Conquering the challenge of reliability: text mining to map trends in reliability engineering literature

Reliability engineering faces many of the same challenges in 2023 that it did at its inception in the 1950s. The fundamental issue remains uncertainty in system representation, specifically related to performance model structure and parametrization. Details of a design are unavailable early in the development process and therefore performance models must either account for the range of possibilities or be wrong. Increasing system complexity has compounded this uncertainty. In this work, we seek to understand how reliability engineering literature has changed over time with the assumption that the focus of literature shifts in part due to challenges in the field. Illuminating this change provides reliability practitioners guidance for what they can do in the face of growing complexity. We build this understanding by executing a systematic literature review of 30,543 reliability engineering papers. Topic modeling was performed on the abstracts of those papers to identify 279 topics. Hierarchical topic reduction resulted in the identification of 8 top-level method topics (prognostics, statistics, maintenance, quality control, management, physics of failure, modeling, and risk assessment) as well as 3 domain-specific topics (nuclear, infrastructure, and software). We found that topics more associated with later phases in the development process (such as prognostics, maintenance, and quality control) have increased in popularity over time relative to other topics. We propose that this is a response to the challenges posed by the previously-discussed model uncertainty and increasing complexity. Through zero-shot classification by a large language model, we also found that papers are including more practical examples or case studies and that those topics associated with later phases typically include more practical examples. Thus, while reliability remains fundamentally difficult to predict early in the development process, the field has shifted focus to later-stage and more applicable activities.

Name thesis:degree_name

Master

Department dc:contributor.department

System Design and Management Program.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Brown, Charles K.

Advisor dc:contributor.advisor

• Cameron, Bruce G.

Statement dc:rights

• Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
• Copyright retained by author(s)

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-sa/4.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/151303

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151303