Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing

Mihai Penica; Mangolika Bhattacharya; William O'Brien; Sean McGrath; Martin Hayes; Eoin O'Connell

doi:10.1109/iCCECE59400.2023.10238531

Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing

Mihai Penica
, Mangolika Bhattacharya
, William O'Brien
, Sean McGrath
, Martin Hayes
, Eoin O'Connell

University of Limerick

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In the context of Industry 4.0, the training of operators can be improved through the use of real-Time chatbot interfaces that provide expedient and focused information. This paper explores the incorporation of a chatbot-based interface within an industrial context, specifically through the development and implementation of an innovative immersive augmented reality (AR) consultation chatbot system. This system utilizes smart glass interfaces and different interoperable industrial internet of Things (IIoT) devices to empower operators with real-Time information and enhance decision-making in manufacturing processes. The system emphasizes interoperability and has the potential for application across diverse production floor settings. Initial feedback from a pilot study is presented, and suggestions for widespread integration of such interfaces in smart manufacturing environments are put forward. The presented proof of concept demonstrates the potential for chatbot-based interfaces to enhance operator training applications in Industry 4.0.

Original language	English
Title of host publication	Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023
Editors	Mahdi H. Miraz, Garfield Southall, Maaruf Ali, Andrew Ware, Carlene Campbell, Terry Walcott
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	23-29
Number of pages	7
ISBN (Electronic)	9798350340921
DOIs	https://doi.org/10.1109/iCCECE59400.2023.10238531
Publication status	Published - 2023
Event	6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023 - Swansea, United Kingdom Duration: 14 Aug 2023 → 16 Aug 2023

Publication series

Name	Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023

Conference

Conference	6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023
Country/Territory	United Kingdom
City	Swansea
Period	14/08/23 → 16/08/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

(IIoT)
Augmented reality (AR)
Chatbots
Industrial Internet of Things
Industry 4.0
Intelligent agents
Interoperability
Natural Language Processing (NLP)
Operator 4.0
Smart Manufacturing
Smart Warehousing

Access to Document

10.1109/iCCECE59400.2023.10238531

Cite this

Penica, M., Bhattacharya, M., O'Brien, W., McGrath, S., Hayes, M., & O'Connell, E. (2023). Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing. In M. H. Miraz, G. Southall, M. Ali, A. Ware, C. Campbell, & T. Walcott (Eds.), Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023 (pp. 23-29). (Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/iCCECE59400.2023.10238531

Penica, Mihai ; Bhattacharya, Mangolika ; O'Brien, William et al. / Adaptable Decision Making Chatbot System : Unlocking Interoperability in Smart Manufacturing. Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023. editor / Mahdi H. Miraz ; Garfield Southall ; Maaruf Ali ; Andrew Ware ; Carlene Campbell ; Terry Walcott. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 23-29 (Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023).

@inproceedings{115d3f83a8dd449d88b9813df725b862,

title = "Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing",

abstract = "In the context of Industry 4.0, the training of operators can be improved through the use of real-Time chatbot interfaces that provide expedient and focused information. This paper explores the incorporation of a chatbot-based interface within an industrial context, specifically through the development and implementation of an innovative immersive augmented reality (AR) consultation chatbot system. This system utilizes smart glass interfaces and different interoperable industrial internet of Things (IIoT) devices to empower operators with real-Time information and enhance decision-making in manufacturing processes. The system emphasizes interoperability and has the potential for application across diverse production floor settings. Initial feedback from a pilot study is presented, and suggestions for widespread integration of such interfaces in smart manufacturing environments are put forward. The presented proof of concept demonstrates the potential for chatbot-based interfaces to enhance operator training applications in Industry 4.0.",

keywords = "(IIoT), Augmented reality (AR), Chatbots, Industrial Internet of Things, Industry 4.0, Intelligent agents, Interoperability, Natural Language Processing (NLP), Operator 4.0, Smart Manufacturing, Smart Warehousing",

author = "Mihai Penica and Mangolika Bhattacharya and William O'Brien and Sean McGrath and Martin Hayes and Eoin O'Connell",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023 ; Conference date: 14-08-2023 Through 16-08-2023",

year = "2023",

doi = "10.1109/iCCECE59400.2023.10238531",

language = "English",

series = "Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "23--29",

editor = "Miraz, \{Mahdi H.\} and Garfield Southall and Maaruf Ali and Andrew Ware and Carlene Campbell and Terry Walcott",

booktitle = "Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023",

}

Penica, M, Bhattacharya, M, O'Brien, W, McGrath, S , Hayes, M & O'Connell, E 2023, Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing. in MH Miraz, G Southall, M Ali, A Ware, C Campbell & T Walcott (eds), Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023. Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023, Institute of Electrical and Electronics Engineers Inc., pp. 23-29, 6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023, Swansea, United Kingdom, 14/08/23. https://doi.org/10.1109/iCCECE59400.2023.10238531

Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing. / Penica, Mihai; Bhattacharya, Mangolika; O'Brien, William et al.
Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023. ed. / Mahdi H. Miraz; Garfield Southall; Maaruf Ali; Andrew Ware; Carlene Campbell; Terry Walcott. Institute of Electrical and Electronics Engineers Inc., 2023. p. 23-29 (Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adaptable Decision Making Chatbot System

T2 - 6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023

AU - Penica, Mihai

AU - Bhattacharya, Mangolika

AU - O'Brien, William

AU - McGrath, Sean

AU - Hayes, Martin

AU - O'Connell, Eoin

PY - 2023

Y1 - 2023

N2 - In the context of Industry 4.0, the training of operators can be improved through the use of real-Time chatbot interfaces that provide expedient and focused information. This paper explores the incorporation of a chatbot-based interface within an industrial context, specifically through the development and implementation of an innovative immersive augmented reality (AR) consultation chatbot system. This system utilizes smart glass interfaces and different interoperable industrial internet of Things (IIoT) devices to empower operators with real-Time information and enhance decision-making in manufacturing processes. The system emphasizes interoperability and has the potential for application across diverse production floor settings. Initial feedback from a pilot study is presented, and suggestions for widespread integration of such interfaces in smart manufacturing environments are put forward. The presented proof of concept demonstrates the potential for chatbot-based interfaces to enhance operator training applications in Industry 4.0.

AB - In the context of Industry 4.0, the training of operators can be improved through the use of real-Time chatbot interfaces that provide expedient and focused information. This paper explores the incorporation of a chatbot-based interface within an industrial context, specifically through the development and implementation of an innovative immersive augmented reality (AR) consultation chatbot system. This system utilizes smart glass interfaces and different interoperable industrial internet of Things (IIoT) devices to empower operators with real-Time information and enhance decision-making in manufacturing processes. The system emphasizes interoperability and has the potential for application across diverse production floor settings. Initial feedback from a pilot study is presented, and suggestions for widespread integration of such interfaces in smart manufacturing environments are put forward. The presented proof of concept demonstrates the potential for chatbot-based interfaces to enhance operator training applications in Industry 4.0.

KW - (IIoT)

KW - Augmented reality (AR)

KW - Chatbots

KW - Industrial Internet of Things

KW - Industry 4.0

KW - Intelligent agents

KW - Interoperability

KW - Natural Language Processing (NLP)

KW - Operator 4.0

KW - Smart Manufacturing

KW - Smart Warehousing

UR - https://www.scopus.com/pages/publications/85172880975

U2 - 10.1109/iCCECE59400.2023.10238531

DO - 10.1109/iCCECE59400.2023.10238531

M3 - Conference contribution

AN - SCOPUS:85172880975

T3 - Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023

SP - 23

EP - 29

BT - Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023

A2 - Miraz, Mahdi H.

A2 - Southall, Garfield

A2 - Ali, Maaruf

A2 - Ware, Andrew

A2 - Campbell, Carlene

A2 - Walcott, Terry

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 14 August 2023 through 16 August 2023

ER -

Penica M, Bhattacharya M, O'Brien W, McGrath S , Hayes M , O'Connell E. Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing. In Miraz MH, Southall G, Ali M, Ware A, Campbell C, Walcott T, editors, Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 23-29. (Proceedings - 2023 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023). doi: 10.1109/iCCECE59400.2023.10238531

Adaptable Decision Making Chatbot System: Unlocking Interoperability in Smart Manufacturing

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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