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Smart and flexible manufacturing systems using Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT).

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Title: Smart and flexible manufacturing systems using Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT).
Authors: Vlachos, Ilias1 (AUTHOR) ivlachos@gmail.com, Pascazzi, Rodrigo Martinez2 (AUTHOR), Ntotis, Miltiadis3 (AUTHOR), Spanaki, Konstantina4 (AUTHOR), Despoudi, Stella5,6 (AUTHOR), Repoussis, Panagiotis7 (AUTHOR)
Source: International Journal of Production Research. Aug2024, Vol. 62 Issue 15, p5574-5595. 22p.
Subjects: Flexible manufacturing systems, Texas Instruments Inc., Manufacturing processes, Automated guided vehicle systems, Internet of things, Autonomous vehicles
Abstract: Technologies such as Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT) increasingly disrupt traditional manufacturing and production systems. However, there is a scarcity of empirical studies synthesising and evaluating the impact of disruptive technologies on existing manufacturing systems. This study examines the impact of AGVs applying IoT on Flexible Manufacturing Systems (FMS) through a case study demonstrating the integration of AGVs with IoT in a manufacturing company. As a concept, FMS was conceived decades ago; this study uses socio-technical systems theory to elaborate the concept of FMS into the current context. Key themes uncovered from the literature review include (i) AGVs in warehouse systems, (ii) AGV scheduling and routing, (iii) Human-machine interface, and (iv) integrating and controlling AGVs/IoT. The case study demonstrates how AGVs can create smart, flexible manufacturing systems by taking the following steps: (a) problem identification, (b) performance measurement, (c) designing the proposed solution, (d) evaluate IoT systems, (e) implementation of the new solution, and (f) future improvements. The study concludes with specific recommendations to implement Industry 4.0 in manufacturing companies. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 178176804
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PubTypeId: academicJournal
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  Data: Smart and flexible manufacturing systems using Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT).
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  Data: <searchLink fieldCode="AR" term="%22Vlachos%2C+Ilias%22">Vlachos, Ilias</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ivlachos@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Pascazzi%2C+Rodrigo+Martinez%22">Pascazzi, Rodrigo Martinez</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ntotis%2C+Miltiadis%22">Ntotis, Miltiadis</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Spanaki%2C+Konstantina%22">Spanaki, Konstantina</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Despoudi%2C+Stella%22">Despoudi, Stella</searchLink><relatesTo>5,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Repoussis%2C+Panagiotis%22">Repoussis, Panagiotis</searchLink><relatesTo>7</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Aug2024, Vol. 62 Issue 15, p5574-5595. 22p.
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  Data: <searchLink fieldCode="DE" term="%22Flexible+manufacturing+systems%22">Flexible manufacturing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Texas+Instruments+Inc%2E%22">Texas Instruments Inc.</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+processes%22">Manufacturing processes</searchLink><br /><searchLink fieldCode="DE" term="%22Automated+guided+vehicle+systems%22">Automated guided vehicle systems</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Autonomous+vehicles%22">Autonomous vehicles</searchLink>
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  Data: Technologies such as Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT) increasingly disrupt traditional manufacturing and production systems. However, there is a scarcity of empirical studies synthesising and evaluating the impact of disruptive technologies on existing manufacturing systems. This study examines the impact of AGVs applying IoT on Flexible Manufacturing Systems (FMS) through a case study demonstrating the integration of AGVs with IoT in a manufacturing company. As a concept, FMS was conceived decades ago; this study uses socio-technical systems theory to elaborate the concept of FMS into the current context. Key themes uncovered from the literature review include (i) AGVs in warehouse systems, (ii) AGV scheduling and routing, (iii) Human-machine interface, and (iv) integrating and controlling AGVs/IoT. The case study demonstrates how AGVs can create smart, flexible manufacturing systems by taking the following steps: (a) problem identification, (b) performance measurement, (c) designing the proposed solution, (d) evaluate IoT systems, (e) implementation of the new solution, and (f) future improvements. The study concludes with specific recommendations to implement Industry 4.0 in manufacturing companies. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/00207543.2022.2136282
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        Text: English
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        PageCount: 22
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      – SubjectFull: Flexible manufacturing systems
        Type: general
      – SubjectFull: Texas Instruments Inc.
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      – SubjectFull: Manufacturing processes
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      – SubjectFull: Automated guided vehicle systems
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      – SubjectFull: Internet of things
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      – SubjectFull: Autonomous vehicles
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              Text: Aug2024
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