About: Engineering tolerance is a research topic. Over the lifetime, 33 publications have been published within this topic receiving 325 citations. The topic is also known as: tolerance & fabrication tolerance.
TL;DR: In this paper, a branch and bound algorithm for ensuring optimum selection of tolerances from a given discrete model involving various manufacturing processes, minimization of manufacturing cost is achieved under the constraint of tolerance stack-up.
Abstract: Tolerancing involves considerations from all phases of the life cycle of a product including design, manufacturing, assembly, and inspection. Along with minimum cost and maximum functionality and interchangeability, the practice of tolerancing urges a designer to choose an appropriate manufacturing (or inspection) process as well. This situation is formalized as a discrete optimization problem. For an optimum selection of tolerances from a given discrete model involving various manufacturing processes, minimization of manufacturing cost is achieved under the constraint of tolerance stack-up. A random variable and its standard deviation are associated with a dimension and its tolerance. This probabilistic approach enables a trade-off between performance and tolerance (cost). But it also suggests probabilistic optimization. With the aid of a notion called the reliability index [8], tolerance selection is formulated as an integer programming problem. A branch and bound algorithm for ensuring optimum selection is developed by exploiting the special structure of the constraints. To make the enumeration tree small, monotonic relations among the reliability index, cost, and tolerance are examined. The algorithm is tested with examples.
TL;DR: In this article, the possibilities and limitations of these two approaches on Tolerance Engineering are discussed in a case where the case describes cross-collaborative improvement work within industry on tolerance and variation management which is similar to a work model called CLTE.
TL;DR: Gauge repeatability and reproducibility (R&R) analyses for two-dimensional data when the engineering tolerance is a circle are considered in this article, where summaries are developed by employing the diameters of circles that provide 99% capture rates.
Abstract: Gauge repeatability and reproducibility (R&R) analyses are considered for two-dimensional data when the engineering tolerance is a circle. Summaries are developed by employing the diameters of circles that provide 99% capture rates. It is also shown ..
TL;DR: This paper proposes three novel capability indices for measuring the performance of a multidimensional machining process under the assumption that the variances of machining results on different directions may not be equal.
Abstract: Engineering tolerance plays an important role in the process capability analysis for determining whether a manufacturing process is capable of making good quality products. In contrast with the engineering tolerance region in a multivariate manufacturing process, the multidimensional machining process or the nano-cutting process has a special engineering tolerance called the positional tolerance. Positional tolerance is a special type of geometric dimensioning and tolerancing which describes the tolerance region between the actual location of machining results and the target location. In the past few years, several capability indices have been developed for measuring the performance of a multidimensional machining process under the assumption that the variances of machining results on different directions are equal. However, this assumption may not be true in most practical situations. In this paper, we propose three novel capability indices for measuring the performance of a multidimensional machining process under the assumption that the variances of machining results on different directions may not be equal. The statistical properties of the point estimators and their confidence intervals for the new capability indices are derived. Both the simulation results and numerical examples show that the new capability indices outperform the predecessors.