In 2018, we announced the establishment of the QREI's Best Paper Award. The plan is to pick the best among papers published in 2019 and repeat the process annually. QREI published a total of 172 papers in 2019, and it would be a challenging task for judges to go through all the papers. In view of this, we shortlisted seven papers (the initial plan was eight but ended with seven), and a panel of judges was invited to provide their assessments and comments. We are very grateful that a panel of very distinguished international colleagues had provided their inputs. They were requested to give scores in three aspects for each paper, that is, contribution, quality, and impact. We would like to take this opportunity to thank all the judges; they are as follows (in alphabetical order of their last name).

Prof. Frank Coolen of Durham University

Prof. Enrique Del Castillo of Penn State University

Prof. Marcus Perry of University of Alabama

Prof. Fugee Tsung of HKUST

Prof. Bill Woodall of Virginia Tech

Prof. Enrico Zio of Politecnico di Milano

Our judges not only gave very insightful comments and assessments but also pointed out that the list of papers is quite diverse, and we are not comparing apple with apple. Professor Woodall, who has been on QREI's editorial board for many years, suggested that instead of selecting only the best paper, it would be fairer (and easier to make the call) to select one in each of the three areas, namely, SPC, DOE, and reliability. While we agree that this is a good suggestion, the number of papers shortlisted may be too few as the initial plan was to select only one. The scoring of these papers continued as planned, and other judges were not aware of the suggestion.

When the inputs from the panel were collated and the scores were tallied, we faced another challenge. The views were not quite aligned, and there were three papers that had almost the same total scores. Upon closer examination, the three papers fall under each of the above areas of SPC, DOE, and reliability. It seemed that an invisible force has drawn us towards implementing the suggestion by Bill, that is, awarding a best paper, respectively, in SPC, DOS, and reliability. The decision to proceed with the best paper award for each area is unanimous and supported by Wiley. Here are the winners and the respective narrative of their contribution and impact.

QREI's Best Paper Award 2020 in Statistical Process Control:

Detecting the process changes for multivariate nonlinear profile data by Jeh‐Nan Pan, Chung‐I Li, and Meng Zhe brings Lu.

This paper brings modern statistical inference into process control by addressing an interesting problem of considerable interest in some production environments, such as Chemical Processes, that is, how to do SPC when you not only have one but many profile responses which are nonlinear. The authors convincingly develop a methodology for using nonparametric models (SVRs based on a radial basis function nonlinearity) to model the profiles and use state‐of‐the‐art rank based, nonparametric charts with controllable in‐control ARL depending on the phase I data set for SPC. The paper also presents nice realistic example. It is original and of practical impact in a digitalized industrial environment.

QREI's Best Paper Award 2020 in Reliability

Robustness of asymptotic accelerated life test plans to small‐sample settings by Caleb King.

This paper addresses an interesting issue in ALT as most ALT tests use asymptotic approximation for the of the prediction at use conditions, and the author presents a new method for ALT test design that is not based on asymptotic results. They then use this model to compare their solutions to those obtained by the usual asymptotic designs. It is shown that the design and analysis using asymptotic results are actually quite good. While in terms of “impact,” it does not influence the current practice, it addresses an important robustness question of the prevailing practice, and thus, it scores high in terms of contribution. Extensive simulations have been conducted to verify the superiority of the method, and some proofs of related theories are presented.

QREI's Best Paper Award 2020 in Design of Experiments

Using a genetic algorithm to generate D‐optimal designs for mixture‐process variable experiments by Wasinee Pradubsri, Boonorm Chomtee, and John J. Borkowski.

This paper uses modern optimization method in addressing a commonly encountered problem of process‐mixture designs. It scores high in terms of practical impact as such design is very useful in the industry especially in the pharmaceutical sector as it includes mixture‐amount designs as a special case. The paper presents some interesting examples to illustrate the applicability of the proposed method. The coding algorithm is available from the authors. Its impact will be felt even more in digitalized manufacturing.

Please join me in congratulating the authors of the above papers for their accomplishments, and we are grateful that they have chosen QREI as the outlet for their research work. All authors will be given 1 year of free online access to QREI, and these papers can be accessed freely online to help in promoting the research by the authors.

We hope that the best has yet to come, and we look forward to receiving more of your excellent work.

Co‐Editors‐in Chief

Loon Ching Tang, on behalf of Aarnout Brombacher and Doug Montgomery