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ABSTRACT
This article optimizes an injection molding process using an efficient sequential design methodology. The goal is to set the process control variables to minimize the shrinkages of a selected collection of injection molded parts. This multiobjective optimization problem is solved by finding those process control variable settings that are Pareto minimizing values (i.e., process settings for which none of the shrinkages of the parts can be decreased by an alternative process setting without increasing the shrinkages of other parts). The sequential design uses an expected improvement criterion to guide updates. The shrinkages are estimated by a calibrated predictor of the process mean shrinkage. The calibration is based on observations of the manufacturing process supplemented by computer runs of a commercial simulator code that mimics the manufacturing process.
About the authors
Dr. Po-Hsu Allen Chen is a research statistician at Battelle, Columbus. His statistical skills include design of experiments, optimization of multiobjective problems, clustering and visualization for high-dimensional data, and computer experiments.
Dr. María Villarreal-Marroquin is a researcher whose interests include mathematical and statistical modeling for multiple objective optimizations and simulation of manufacturing processes, as well as statistical analysis of massive and complex datasets.
Dr. Angela M. Dean is Professor Emeritus of Statistics. Her research focuses on design for experiments that involve many factors but require small budgets, especially in the manufacturing industries and in engineering.
Dr. Thomas J. Santner is Professor Emeritus of Statistics. His research interests include the design of experiments. His most recent work involves the use of computer simulators as experimental platforms, either alone or in combination with a traditional physical experiments.
Dr. Rachmat Mulyana is an instructional technology specialist. His research interests include the optimization of plastic manufacturing processes.
Dr. José M. Castro is Full Professor in the Department of Integrated Systems Engineering. His research focuses on modeling and optimization of industrial processes, and the development of novel environmentally friendly alternatives to current processes. His research groups' areas of expertise include sheet molding compound compression molding, in-mold coatings, reactive liquid molding, and injection molding.
Additional information
Funding
Notes on contributors
Po-Hsu Allen Chen
Dr. Po-Hsu Allen Chen is a research statistician at Battelle, Columbus. His statistical skills include design of experiments, optimization of multiobjective problems, clustering and visualization for high-dimensional data, and computer experiments.
María G. Villarreal-Marroquín
Dr. María G. Villarreal-Marroquín is a researcher whose interests include mathematical and statistical modeling for multiple objective optimizations and simulation of manufacturing processes, as well as statistical analysis of massive and complex datasets.
Angela M. Dean
Dr. Angela M. Dean is Professor Emeritus of Statistics. Her research focuses on design for experiments that involve many factors but require small budgets, especially in the manufacturing industries and in engineering.
Thomas J. Santner
Dr. Thomas J. Santner is Professor Emeritus of Statistics. His research interests include the design of experiments. His most recent work involves the use of computer simulators as experimental platforms, either alone or in combination with a traditional physical experiments.
Rachmat Mulyana
Dr. Rachmat Mulyana is an instructional technology specialist. His research interests include the optimization of plastic manufacturing processes.
José M. Castro
Dr. José M. Castro is Full Professor in the Department of Integrated Systems Engineering. His research focuses on modeling and optimization of industrial processes, and the development of novel environmentally friendly alternatives to current processes. His research groups' areas of expertise include sheet molding compound compression molding, in-mold coatings, reactive liquid molding, and injection molding.