Enabling Big Data Analytics and AI Solutions for Smart Warehouse

Nihal Er; Gizem Melike Cidal; Simge Ünsal; Muammer Altan Çakır

doi:10.1007/978-3-030-85626-7_108

Enabling Big Data Analytics and AI Solutions for Smart Warehouse

Nihal Er
, Gizem Melike Cidal
, Simge Ünsal^*
, Muammer Altan Çakır

^*Bu çalışma için yazışmadan sorumlu yazar

Fizik Mühendisliği Bölümü

DHL Supply Chain

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

2 Atıf (Scopus)

Özet

Today’s warehouse processes require more flexibility than conventional methods in behalf of greater responsiveness to customer orders. The improvement of a smart warehouse strategy through the use of big data technologies and AI, including smart data collection and data manipulation tools, to improve warehouse efficiency and productivity is a popular discussion topic. AI-based data manipulation techniques are used to categorize the types of optimal input for the operation of retrieving goods from specified storage locations based on customer orders, order picking to provide more flexible planning and predictive analysis in the warehouse and distribution center. This study focuses specifically on a web-based interactive AI order picking optimization tool for data manipulation. The AI-based data manipulation tool has a mainspring effect on warehouse performance to get a robust dynamic order picking operation that allows for changes of picking lists during a picking cycle in the warehouse.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference
Editörler	Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	929-936
Sayfa sayısı	8
ISBN (Basılı)	9783030856250
DOI'lar	https://doi.org/10.1007/978-3-030-85626-7_108
Yayın durumu	Yayınlandı - 2022
Etkinlik	International Conference on Intelligent and Fuzzy Systems, INFUS 2021 - Istanbul, Türkiye Süre: 24 Ağu 2021 → 26 Ağu 2021

Yayın serisi

Adı	Lecture Notes in Networks and Systems
Hacim	307
ISSN (Basılı)	2367-3370
ISSN (Elektronik)	2367-3389

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	International Conference on Intelligent and Fuzzy Systems, INFUS 2021
Ülke/Bölge	Türkiye
Şehir	Istanbul
Periyot	24/08/21 → 26/08/21

Bibliyografik not

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Finansman

Supported by DHL Supply Chain.

Finansörler
DHL

Belgeye Erişim

10.1007/978-3-030-85626-7_108

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Er, N., Cidal, G. M., Ünsal, S., & Çakır, M. A. (2022). Enabling Big Data Analytics and AI Solutions for Smart Warehouse. In C. Kahraman, S. Cebi, S. Cevik Onar, B. Oztaysi, A. C. Tolga, & I. U. Sari (Eds.), Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference (pp. 929-936). (Lecture Notes in Networks and Systems; Hac. 307). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-85626-7_108

Er, Nihal ; Cidal, Gizem Melike ; Ünsal, Simge et al. / Enabling Big Data Analytics and AI Solutions for Smart Warehouse. Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference. editör / Cengiz Kahraman ; Selcuk Cebi ; Sezi Cevik Onar ; Basar Oztaysi ; A. Cagri Tolga ; Irem Ucal Sari. Springer Science and Business Media Deutschland GmbH, 2022. pp. 929-936 (Lecture Notes in Networks and Systems).

@inproceedings{1f36128d8ae54dca951eda1056e7a194,

title = "Enabling Big Data Analytics and AI Solutions for Smart Warehouse",

abstract = "Today{\textquoteright}s warehouse processes require more flexibility than conventional methods in behalf of greater responsiveness to customer orders. The improvement of a smart warehouse strategy through the use of big data technologies and AI, including smart data collection and data manipulation tools, to improve warehouse efficiency and productivity is a popular discussion topic. AI-based data manipulation techniques are used to categorize the types of optimal input for the operation of retrieving goods from specified storage locations based on customer orders, order picking to provide more flexible planning and predictive analysis in the warehouse and distribution center. This study focuses specifically on a web-based interactive AI order picking optimization tool for data manipulation. The AI-based data manipulation tool has a mainspring effect on warehouse performance to get a robust dynamic order picking operation that allows for changes of picking lists during a picking cycle in the warehouse.",

keywords = "Artificial intelligence solutions, Data manipulation, Order picking operation, Order picking optimisation, Smart warehouse",

author = "Nihal Er and Cidal, \{Gizem Melike\} and Simge {\"U}nsal and {\c C}akır, \{Muammer Altan\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2021 ; Conference date: 24-08-2021 Through 26-08-2021",

year = "2022",

doi = "10.1007/978-3-030-85626-7\_108",

language = "English",

isbn = "9783030856250",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "929--936",

editor = "Cengiz Kahraman and Selcuk Cebi and \{Cevik Onar\}, Sezi and Basar Oztaysi and Tolga, \{A. Cagri\} and Sari, \{Irem Ucal\}",

booktitle = "Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference",

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Er, N, Cidal, GM, Ünsal, S & Çakır, MA 2022, Enabling Big Data Analytics and AI Solutions for Smart Warehouse. in C Kahraman, S Cebi, S Cevik Onar, B Oztaysi, AC Tolga & IU Sari (eds), Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference. Lecture Notes in Networks and Systems, hac. 307, Springer Science and Business Media Deutschland GmbH, pp. 929-936, International Conference on Intelligent and Fuzzy Systems, INFUS 2021, Istanbul, Türkiye, 24/08/21. https://doi.org/10.1007/978-3-030-85626-7_108

Enabling Big Data Analytics and AI Solutions for Smart Warehouse. / Er, Nihal; Cidal, Gizem Melike; Ünsal, Simge et al.
Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference. ed. / Cengiz Kahraman; Selcuk Cebi; Sezi Cevik Onar; Basar Oztaysi; A. Cagri Tolga; Irem Ucal Sari. Springer Science and Business Media Deutschland GmbH, 2022. p. 929-936 (Lecture Notes in Networks and Systems; Hac. 307).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

TY - GEN

T1 - Enabling Big Data Analytics and AI Solutions for Smart Warehouse

AU - Er, Nihal

AU - Cidal, Gizem Melike

AU - Ünsal, Simge

AU - Çakır, Muammer Altan

PY - 2022

Y1 - 2022

N2 - Today’s warehouse processes require more flexibility than conventional methods in behalf of greater responsiveness to customer orders. The improvement of a smart warehouse strategy through the use of big data technologies and AI, including smart data collection and data manipulation tools, to improve warehouse efficiency and productivity is a popular discussion topic. AI-based data manipulation techniques are used to categorize the types of optimal input for the operation of retrieving goods from specified storage locations based on customer orders, order picking to provide more flexible planning and predictive analysis in the warehouse and distribution center. This study focuses specifically on a web-based interactive AI order picking optimization tool for data manipulation. The AI-based data manipulation tool has a mainspring effect on warehouse performance to get a robust dynamic order picking operation that allows for changes of picking lists during a picking cycle in the warehouse.

AB - Today’s warehouse processes require more flexibility than conventional methods in behalf of greater responsiveness to customer orders. The improvement of a smart warehouse strategy through the use of big data technologies and AI, including smart data collection and data manipulation tools, to improve warehouse efficiency and productivity is a popular discussion topic. AI-based data manipulation techniques are used to categorize the types of optimal input for the operation of retrieving goods from specified storage locations based on customer orders, order picking to provide more flexible planning and predictive analysis in the warehouse and distribution center. This study focuses specifically on a web-based interactive AI order picking optimization tool for data manipulation. The AI-based data manipulation tool has a mainspring effect on warehouse performance to get a robust dynamic order picking operation that allows for changes of picking lists during a picking cycle in the warehouse.

KW - Artificial intelligence solutions

KW - Data manipulation

KW - Order picking operation

KW - Order picking optimisation

KW - Smart warehouse

UR - https://www.scopus.com/pages/publications/85115072834

U2 - 10.1007/978-3-030-85626-7_108

DO - 10.1007/978-3-030-85626-7_108

M3 - Conference contribution

AN - SCOPUS:85115072834

SN - 9783030856250

T3 - Lecture Notes in Networks and Systems

SP - 929

EP - 936

BT - Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference

A2 - Kahraman, Cengiz

A2 - Cebi, Selcuk

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Tolga, A. Cagri

A2 - Sari, Irem Ucal

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2021

Y2 - 24 August 2021 through 26 August 2021

ER -

Er N, Cidal GM, Ünsal S, Çakır MA. Enabling Big Data Analytics and AI Solutions for Smart Warehouse. In Kahraman C, Cebi S, Cevik Onar S, Oztaysi B, Tolga AC, Sari IU, editörler, Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference. Springer Science and Business Media Deutschland GmbH. 2022. p. 929-936. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-85626-7_108

Enabling Big Data Analytics and AI Solutions for Smart Warehouse

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap