Field Failure Resolution of a Tractor Engine Exhaust System Using Constrained Single Objective Optimization and Stochastic Analysis

Paper #:
  • 2017-26-0233

Published:
  • 2017-01-10
Citation:
Perumal, S., Kumar, A., Mahajan, A., Redkar, D. et al., "Field Failure Resolution of a Tractor Engine Exhaust System Using Constrained Single Objective Optimization and Stochastic Analysis," SAE Int. J. Commer. Veh. 10(1):411-422, 2017, https://doi.org/10.4271/2017-26-0233.
Pages:
12
Abstract:
The tractor engine related mounting brackets are very critical due to different aspects of vehicle performance, durability and noise. These mounting bracket have been designed as a framework to support engine external parts like muffler, exhaust tail pipe, alternator etc. Vibration and fatigue has been continuously a concern which may lead to structural failure and performance issues. Various such failures are faced regularly by automotive industry and finite element based analysis are used to resolve them. The resolution is done by playing with the component thicknesses, material, by providing additional support etc. However, due to large degree of uncertainty associated with the loading, boundary conditions, manufacturing, environmental effects; still there is some probability of failure. This paper focuses on a field failure issue of an exhaust system of a tractor and subsequent concern resolution. Multiple field failures like Under Hood Muffler (UHM) lug failure and UHM mounting bracket failure were reported during different tractor applications. A finite element model was generated; static, modal and force frequency response analyses were performed and the field failures were simulated. As there were multiple failure modes, a multi-constrained single objective optimization problem was formulated and an optimum solution was obtained. To start with, few key influencing design parameters were identified, design of experiments (DoE) were conducted, a transfer function was developed and finally an optimum solution was derived. To evaluate the robustness of optimum design under uncertainty of material properties, thicknesses, exhaust temperature; a stochastic analysis were performed to find out the probability of success. No probability of failure was observed for all the objectives.
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