User-Friendly MES Interfaces: Recommendations for an AI-Based Chatbot Assistance in Industry 4.0 Shop Floors

Mantravadi, Soujanya; Jansson, Andreas Dyrøy; Møller, Charles

doi:10.1007/978-3-030-42058-1_16

Cited by 17 publications

(19 citation statements)

References 25 publications

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“…In addition, artificial intelligence is potentially useful in supporting consumers about shopping (Pizzi, et al, 2021). In the manufacturing sector, chatbots can be used for technical assistance (Mantravadi, et al, 2020). By considering e-commerce platforms, the online chatbot is a good channel for customer communication and assistance (Landim, et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Text Mining Approaches Oriented on Customer Care Efficiency

Massaro¹,

Magaletti²,

Cosoli³

et al. 2022

Preprint

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In the proposed work is performed a text classification for a chatbot application used by a company working in assistance services of automatic warehouses. industries. Specifically, text mining technique is adopted for the classification of questions and answers. Business Process Modeling Notation (BPMN) models describe the passage from “AS-IS” to “TO BE” in the context of the analyzed industry, by focusing the attention mainly on customer and technical support services where chatbot is adopted. A two-step process model is used to connect technological improvements and relationship marketing in chatbot assistance: the first step provides the hierarchical clustering able to classify questions and answers through Latent Dirichlet Allocation -LDA- algorithm, and the second one executes the Tag Cloud representing the visual representation of more frequent words contained in the experimental dataset. Tag cloud is used to show the critical issues that customers find in the usage of the proposed service. By considering an initial dataset, 24 hierarchical clusters are found representing the preliminary combination of the couple’s question-answer. The proposed approach is suitable to automatically construct a combination of chatbot questions and appropriate answers in intelligent systems.

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Section: Literature Reviewmentioning

confidence: 99%

Text Mining Approaches Oriented on Customer Care Efficiency

Massaro¹,

Magaletti²,

Cosoli³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In [7], a chatbot was developed to aid new hires through their onboarding process and meets related information needs as if it were a human assistant. In [17], a chatbot has been integrated within a MES (Manufacturing Execution System) to provide technical assistance for shop floor operators, for predictive maintenance purposes. The paper [31] proposes the idea of chatbots as virtual assistants to help shop floor workers in learning assembly tasks in the manufacturing domain.…”

Section: Related Workmentioning

confidence: 99%

aCHAT-WF: Generating conversational agents for teaching business process models

et al. 2021

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This paper proposes a general approach for using conversational interfaces such as chatbots to offer adaptive learning of business processes in an environment involving different actors. Adaptivity concerns both the content being proposed, the sequence of learning items, and the way the conversation is conducted. The original approach allows the development of sustainable chatbots and empowers various non-technical actors (authors, teachers, publishers, and learners) to control the chatbot features directly. The aCHAT-WF framework (adaptive CHATbot for WorkFlows), proposed in this paper for managing conversational interfaces, conceptually represents all the aspects related to a conversation about business processes, with different facets for the user, the conversation flow, and the conversation contents, combining them to obtain a flexible interaction with the user. The paper focuses on the different preparation phases for instructional material based on Business Process Modeling Notation (BPMN) models, separating the different roles involved in the construction of a chatbot for teaching business processes and with the possibility of defining different styles for the interaction with the users. The proposed method is configuration-driven, to facilitate the separation of the different aspects of the control of the interaction and the delivery of contents.

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“…Fig. 20: Assessment of a conversational MES interface for order management [44] We present architectural recommendations for AI-based chatbot assistance in Industry 4.0 shop floors based on this.…”

Section: Discussionmentioning

confidence: 99%

“…• Paper 5 studies the Industry 4.0 scenario of technical assistance and applies MES/MOM for information retrieval by accommodating a chatbot interface layer to the MES architecture. The interface layer uses natural language processing to add predictive power to MES and improve the efficiency of the processes MES/MOM is intended to support [44].…”

Section: Thesis Structurementioning

confidence: 99%

“…[79] By contrast, research on the user aspect of MES/MOM is limited. This is despite the fact that MES/MOM is intended to interact with human users to aid them in smooth production management [80,44]. However, the production workforce can make informed decisions with the help of AI-based intuitive assistant systems, such as chatbots for EIS.…”

Section: Knowledge Managementmentioning

confidence: 99%

See 1 more Smart Citation

Enabling the Smart Factory with Industrial Internet of Things-Connected MES/MOM

Mantravadi¹

Self Cite

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User-Friendly MES Interfaces: Recommendations for an AI-Based Chatbot Assistance in Industry 4.0 Shop Floors

Cited by 17 publications

References 25 publications

Text Mining Approaches Oriented on Customer Care Efficiency

Text Mining Approaches Oriented on Customer Care Efficiency

aCHAT-WF: Generating conversational agents for teaching business process models

Enabling the Smart Factory with Industrial Internet of Things-Connected MES/MOM

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