The Experts below are selected from a list of 37146 Experts worldwide ranked by ideXlab platform
Kees Jan Roodbergen - One of the best experts on this subject based on the ideXlab platform.
-
Design and control of warehouse order picking: A literature review
European Journal of Operational Research, 2007Co-Authors: René De Koster, Tho Le-duc, Kees Jan RoodbergenAbstract:Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions. © 2006 Elsevier B.V. All rights reserved.
-
Design and Control of Warehouse Order Picking: a literature review ERIM Report Series reference number
European Journal of Operational Research, 2007Co-Authors: René De Koster, Tho Le-duc, Kees Jan RoodbergenAbstract:Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.
René De Koster - One of the best experts on this subject based on the ideXlab platform.
-
Aligning order picking methods with incentive systems and pickers for performance
ILS 2014 - 5th International Conference on Information Systems Logistics and Supply Chain, 2014Co-Authors: Jelle De Vries, René De Koster, Daniele StamAbstract:A unique controlled field experiment investigates order picking performance (in terms of productivity, quality, and job satisfaction). We examined three manual picker-to-parts order picking methods (parallel, zone, and dynamic zone picking) under two different incentive systems (individual-based versus team-based) for pickers with a different regulatory focus (dominant prevention-focus versus dominant promotion-focus). The study was carried out in a warehouse erected especially for the purposes of this study. Our results show that when using a parallel picking method an individual-based incentive system increases productivity and quality compared to a team-based incentive system, and that when using a zone picking method it is more productive to use a team-based incentive system. This pattern of results was especially pronounced for pickers with a dominant promotion focus. Dominantly prevention focused pickers, however, were more productive with a team-based incentive system, irrespective of the picking method. Additionally, a teambased incentive system delivered a low quality performance in zone picking, but a high quality performance in dynamic zone picking. No substantial differences in job satisfaction could be identified. The analyses demonstrate that by aligning order picking methods, incentive systems and regulatory focus, warehouses can improve productivity and quality, and reduce wage costs by up to 20%.
-
Design and control of warehouse order picking: A literature review
European Journal of Operational Research, 2007Co-Authors: René De Koster, Tho Le-duc, Kees Jan RoodbergenAbstract:Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions. © 2006 Elsevier B.V. All rights reserved.
-
Design and Control of Warehouse Order Picking: a literature review ERIM Report Series reference number
European Journal of Operational Research, 2007Co-Authors: René De Koster, Tho Le-duc, Kees Jan RoodbergenAbstract:Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.
Tho Le-duc - One of the best experts on this subject based on the ideXlab platform.
-
Design and control of warehouse order picking: A literature review
European Journal of Operational Research, 2007Co-Authors: René De Koster, Tho Le-duc, Kees Jan RoodbergenAbstract:Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions. © 2006 Elsevier B.V. All rights reserved.
-
Design and Control of Warehouse Order Picking: a literature review ERIM Report Series reference number
European Journal of Operational Research, 2007Co-Authors: René De Koster, Tho Le-duc, Kees Jan RoodbergenAbstract:Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.
Russell D Meller - One of the best experts on this subject based on the ideXlab platform.
-
selecting between batch and zone order picking strategies in a distribution center
Transportation Research Part E-logistics and Transportation Review, 2008Co-Authors: Pratik J Parikh, Russell D MellerAbstract:An order picking strategy in a distribution center (DC) defines the manner in which pickers navigate the picking area to pick items from storage locations. We focus on the problem of selecting between a batch picking and a zone picking strategy. For this problem, we propose a cost model to estimate the cost of each type of picking strategy. In our cost model we consider the effects of pick-rate, picker blocking, workload-imbalance, and the sorting system requirement. Through an example problem, we show how system throughput, order sizes, item distribution in orders, and wavelength affect the picking strategy selection decision.
Germano Veiga - One of the best experts on this subject based on the ideXlab platform.
-
Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
IEEE Robotics and Automation Letters, 2016Co-Authors: Eduardo Moreira, Luies F. Luís F Rocha, Andry M. Pinto, A. Paulo Moreira, Germano VeigaAbstract:This letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts.
-
assessment of robotic picking operations using a 6 axis force torque sensor
International Conference on Robotics and Automation, 2016Co-Authors: Eduardo Moreira, Luies F. Luís F Rocha, Andry M. Pinto, Paulo A Moreira, Germano VeigaAbstract:This letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts.