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Ludwig H, Kühn M, Schmidt T (2023). When voice assistants take hold: How smart technology makes goods receipt more efficient. Logistics Journal : Proceedings, Vol. 2023. (urn:nbn:de:0009-14-58111)

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%0 Journal Article
%T When voice assistants take hold: How smart technology makes goods receipt more efficient
%A Ludwig, Heiner
%A Kühn, Mathias
%A Schmidt, Thorsten
%J Logistics Journal : Proceedings
%D 2023
%V 2023
%N 1
%@ 2192-9084
%F ludwig2023
%X Goods receipt is an essential step in supply chains. It is often performed manually by warehouse staff. They are confronted with challenges such as time pressure, missing goods, wrong quantities, damages and incomplete documents. To support the workers in the best possible way, digital assistance systems are suitable. The study aims to investigate the potential of voice assistance in various processes of goods receipt. These include verbal identification of incoming goods and interactive guidance in quality control. Technical requirements will be defined, an adaptive data structure will be presented, and a novel neural network will be trained for multiple inputs. Finally, two example scenarios are evaluated and compared with currently used methods and tools.
%L 620
%K Wareneingang
%K Sprachassistent
%K Natürliche Sprachdatenverarbeitung
%K goods receipt
%K voice assistant
%K natural language processing
%R 10.2195/lj_proc_ludwig_en_202310_01
%U http://nbn-resolving.de/urn:nbn:de:0009-14-58111
%U http://dx.doi.org/10.2195/lj_proc_ludwig_en_202310_01
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Bibtex

@Article{ludwig2023,
  author = 	"Ludwig, Heiner
		and K{\"u}hn, Mathias
		and Schmidt, Thorsten",
  title = 	"When voice assistants take hold: How smart technology makes goods receipt more efficient",
  journal = 	"Logistics Journal : Proceedings",
  year = 	"2023",
  volume = 	"2023",
  number = 	"1",
  keywords = 	"Wareneingang; Sprachassistent; Nat{\"u}rliche Sprachdatenverarbeitung; goods receipt; voice assistant; natural language processing",
  abstract = 	"Goods receipt is an essential step in supply chains. It is often performed manually by warehouse staff. They are confronted with challenges such as time pressure, missing goods, wrong quantities, damages and incomplete documents. To support the workers in the best possible way, digital assistance systems are suitable. The study aims to investigate the potential of voice assistance in various processes of goods receipt. These include verbal identification of incoming goods and interactive guidance in quality control. Technical requirements will be defined, an adaptive data structure will be presented, and a novel neural network will be trained for multiple inputs. Finally, two example scenarios are evaluated and compared with currently used methods and tools.",
  issn = 	"2192-9084",
  doi = 	"10.2195/lj_proc_ludwig_en_202310_01",
  url = 	"http://nbn-resolving.de/urn:nbn:de:0009-14-58111"
}
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RIS

TY  - JOUR
AU  - Ludwig, Heiner
AU  - Kühn, Mathias
AU  - Schmidt, Thorsten
PY  - 2023
DA  - 2023//
TI  - When voice assistants take hold: How smart technology makes goods receipt more efficient
JO  - Logistics Journal : Proceedings
VL  - 2023
IS  - 1
KW  - Wareneingang
KW  - Sprachassistent
KW  - Natürliche Sprachdatenverarbeitung
KW  - goods receipt
KW  - voice assistant
KW  - natural language processing
AB  - Goods receipt is an essential step in supply chains. It is often performed manually by warehouse staff. They are confronted with challenges such as time pressure, missing goods, wrong quantities, damages and incomplete documents. To support the workers in the best possible way, digital assistance systems are suitable. The study aims to investigate the potential of voice assistance in various processes of goods receipt. These include verbal identification of incoming goods and interactive guidance in quality control. Technical requirements will be defined, an adaptive data structure will be presented, and a novel neural network will be trained for multiple inputs. Finally, two example scenarios are evaluated and compared with currently used methods and tools.
SN  - 2192-9084
UR  - http://nbn-resolving.de/urn:nbn:de:0009-14-58111
DO  - 10.2195/lj_proc_ludwig_en_202310_01
ID  - ludwig2023
ER  -
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Wordbib

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ISI

PT Journal
AU Ludwig, H
   Kühn, M
   Schmidt, T
TI When voice assistants take hold: How smart technology makes goods receipt more efficient
SO Logistics Journal : Proceedings
PY 2023
VL 2023
IS 1
DI 10.2195/lj_proc_ludwig_en_202310_01
DE Wareneingang; Sprachassistent; Natürliche Sprachdatenverarbeitung; goods receipt; voice assistant; natural language processing
AB Goods receipt is an essential step in supply chains. It is often performed manually by warehouse staff. They are confronted with challenges such as time pressure, missing goods, wrong quantities, damages and incomplete documents. To support the workers in the best possible way, digital assistance systems are suitable. The study aims to investigate the potential of voice assistance in various processes of goods receipt. These include verbal identification of incoming goods and interactive guidance in quality control. Technical requirements will be defined, an adaptive data structure will be presented, and a novel neural network will be trained for multiple inputs. Finally, two example scenarios are evaluated and compared with currently used methods and tools.
ER
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Mods

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  <abstract>Goods receipt is an essential step in supply chains. It is often performed manually by warehouse staff. They are confronted with challenges such as time pressure, missing goods, wrong quantities, damages and incomplete documents. To support the workers in the best possible way, digital assistance systems are suitable. The study aims to investigate the potential of voice assistance in various processes of goods receipt. These include verbal identification of incoming goods and interactive guidance in quality control. Technical requirements will be defined, an adaptive data structure will be presented, and a novel neural network will be trained for multiple inputs. Finally, two example scenarios are evaluated and compared with currently used methods and tools.</abstract>
  <subject>
    <topic>Wareneingang</topic>
    <topic>Sprachassistent</topic>
    <topic>Natürliche Sprachdatenverarbeitung</topic>
    <topic>goods receipt</topic>
    <topic>voice assistant</topic>
    <topic>natural language processing</topic>
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Full Metadata

Bibliographic Citation Logistics Journal : referierte Veröffentlichungen, Vol. 2023, Iss. 1
Title

When voice assistants take hold: How smart technology makes goods receipt more efficient (eng)

Wenn Sprachassistenz Einzug hält: Wie smarte Technologie die Effizienz im Wareneingang erhöht (ger)
Author Heiner Ludwig, Mathias Kühn, Thorsten Schmidt
Language eng
Abstract Goods receipt is an essential step in supply chains. It is often performed manually by warehouse staff. They are confronted with challenges such as time pressure, missing goods, wrong quantities, damages and incomplete documents. To support the workers in the best possible way, digital assistance systems are suitable. The study aims to investigate the potential of voice assistance in various processes of goods receipt. These include verbal identification of incoming goods and interactive guidance in quality control. Technical requirements will be defined, an adaptive data structure will be presented, and a novel neural network will be trained for multiple inputs. Finally, two example scenarios are evaluated and compared with currently used methods and tools. Der Wareneingang stellt einen essentiellen Schritt in Lieferketten dar. Dieser wird dabei oftmals von Lageristen manuell durchgeführt, die mit unterschiedlichen Herausforderungen wie Zeitdruck, fehlenden Waren, falsche Mengen, Schäden und unvollständigen Dokumenten konfrontiert sind. Um die Arbeitskräfte bestmöglich zu unterstützen, sind digitale Assistenzsysteme geeignet. In der Studie soll das Potenzial der Sprachassistenz in verschiedenen Prozessen des Wareneingangs untersucht werden. Dazu gehören die verbale Identifikation eingehender Güter und die interaktive Anleitung in der Qualitätskontrolle. Es werden technische Anforderungen definiert, eine lernfähige Datenstruktur vorgestellt und ein neuartiges neuronales Netz für Mehrfacheingaben trainiert. Abschließend werden zwei Beispielszenarien evaluiert und mit derzeitig genutzten Methoden und Werkzeugen verglichen.
Subject Wareneingang, Sprachassistent, Natürliche Sprachdatenverarbeitung, goods receipt, voice assistant, natural language processing
DDC 620
Rights cc-by
URN: urn:nbn:de:0009-14-58111
DOI https://doi.org/10.2195/lj_proc_ludwig_en_202310_01