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NLP-Oriented Voice-Based Order Picking System in a Warehouse Management: A Systematic Review

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Smart Data Intelligence

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

Warehouse management system (WMS) is a software solution that provides visibility into a company’s complete inventory while also managing supply chain fulfillment activities from the warehouses to the store shelves, among other things. It usually delivers laborers to participate in a massive number of works in accordance with the output. The lag in the performance will lead to an increase in costs and unsatisfied customers. The emergence of new markets in this century makes the warehouses hold a massive number of orders within the stipulated period of time. Hence, to handle this issue, the operations that use order picking might need to enforce different portfolios to solve a wide range of planning-related issues by ensuring proper optimization strategies. This optimization method for fixing planning-related issues in order picking might yield better performance in total WMS. Generally, the warehouse planning might emphasize different planning problems. Implementing supply chain management in association with the natural language processing in order picking may improve the performance in handling the related issues. This review focuses on voice picking-related issues in handling planning problems associated with multiple order picking. The various analysis has been done by investigating various scientific literature and works involved in handling various order picking problems. In addition, this analysis aims to identify the effective policy combinations, thus providing valuable guidance for warehouse managers on experiencing the benefits by combining planning-related difficulties to develop a most efficient voice-related order picking system by improving customer service. Incorporating various order picking planning problems yields significant efficiency gains, which are needed to keep up with current market trends.

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Author information

Authors and Affiliations

  1. Department of Computer Science Engineering, Hindustan Institute of Technology and Science, Chennai, India

    I. Mohammed Musthafa Sheriff & D. John Aravindhar

Authors
  1. I. Mohammed Musthafa Sheriff
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  2. D. John Aravindhar
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Correspondence to I. Mohammed Musthafa Sheriff .

Editor information

Editors and Affiliations

  1. Kongunadu College of Engineering and Technology, Tholurpatti, India

    R. Asokan

  2. School of Information Technology and Telecommunications Engineering, University of Granada, Granada, Spain

    Diego P. Ruiz

  3. Deakin University, Waurn Ponds, VIC, Australia

    Zubair A. Baig

  4. Information Systems and Operations Management (ISOM), University of Florida, Gainesville, FL, USA

    Selwyn Piramuthu

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Mohammed Musthafa Sheriff, I., John Aravindhar, D. (2022). NLP-Oriented Voice-Based Order Picking System in a Warehouse Management: A Systematic Review. In: Asokan, R., Ruiz, D.P., Baig, Z.A., Piramuthu, S. (eds) Smart Data Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-3311-0_16

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