The study of variability in engineering design—An appreciation and a retrospective

We explore the concept of parameter design applied to the production of glass beads in the manufacture of metal-encapsulated transistors. The main motivation is to complete the analysis hinted at in the original publication by Jim Morrison in 1957, which was an early example of discussing the idea of transmitted variation in engineering design, and an influential paper in the development of analytic parameter design as a data-centric engineering activity. Parameter design is a secondary design activity focused on selecting the nominals of the design variables to achieve the required target performance and to simultaneously reduce the variance around the target. Although the 1957 paper is not recent, its approach to engineering design is modern.

Robust Mechanical Design Using Engineering Models

This paper examines how engineering models can be used to develop robust designs—designs that can tolerate variation. Variation is defined in terms of tolerances which bracket the expected deviation of model variables and/or parameters. Several methods for robust design are discussed. The method of transmitted variation is explained in detail and illustrated on a linkage design problem and a check valve design problem.

Robust Mechanical Design Using Engineering Models

This paper examines how engineering models can be used to develop robust designs—designs that can tolerate variation. Variation is defined in terms of tolerances which bracket the expected deviation of model variables and/or parameters. Several methods for robust design are discussed. The method of transmitted variation is explained in detail and illustrated on a linkage design problem and a check valve design problem.

Tolerances and Robustness in Engineering Design Optimization

This paper describes a new strategy for incorporating tolerances as part of engineering design optimization. The tolerance problem is defined in a general way that allows for tolerances on all model variables and parameters and includes worst case and statistical analysis. Two methods are described for taking tolerances into account during optimization such that an optimal design will remain feasible despite fluctuations in variables or parameters. Methods are also presented for directly controlling transmitted variation, and a framework for optimal tolerance allocation is proposed.