Petter Andersson

Manufacturability Assessment in the Conceptual Design of Aircraft Engines – Building Knowledge and Balancing Trade-Offs

This paper addresses the automated assessment of manufacturability of air-craft engine components in the early stages of design, focused on the welding process. It is a novel part of a multi-objective decision support tool for design evaluation, currently running at a manufacturer of jet engine components. The paper briefly describes the tool and how it impacts the product development process. Further, the paper presents an integrated method for manufacturability assessment by finding welding processes that complies with all geometrical and other constraints found in the CAD-models of the conceptual engine. Here, preferences made by manufacturing engineers serves as a base for a manufacturability index so that different parameter settings in the CAD-models can be compared to find the best parameter settings, considering the trade-off with other performance criteria’s of the engine.

Tree-Based Response Surface Analysis

Computer-simulated experiments have become a cost effective way for engineers to replace real experiments in the area of product development. However, one single computer-simulated experiment can still take a significant amount of time. Hence, in order to minimize the amount of simulations needed to investigate a certain design space, different approaches within the design of experiments area are used. One of the used approaches is to minimize the time consumption and simulations for design space exploration through response surface modeling. The traditional methods used for this purpose are linear regression, quadratic curve fitting and support vector machines. This paper analyses and compares the performance of four machine learning methods for the regression problem of response surface modeling. The four methods are linear regression, support vector machines, M5P and random forests. Experiments are conducted to compare the performance of tree models M5P and random forests with the performance of non-tree models support vector machines and linear regression on data that is typical for concept evaluation within the aerospace industry. The main finding is that comprehensible models the tree models perform at least as well as or better than traditional black-box models the non-tree models. The first observation of this study is that engineers understand the functional behavior, and the relationship between inputs and outputs, for the concept selection tasks by using comprehensible models. The second observation is that engineers can also increase their knowledge about design concepts, and they can reduce the time for planning and conducting future experiments.

Introducing welding manufacturability in a multidisciplinary platform for the evaluation of conceptual aircraft engine components

Computer simulations play an important role for evaluating designs in an early stages leading to that more informed decisions can be taken and thereby reducing the risk of costly re-design. In this paper, a platform currently in operation at an aeronautical company for doing extensive automated multi-objective design parameter studies on conceptual designs of aircraft engine components is studied. In the paper, an extension of the capability of the platform into making a rule-based evaluation of the welding manufacturability of the conceptual designs is proposed. The extension is tested by a prototype system at the air-craft manufacturer showing the relation between the design parameters and the manufacturability of the components. The results are presented as a manufacturability index showing what trade-offs with other performance criteria of the engine that can be made. It is shown that the manufacturability evaluation can be integrated in the knowledge value stream and supports a set-based concurrent engineering approach in the company.

Automated Producibility Assessment Enabling Set-Based Concurrent Engineering.

The aero-engine industry is continuously faced with new challenging cost and environmental requirements. This forces companys, active in the industry, to work toward more fuel efficient engines with less environmental impact at a lower cost. This paper presents a method for assessing producibility of large sets of components within aircraft engines to enable a Set-Based Concurrent Engineering development approach. A prototype system has been developed aimed at enabling weldability analysis at a sub-supplier within the aero-engine industry. It is a part of a multi-objective decision support tool used in early design stages. The tool produces sets of CAD-models reaching the hundreds for different analyses, mainly focusing on performance aspects within structural analysis, aerodynamics and thermodynamics.

Designing simulation platforms for uncertainty—An example from an aerospace supplier

Variation poses a serious threat to the functionality, safety and reliability of aircraft. As the aerospace industry depends ever more heavily on modeling and simulation in their product development, there is an increased need to assess the effects of variation in a virtual environment. This paper outlines the methods proposed by a Swedish aerospace supplier to incorporate robust design methodology into platform-based product development. These methods evaluate how geometric variation affects the aerodynamic, thermal and structural performance of turbofan engine components. The results of the study show that simulation results are heavily affected by variations in geometry. Moreover, this study showcases automated simulation platforms as a powerful tool for robustness analyses. In addition to optimizing the robustness of products, these tools are equally effective as a tool for allocating engineering resources to optimize quality-to-cost ratio.