Robust Tolerance Design for Quality

1996 ◽  
Vol 118 (1) ◽  
pp. 166-169 ◽  
Author(s):  
A. Kusiak ◽  
Chang-Xue Feng
Keyword(s):  
Design Of Experiments ◽  
System Design ◽  
Robust Design ◽  
Current Literature ◽  
Design Parameter ◽  
Parameter Design ◽  
Manufacturing Processes ◽  
Tolerance Design ◽  
Tolerance Synthesis

Design of a product (process) includes system design, parameter design, and tolerance design. Robust design is closely applicable to parameter design and tolerance design. The current literature on robust design has focused on parameter design while the problem of tolerance design has not been adequately covered. The tolerance design literature emphasizes the use of optimization to minimize cost while little attention has been paid to minimizing the sensitivity of tolerances to the variation of manufacturing processes. This paper discusses the application of the design of experiments (DOE) approach to tolerance synthesis to minimize manufacturing variations in a probabilistic case. The DOE approach is illustrated with an example.

Robust Design: Tolerance Design Method

1999 ◽  
Author(s):  
Hanxiang Yang ◽  
Pah I. Chen
Keyword(s):  
Iterative Method ◽  
Robust Design ◽  
Test Data ◽  
Design Parameter ◽  
Parameter Design ◽  
Specific Yield ◽  
Design Parameters ◽  
Pneumatic Cylinder ◽  
Tolerance Design ◽  
Simple Task

Abstract There are three phases involved in Robust Design — conceptual design, parameter design, and tolerance design. Parameter design aims to specify the variations of the design parameters in order to meet the design requirement, and the tolerance design further specifies the optimized parameters in order to reduce the performance variation near the design target. A robust design requires that tolerance design to be preceded by parameter design. In this paper, our effort will be focused on presenting an iterative method to perform the tolerance design phase. Two hypothetical examples (whose parameter designs have been completed) will be used to illustrate the tolerance design methodology. The first example involves the design of a pneumatic cylinder whose piston movement can be expressed by a theoretical equation containing five parameters. With the equation, it becomes a simple task for determining the tolerances of the optimized parameters to constrain the design target. The second example involves the production of a agrochemical by mixing two chemicals to achieve a specific yield. A set of test data is available but the equation relating the parameters is not. In this case, we shall adopt the linear regression technique to obtain an experimental equation to represent the test data. Based on this equation, we can proceed to determine the tolerances of different parameters in order to achieve a specific variation of the yield. The step-by-step procedure outlined in the hypothetical examples demonstrates that this iterative method is a simple and effective way to conduct the tolerance design.

Design of Tolerances for Quality

1994 ◽  
Author(s):  
Chang-Xue Feng ◽  
Andrew Kusiak
Keyword(s):  
Robust Design ◽  
Current Literature ◽  
Design Method ◽  
Solution Procedure ◽  
Taguchi Methods ◽  
Parameter Design ◽  
Manufacturing Cost ◽  
Tolerance Design ◽  
Manufacturing Defects ◽  
Robust Design Method

Abstract Design of a product (process) includes system design, parameter design, and tolerance design. Robust design is closely applicable to parameter design and tolerance design. The current literature on robust design is focused on parameter design while little attention has been paid to tolerance design. The current literature on tolerance design has focused on the use of optimization to minimize cost while little attention has been paid to minimizing manufacturing variations. This paper attempts to apply a robust design method, the design of experiments (DOE) approach, in tolerance synthesis to minimize manufacturing variations in the probabilistic case. Both, the manufacturing cost and the number of manufacturing defects are minimized in robust tolerance design. A solution procedure is proposed to apply the DOE approach to probabilistic tolerance design. The procedure is illustrated with an example. Special applications of the DOE approach to tolerance design are discussed. A brief comparison of the DOE approach with optimization, Taguchi methods, and zero defect design is presented.

Robust Tolerance Synthesis With the Design of Experiments Approach

1999 ◽  
Vol 122 (3) ◽  
pp. 520-528 ◽  
Author(s):  
Chang-Xue (Jack) Feng ◽  
Andrew Kusiak
Keyword(s):  
Design Of Experiments ◽  
Heuristic Algorithms ◽  
Exact Algorithms ◽  
Manufacturing Processes ◽  
Manufacturing Cost ◽  
Simulation Approach ◽  
Worst Case ◽  
Quality Cost ◽  
Tolerance Synthesis ◽  
Selection Of

Design of tolerances impacts quality, cost, and cycle time of a product. Most literature on deterministic tolerance design has focused on developing exact and heuristic algorithms to minimize manufacturing cost. Some research has been published on probabilistic tolerance synthesis and optimization. This paper presents the design of experiments (DOE) approach for concurrent selection of component tolerances and the corresponding manufacturing processes. The objective is to minimize the variation of tolerance stackups. Numerical examples illustrate the methodology. The Monte Carlo simulation approach is used to obtain component tolerances and tolerance stackups. Process shift, the worst case and root sum square tolerance stackup constraints, and setup reduction constraints have been incorporated into the proposed methodology. Benefits of the proposed DOE approach over exact algorithms are discussed. [S1087-1357(00)00202-1]

Manufacturing System Robustness Through Integrated Modeling

1999 ◽  
Vol 123 (4) ◽  
pp. 630-636 ◽  
Author(s):  
Rajiv Suri ◽  
Kevin Otto
Keyword(s):  
Robust Design ◽  
Manufacturing System ◽  
Parameter Design ◽  
Manufacturing Processes ◽  
Stretch Forming ◽  
Complete Set ◽  
Product Variation ◽  
System Robustness ◽  
Operating Points ◽  
Geographical Locations

Robust design techniques are often applied to the design of manufacturing processes to determine the most robust operating points for a production system. However, such efforts have traditionally been focused on treating the output of each manufacturing operation in isolation. This approach ignores the fact that the sensitivity of each operation to input variation is a function of the operating point, which can only be changed in conjunction with the operating points of all other operations in that system. As such, applying robust design to each operation within a system individually does not guarantee lowest end-of-line variation. This is contrary to commonly held beliefs. What is needed instead is a method for conducting a system-wide parameter design where the operating points of each operation are optimized as a complete set to reduce final product variation. The logistics of such an integrated parameter design scheme become difficult or impossible on processes that may occur in different geographical locations. In this paper we outline the use of mathematical models to conduct system-wide parameter design. We demonstrate this technique on a model of a sheet stretch-forming manufacturing system. Through this example, we show that selecting operating points while considering the entire system results in a greater reduction in variation than Taguchi-style robust design conducted independently on each of the operations within the system.

Robust Design of Horizontal Axis Wind Turbines Using Taguchi Method

2011 ◽  
Vol 133 (11) ◽  
Author(s):  
Yi Hu ◽  
Singiresu S. Rao
Keyword(s):  
Taguchi Method ◽  
Robust Design ◽  
Wind Turbines ◽  
Design Problem ◽  
Horizontal Axis ◽  
Parameter Design ◽  
Tolerance Design ◽  
Design Problems ◽  
Momentum Theory ◽  
Horizontal Axis Wind Turbines

The robust design of horizontal axis wind turbines, including both parameter design and tolerance design, is presented. A simple way of designing robust horizontal axis wind turbine systems under realistic conditions is outlined with multiple design parameters (variables), multiple objectives, and multiple constraints simultaneously by using the traditional Taguchi method and its extensions. The performance of the turbines is predicted using the axial momentum theory and the blade element momentum theory. In the parameter design stage, the energy output of the turbine is maximized using the Taguchi method and an extended penalty-based Taguchi method is proposed to solve constrained parameter design problems. The results of the unconstrained and constrained parameter design problems, in terms of the objective function and constraints are compared. Using an appropriate set of tolerance settings of the parameters, the tolerance design problem is formulated so as to yield an economical design, while ensuring a minimal variability in the performance of the wind turbine. The resulting multi-objective tolerance design problem is solved using the traditional Taguchi method. The present work provides a simple and economical approach for the robust optimal design of horizontal axis wind turbines.

Robust design of a polygonal shaft-hub coupling

2015 ◽  
Author(s):  
R. Citarella ◽  
M. Perrella
Keyword(s):  
Boundary Element Method ◽  
Taguchi Method ◽  
Design Of Experiments ◽  
Robust Design ◽  
Design Parameter ◽  
Numerical Experiments ◽  
Optimal Choice ◽  
Performance Function ◽  
Set Up ◽  
Parameter Values

In this work, the Taguchi method is applied for the optimal choice of design parameter values for a polygonal shaft-hub coupling. The objective is to maximize a performance function, minimizing, at the same time, its sensitivity to noises factors (robust design). The Design of Experiments (DoE) is adopted to set up a plan of numerical experiments, whose different configurations are simulated using the Boundary Element Method (BEM).

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