views: 432; Downloads: 59
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Abstract: Robotics has been gaining attention in intralogistics applications in recent years. Automation of intralogistics processes aims to cope with the rising trends of workforce deficiency, aging, and increasing demands that came with the rise of E-commerce. Many improvements aim at bin-picking applications since order-picking requires most contributions while adding little to the products' value. Robotic bin-pickers are showing promising results; however, they are still subject to many limitations. First, the vision system must correctly determine the object's location and orientation. Second, a correct robotic gripper must be chosen. Lastly, appropriate grasping points that lead to successful picking must be selected. In this paper, we explore the influencing parameters of object detection using a 3D vision system. Second, we analyze an actual bin-picking application to determine the most appropriate selection of the robotic gripper. Based on the experiments, we provide the guidelines for selecting the most appropriate robotic bin-picking configuration.
Keywords: intralogistics, robotic bin-picking, detection analysis, graspability analysis
Published in DKUM: 25.07.2023; Views: 407; Downloads: 27
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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: 65
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