Concept of a Voice-Enabled Digital Assistant for Predictive Maintenance in Manufacturing

8 Pages Posted: 26 Oct 2020

See all articles by Stefan Wellsandt

Stefan Wellsandt

Bremer Institut für Produktion und Logistik GmbH

Zoltan Rusak

Delft University of Technology

Santiago Ruiz Arenas

Delft University of Technology

Doris Aschenbrenner

Delft University of Technology

Karl A. Hribernik

Bremer Institut für Produktion und Logistik GmbH

Klaus-Dieter Thoben

Bremer Institut für Produktion und Logistik GmbH

Date Written: October 23, 2020

Abstract

Voice-enabled assistants, such as Alexa and Google Assistant, are among the fastest-growing information technology applications. Their technological foundation matured over the last years and reached a point where new application areas in challenging business environments become a certainty. Maintenance in manufacturing is one of these areas. This paper presents expectations, requirements, and a concept for a voice-enabled digital intelligent assistant that supports maintenance activities. We identified process monitoring, task execution, reporting, problem-solving, and maintenance planning as the key functional modules for an assistant. Realizing them depends on basic, utility, and maintenance functions. Our discussion states that all fundamental technologies and tools to realize an assistant for maintenance exist, but they have constraints. For instance, Speech-to-Text mechanisms lack transparent and performant solutions, and natural language understanding must rely on small datasets, which is challenging. We argue that continuous improvement and systematic evaluation of an assistant prototype is important to create high-quality training data. Trial-and-error is common because some technologies still mature, and conversation designers lack design patterns for the maintenance domain. Challenges for system adoption include providing an outstanding user experience, handling factory-specific jargon, and the limited availability of easy-to-use data exchange interfaces for machines and business applications. We conclude that further efforts on interoperability, technology stack management, AI-focused change management, and education programs are necessary. Furthermore, the accountability of AI systems is a cost factor for the assistant’s service providers and the client companies in manufacturing – AI insurance services, human-in-the-loop functions, user training, and professional education are actions to address this issue.

Keywords: Intelligent Assistant; Voice Assistant; Digital Twin; Product Avatar; Maintenance; Manufacturing; Artificial Intelligence

Suggested Citation

Wellsandt, Stefan and Rusak, Zoltan and Ruiz Arenas, Santiago and Aschenbrenner, Doris and Hribernik, Karl A. and Thoben, Klaus-Dieter, Concept of a Voice-Enabled Digital Assistant for Predictive Maintenance in Manufacturing (October 23, 2020). TESConf 2020 - 9th International Conference on Through-life Engineering Services, Available at SSRN: https://ssrn.com/abstract=3718008 or http://dx.doi.org/10.2139/ssrn.3718008

Stefan Wellsandt (Contact Author)

Bremer Institut für Produktion und Logistik GmbH ( email )

Zoltan Rusak

Delft University of Technology

Stevinweg 1
Stevinweg 1
Delft, 2628 CN
Netherlands

Santiago Ruiz Arenas

Delft University of Technology

Stevinweg 1
Stevinweg 1
Delft, 2628 CN
Netherlands

Doris Aschenbrenner

Delft University of Technology

Stevinweg 1
Stevinweg 1
Delft, 2628 CN
Netherlands

Karl A. Hribernik

Bremer Institut für Produktion und Logistik GmbH

Klaus-Dieter Thoben

Bremer Institut für Produktion und Logistik GmbH

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