Towards Flexible and Cognitive Production—Addressing the Production Challenges

Globalization in the field of industry is fostering the need for cognitive production systems. To implement modern concepts that enable tools and systems for such a cognitive production system, several challenges on the shop floor level must first be resolved. This paper discusses the implementation...

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Main Authors: Muaaz Abdul Hadi, Daniel Kraus, Amer Kajmakovic, Josef Suschnigg, Ouijdane Guiza, Milot Gashi, Georgios Sopidis, Matej Vukovic, Katarina Milenkovic, Michael Haslgruebler, Markus Brillinger, Konrad Diwold
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/17/8696
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author Muaaz Abdul Hadi
Daniel Kraus
Amer Kajmakovic
Josef Suschnigg
Ouijdane Guiza
Milot Gashi
Georgios Sopidis
Matej Vukovic
Katarina Milenkovic
Michael Haslgruebler
Markus Brillinger
Konrad Diwold
author_facet Muaaz Abdul Hadi
Daniel Kraus
Amer Kajmakovic
Josef Suschnigg
Ouijdane Guiza
Milot Gashi
Georgios Sopidis
Matej Vukovic
Katarina Milenkovic
Michael Haslgruebler
Markus Brillinger
Konrad Diwold
author_sort Muaaz Abdul Hadi
collection DOAJ
description Globalization in the field of industry is fostering the need for cognitive production systems. To implement modern concepts that enable tools and systems for such a cognitive production system, several challenges on the shop floor level must first be resolved. This paper discusses the implementation of selected cognitive technologies on a real industrial case-study of a construction machine manufacturer. The partner company works on the concept of mass customization but utilizes manual labour for the high-variety assembly stations or lines. Sensing and guidance devices are used to provide information to the worker and also retrieve and monitor the working, with respecting data privacy policies. Next, a specified process of data contextualization, visual analytics, and causal discovery is used to extract useful information from the retrieved data via sensors. Communications and safety systems are explained further to complete the loop of implementation of cognitive entities on a manual assembly line. This deepened involvement of cognitive technologies are human-centered, rather than automated systems. The explained cognitive technologies enhance human interaction with the processes and ease the production methods. These concepts form a quintessential vision for an effective assembly line. This paper revolutionizes the existing industry 4.0 with an even-intensified human–machine interaction and moving towards cognitivity.
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spelling doaj.art-1ef71244732a4413ac0f8b4d297d14412023-11-23T12:45:32ZengMDPI AGApplied Sciences2076-34172022-08-011217869610.3390/app12178696Towards Flexible and Cognitive Production—Addressing the Production ChallengesMuaaz Abdul Hadi0Daniel Kraus1Amer Kajmakovic2Josef Suschnigg3Ouijdane Guiza4Milot Gashi5Georgios Sopidis6Matej Vukovic7Katarina Milenkovic8Michael Haslgruebler9Markus Brillinger10Konrad Diwold11Pro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaPro2Future GmbH, 4040 Linz, AustriaGlobalization in the field of industry is fostering the need for cognitive production systems. To implement modern concepts that enable tools and systems for such a cognitive production system, several challenges on the shop floor level must first be resolved. This paper discusses the implementation of selected cognitive technologies on a real industrial case-study of a construction machine manufacturer. The partner company works on the concept of mass customization but utilizes manual labour for the high-variety assembly stations or lines. Sensing and guidance devices are used to provide information to the worker and also retrieve and monitor the working, with respecting data privacy policies. Next, a specified process of data contextualization, visual analytics, and causal discovery is used to extract useful information from the retrieved data via sensors. Communications and safety systems are explained further to complete the loop of implementation of cognitive entities on a manual assembly line. This deepened involvement of cognitive technologies are human-centered, rather than automated systems. The explained cognitive technologies enhance human interaction with the processes and ease the production methods. These concepts form a quintessential vision for an effective assembly line. This paper revolutionizes the existing industry 4.0 with an even-intensified human–machine interaction and moving towards cognitivity.https://www.mdpi.com/2076-3417/12/17/8696smart productionindustry 4.0assembly systemscognitive productionadaptive assemblyhuman–machine interaction
spellingShingle Muaaz Abdul Hadi
Daniel Kraus
Amer Kajmakovic
Josef Suschnigg
Ouijdane Guiza
Milot Gashi
Georgios Sopidis
Matej Vukovic
Katarina Milenkovic
Michael Haslgruebler
Markus Brillinger
Konrad Diwold
Towards Flexible and Cognitive Production—Addressing the Production Challenges
Applied Sciences
smart production
industry 4.0
assembly systems
cognitive production
adaptive assembly
human–machine interaction
title Towards Flexible and Cognitive Production—Addressing the Production Challenges
title_full Towards Flexible and Cognitive Production—Addressing the Production Challenges
title_fullStr Towards Flexible and Cognitive Production—Addressing the Production Challenges
title_full_unstemmed Towards Flexible and Cognitive Production—Addressing the Production Challenges
title_short Towards Flexible and Cognitive Production—Addressing the Production Challenges
title_sort towards flexible and cognitive production addressing the production challenges
topic smart production
industry 4.0
assembly systems
cognitive production
adaptive assembly
human–machine interaction
url https://www.mdpi.com/2076-3417/12/17/8696
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