Robust Design Methods [Working Title]

2021 ◽  
Keyword(s):  
Robust Design ◽  
Design Methods

A review of robust design methods for multiple responses

2005 ◽  
Vol 16 (3) ◽  
pp. 118-132 ◽  
Author(s):  
Terrence E. Murphy ◽  
Kwok-Leung Tsui ◽  
Janet K. Allen
Keyword(s):  
Robust Design ◽  
Design Methods ◽  
Multiple Responses

Optimisation and Robust Design in Aero Engine Development

2004 ◽  
Author(s):  
Alexander Karl ◽  
Stephan Lisiewicz ◽  
Winfried-Hagen Friedl ◽  
Janet Worgan ◽  
Gordon May
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Response Surface ◽  
Robust Design ◽  
Design Methods ◽  
Surface Model ◽  
Widespread Application ◽  
Deterministic Optimization ◽  
Aero Engine ◽  
Engine Development

Recent developments in computer capabilities and software enabled the application of deterministic optimization and Robust Design methods in real world aero engine development programs. This paper describes the methods used and shows several applications of this technology. The first example is the application of a Monte-Carlo simulation to support design decisions in the HP turbine casing air system. Here the main goal was to achieve a robust design addressing the variation of build tolerances on flow areas. The variation of parameters as mass flows, pressures and temperatures based on 5000 permutations of the base model give a high confidence level for achieving reliable system behavior for a large population of engines. In addition, dependencies of result parameters on input variations indicate the main levers for system improvement. A second example is the optimization of compressor discs. Here the main emphasis was on the influence of manufacturing tolerances and on the best method to evaluate these tolerances for longer running analysis tasks. Therefore, results of a full Monte-Carlo simulation are compared with results based on two surrogate models, a response surface and a Taylor series expansion. As a final example the optimization of a HP turbine disc for which a Design of Experiment has been performed to generate a response surface model is discussed. Using the response surface data the life variability due to assumptions in the thermal modeling have been quantified and used to adjust the constraints for the subsequent deterministic optimization for weight of the HP turbine. Using deterministic optimization and especially Robust Design methods a considerable decrease in development time and cost as well as an increased product quality and reliability have been achieved. However, deterministic optimization methods alone normally drive designs on to the constraint boundaries, leading to “cliff-edge” designs. Therefore, the application of Robust Design methods is required to increase the product reliability. These methods still require a considerable computing effort, so the widespread application is just starting.

Robust Topological Design of Cellular Materials

2003 ◽  
Author(s):  
Carolyn Conner Seepersad ◽  
Janet K. Allen ◽  
David L. McDowell ◽  
Farrokh Mistree
Keyword(s):  
Robust Design ◽  
Design Method ◽  
Cellular Materials ◽  
Design Methods ◽  
Topology Design ◽  
Research Areas ◽  
Topological Design ◽  
Capability Indices ◽  
Active Research ◽  
Design Techniques

A robust topology exploration method is under development in which robust design techniques are extended to the early stages of a design process when a product’s layout or topology is determined. The performance of many designs is strongly influenced by both topology, or the geometric arrangement and connectivity of a design, and potential variations in factors such as the operating environment, the manufacturing process, and specifications of the design itself. While topology design and robust design are active research areas, little attention has been devoted to integrating the two categories of design methods. In this paper, we move toward a comprehensive robust topology exploration method by coupling robust design methods, namely, design capability indices with topology design techniques. The resulting design method facilitates efficient, effective realization of robust designs with complex topologies. The method is employed to design extruded cellular materials with robust, desirable elastic properties. For this class of materials, 2D cellular topologies are customizable and largely govern multifunctional performance. By employing robust, topological design methods, we obtain cellular material designs that are characterized by ranged sets of design specifications with topologies that reliably meet a set of design requirements and are relatively simple and robust to anticipated variability.

scholarly journals System Theoretic Approach for Determining Causal Factors of Quality Loss in Complex System Design

2014 ◽  
Author(s):  
Stephanie L. Goerges ◽  
Qi D. Van Eikema Hommes
Keyword(s):  
New Product Development ◽  
Robust Design ◽  
Failure Modes ◽  
Process Analysis ◽  
Design Methods ◽  
Theoretic Approach ◽  
Quality Loss ◽  
Causal Factors ◽  
Traditional Design

Identifying the factors that could lead to the loss of quality is difficult for large complex product systems. Traditional design methods such as Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and Robust Design have been proven effective at identifying component failures, but are less effective for causes of quality loss that involve interactions between components, software flaws, or external noises. This research applied System Theoretic Process Analysis (STPA) to a case study at Cummins, Inc. The case study was a technology change to a subsystem in a new product development project. The intent of this case was to determine if STPA, developed for safety engineering and hazard analysis, would be effective in identifying causes of quality losses. The results of the case study were compared to the traditional design methods. STPA allowed design teams to identify more causal factors for quality losses than FMEA or FTA, especially those involving component interactions, software flaws, and external noises. STPA was also found to be complementary to Robust Design methods.

Robust Design: Methods and Application to Real World Examples

2006 ◽  
Author(s):  
A. Karl ◽  
G. May ◽  
C. Barcock ◽  
G. Webster ◽  
N. Bayley
Keyword(s):  
Product Quality ◽  
Robust Design ◽  
Real World ◽  
Design Methods ◽  
Aero Engine ◽  
Recent Developments ◽  
Quality And Reliability ◽  
Optimisation Methods ◽  
Automated Processes ◽  
Engine Development

Recent developments in computer capabilities and software have enabled the application of deterministic optimisation and Robust Design methods in real-world aero-engine development programmes. This paper describes both the methods used and several applications of this technology. Using automated processes, deterministic optimisation, and especially Robust Design methods, an increased product quality and reliability have been achieved, while at the same time producing a considerable decrease in development time and cost. It is the application of Robust Design methods that leads to increased product quality and reliability, as deterministic optimisation methods alone often drive on to constraint boundaries, leading to “cliff-edge” designs.

scholarly journals State of the Art on Robust Design Methods for Additive Manufacturing

2021 ◽  
pp. 80-85
Author(s):  
Youssef Malyani ◽  
Myriam Orquéra ◽  
Dominique Millet
Keyword(s):  
Additive Manufacturing ◽  
Robust Design ◽  
Manufacturing Process ◽  
State Of The Art ◽  
Design Methods ◽  
Complex Geometries

AbstractAdditive Manufacturing (AM) technologies allow to produce functional parts with complex geometries that cannot be manufactured by conventional processes. However, the complexity of the product is increased and causes new constraints in the manufacturing process. Therefore, these new processes lead particularly to new needs in design methods. The objective of this paper is to explore and form an overall view of design methods, especially, robust design (RD) methods. Robust design is defined here as a methodology that enables to design a product with optimal performances and insensitivity to small variations of the inputs of the manufacturing process. In this contribution a state of the art of robust design methods applied to AM will be carried out.

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