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Performance evaluation of two-worker operations in a worker-to-cell order assorting system
Affiliation:1. Automatic Control Department, Universitat Politècnica de Catalunya, Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Llorens i Artigas 4-6, Planta 2, 08028 Barcelona, Spain;2. Laboratory of Signals and Systems (L2S, UMR CNRS 8506), Centrale Supélec-CNRS Université Paris Sud, Université Paris-Saclay, 91190 Gif-sur-Yvette, France;1. Production Systems and Logistic Systems, BIBA – Bremer Institut für Produktion und Logistik GmbH, University of Bremen, Bremen, Germany;2. Faculty of Business Studies, University of Applied Sciences Emden/Leer, Emden, Germany;1. Department of Industrial and Management Engineering, Incheon National University, 119, Academy-ro, Yeonsu-gu, 22012 Incheon, South Korea;2. Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
Abstract:This paper studies an order assorting system (OAS) composed of multiple-parallel order assorting aisles (OAAs) in a retailer’s order fulfillment center. We evaluate two worker-assignment policies for a worker-to-part OAA: a dedicated-assignment policy and a shared-assignment policy. Our analytical models evaluate the mean value and variance of worker process time including assorting time, walk time, empty walk time, and blocking time when single-line products arrive randomly. From the worker process time, we identify the system flow time of product lines per each worker-assignment policy using G/G/1 and G/G/2 queuing models. We find that the shared-assignment policy performs better compared to the dedicated-assignment policy in spite of workers’ productivity losses incurred by blocking delays over high sort probability, slow walk speed, and high magnitude and variations of inter-arrival times. At the worker-centric break-even point of worker process time, where worker process time suggests selecting either policy, system flow time always suggests selecting the shared-assignment policy.
Keywords:Facility design and planning  Order assorting system  Put-to-light system  Probability and queueing models  Material handling
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