Research Papers: Design Automation

Quantitative Assessment of the Impact of Alternative Manufacturing Methods on Aeroengine Component Lifing Decisions

[+] Author and Article Information
Benjamin Thomsen

Department of Mechanical Engineering,
Massachusetts Institute of Technology,
Cambridge, MA 02139

Michael Kokkolaras

Associate Professor
Department of Mechanical Engineering,
McGill University,
Montréal, QC H3A 0C3, Canada;
Visiting Researcher
Department of Product and
Production Development,
Chalmers University,
Göteborg 41258, Sweden

Tomas Månsson

GKN Aerospace Engine Systems Sweden
Trollhättan 461 81, Sweden

Ola Isaksson

Department of Product and
Production Development,
Chalmers University,
Göteborg 41258, Sweden;
GKN Aerospace Engine Systems Sweden,
Trollhättan 461 81, Sweden

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 7, 2015; final manuscript received September 26, 2016; published online November 14, 2016. Assoc. Editor: Irem Tumer.

J. Mech. Des 139(2), 021401 (Nov 14, 2016) (10 pages) Paper No: MD-15-1692; doi: 10.1115/1.4034883 History: Received October 07, 2015; Revised September 26, 2016

Static structural aeroengine components are typically designed for full lifetime operation. Under this assumption, efforts to reduce weight in order to improve the performance result in structural designs that necessitate proven yet expensive manufacturing solutions to ensure high reliability. However, rapid developments in fabrication technologies such as additive manufacturing may offer viable alternatives for manufacturing and/or repair, in which case different component lifing decisions may be preferable. The research presented in this paper proposes a value-maximizing design framework that models and optimizes component lifing decisions in an aeroengine product–service system context by considering manufacturing and maintenance alternatives. To that end, a lifecycle cost model is developed as a proxy of value creation. Component lifing decisions are made to minimize net present value of lifecycle costs. The impact of manufacturing (represented by associated intial defects) and maintenance strategies (repair and/or replace) on lifing design decisions is quantified by means of failure models whose output is an input to the lifecycle cost model. It is shown that, under different conditions, it may not be prudent to design for full life but rather accept shorter life and then repair or replace the component. This is especially evident if volumetric effects on low cycle fatigue life are taken into account. It is possible that failure rates based on legacy engines do not translate necessarily to weight-optimized components. Such an analysis can play a significant supporting role in engine component design in a product–service system context.

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Fig. 1

Present value of lifecycle costs as a function of TRS lifespan

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Fig. 2

Optimal TRS lifespan as a function of fuel burn

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Fig. 3

Robustness of optimal TRS lifespan to varying parameter values

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Fig. 4

Optimal TRS lifespan as a function of two-at-a-time varying parameters

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Fig. 5

Excerpt of sensitivity, knowledge maturity, and weighted knowledge maturity calculations

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Fig. 6

Cumulative probability of failure for a TRS as a function of lifespan

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Fig. 7

Schematic profiles for volume fraction exposed to high stresses. Profile (a) corresponds to baseline concept, (b) represents test specimen, and (c) denotes profile optimized with respect to weight.

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Fig. 10

The optimal (cost-minimizing) lifespan of a TRS as a function of material defects

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Fig. 11

A potential recertification plan would skew cost-minimizing lifespan toward a lower value

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Fig. 8

Cumulative probability of failure for a 250 kg TRS with 20 initial material defects as a function of lifespan

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Fig. 9

Cumulative probability of failure for TRS as a function of initial material defects




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