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

Stefan Wellsandt, Z. Rusak, S. Ruiz Arenas, D. Aschenbrenner, Karl Hibernik, Klaus Dieter Thoben

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


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.
Original languageEnglish
Title of host publicationTESConf 2020 - 9th International Conference on Through-life Engineering Services
Number of pages8
Publication statusPublished - 2020


  • Intelligent Assistant
  • Artificial Intelligence
  • Manufacturing
  • Maintenance
  • Product Avatar
  • Digital Twin
  • Voice Assistant


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