From natural language text to rules: knowledge acquisition from formal documents for aircraft assembly

Abstract

Knowledge acquisition is a well-acknowledged bottleneck in the building of knowledge-based systems. Documents are a useful source of knowledge from experts. This paper targets the reuse of knowledge from the assembly phase of a product in the design and planning phases. Issues, their causes and the parameters involved are necessary to be acquired for reusing the knowledge so acquired. This paper discusses a method for knowledge acquisition, as a pipeline of existing tools in natural language understanding and processing. The acquired knowledge is expected to help in the decision making for a smart manufacturing system. The process of knowledge acquisition involves recognising the presence of issues and their causes using a combination of sentiment analysis and text patterns. The causes are then dissected to identify the constraints and constituent parameters. These pieces of knowledge are then reconstructed to form rules in a knowledge base. This paper demonstrates progress towards realising the method, by developing the cause dissection and rule-writing components, and validation of the issue-cause acquisition component with human subjects. A discussion is then presented on the potential integration and validation of the overall knowledge acquisition pipeline with a smart manufacturing system.

KEYWORDS:

• Knowledge acquisition
• natural language text
• aircraft assembly

Acknowledgements

The authors wish to thank all the test subjects who participated in the reading exercises.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

N. Madhusudanan http://orcid.org/0000-0003-3086-7003

Balan Gurumoorthy http://orcid.org/0000-0001-9857-9011

Amaresh Chakrabartihttp://orcid.org/0000-0002-1809-1831