ABSTRACT
Engineers may be technically competent; however, some lack the communication skills necessary to transfer information and reason. This situation makes excellent technical skills superfluous. In this paper, communication is reviewed from a reliability engineering viewpoint, discussing why conveying well-crafted information to decision-makers is pivotal to success. Firstly, the authors examine several engineering communication myths. The authors then present how good communication fundamentals can be used to meet the decision-maker requirements leading to the desired engineering outcomes. Next, the authors narrow the scope to examine presenting reliability growth plans and their associated risk to decision-makers from a reliability engineering perspective. The paper concludes with an analysis of the robustness of reliability estimates and why distribution or interval estimators should always be preferable to point estimators when describing reliability metrics. While the paper focuses on reliability engineering practitioners and their efforts, the content is helpful for other engineering specialists when considering communication.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. Management strategy: The proportion of the rate of occurrence of failures due to failure modes that would receive corrective action if surfaced during the developmental test program (US Dept of Defense Citation2011).
2. Fix effectiveness factor: A fraction representing the reduction in an individual mode failure rate due to the implementation of a corrective action (US Dept of Defense Citation2011).
3. Confidence limit: Confidence limits for the mean are an interval estimate for the mean (Sneddor and Cochrane Citation1989). Interval estimates are often desirable because the estimate of the mean varies from sample to sample. Instead of a single estimate for the mean, a confidence interval generates a lower and upper limit for the mean. The interval estimate gives an indication of how much uncertainty there is in our estimate of the true mean.
4. Now known as the US Army Combat Capabilities Data and Analysis Center.
Additional information
Notes on contributors
Paul Nation
Paul Nation works within the Australian Department of Defence as an internal test and evaluation consultant and senior reliability and maintenance engineer. In this role, he provides reliability consulting support to various organisations and programs within the Defence land domain. He holds a BEng in Automotive Engineering from RMIT University and an MSc in Reliability Engineering from the University of Maryland. He is currently a PhD candidate undertaking research on Bayesian approach application to discrete-use system reliability growth planning.
Martin Wayne
Martin Wayne leads the Center for Reliability Growth within the US Army Combat Capabilities Development Command Data and Analysis Center, Aberdeen Proving Ground, Maryland (previously the Army Materiel Systems Analysis Activity, AMSAA). In this role, he provides reliability engineering support to various government and US Defense organisations. Doctor Wayne received his MSc in Applied Mathematics from Johns Hopkins University and his PhD in Reliability Engineering from the University of Maryland.
Mohammad Modarres
Mohammad Modarres is a scientist and educator in the fields of nuclear and reliability engineering. He is a Distinguished Scholar and Nicole Y. Kim Eminent Professor of the University of Maryland. Within the A. James Clark School of Engineering, he founded the world’s first graduate curriculum in reliability engineering. As the University of Maryland Center for Risk and Reliability Director, Professor Modarres serves as an international expert on reliability and risk analysis. A PhD graduate of the Massachusetts Institute of Technology, he has authored numerous books and hundreds of scholarly papers on nuclear and reliability engineering.