Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.576478
Title: The identification and modelling of the dominant failure mode in hot forging tooling
Author: Anderson, Magnus
ISNI:       0000 0004 2054 5868
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2013
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
The aim of the thesis is the identification and modelling of the dominant failure mode in hot forging tooling, used in the production of nickel based superalloy compressor blades. A preliminary study identified the most frequently occurring part defects that cause tool failure. The forming process was characterised, relevant tooling failure modes were identified and the mechanical properties and microstructure of the tooling was reviewed. Case studies have been performed identifying the observable damage in worn tooling and investigating the conditions that result in tool failure. The investigation made use of finite element analysis, metrology, metallurgical analysis and thermal measurement. The dominant failure mode was associated with the plastic deformation of the tooling. Testing was performed to gather sufficient data to allow for the development of a lifing model. Isothermal tensile and fatigue tests were performed under temperatures and strain rates representative of hot forging tooling conditions. The microstructural instability during these conditions was investigated. A literature review explored state of the art approaches to modelling the plastic flow behaviour of tempered martensitic tool steels for the purpose of tool life prediction. A lifing model was developed to describe the plastic flow behaviour of tempered martensitic steel. A physical based model developed to describe the creep behaviour of 9-12%Cr tempered martensitic steel has been applied to describe the thermo-mechanical fatigue behaviour of 5%Cr tempered martensitic hot work tool steel. The model was verified by comparing model predictions to experimental data not used in the development of the model. The model was then applied to predict the life of tooling examined in the case studies. The life predictions were within a factor of 10 from measured die lives measured from the forge.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.576478  DOI: Not available
Share: