Thesis (B.S.)--University of Missouri, School of Mines and Metallurgy, 1909. / The entire thesis text is included in file. Typescript. Illustrated by author. Title from title screen of thesis/dissertation PDF file (viewed March 24, 2009)

Licentiatavhandling (sammanfattning) Karlstad : Karlstads universitet, 2008. / Härtill 4 uppsatser.

Thesis (B.S.)--University of Missouri, School of Mines and Metallurgy, 1910. / Typescript. Illustrated by author. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 22, 2008) Includes bibliographical references (p. 29).

Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 99-104).

Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 151-161).

Thesis (M.S.)--Wisconsin. / Includes bibliographical references (leaves 69-70).

Today’s production industry is faced with the challenge of maximising its resources and productivity. Tool condition monitoring (TCM) is an important diagnostic tool and if integrated in manufacturing, machining efficiency will increase as a result of reducing downtime resulting from tool failures by intensive wear. The research work presented in the study highlights the principles in tool condition monitoring and identifies acoustic emission (AE) as a reliable sensing technique for the detection of wear conditions. It reviews the importance of acoustic emission as an efficient technique and proposes a TCM model for the prediction of tool wear. The study presents a TCM framework to monitor an end-milling operation of H13 tool steel at different cutting speeds and feed rates. For this, three industrial acoustic sensors were positioned on the workpiece. The framework identifies a feature selection, extraction and conditioning process and classifies AE signals using an artificial neural network algorithm to create an autonomous system. It concludes by recognizing the mean and rms features as viable features in the identification of tool state and observes that chip coloration provides direct correlation to the temperature of machining as well as tool condition. This proposed model is aimed at creating a timing schedule for tool change in industries. This model ultimately links the rate of wear formation to characteristic AE features.

published_or_final_version / abstract / Mechanical Engineering / Master / Master of Philosophy

Thesis (M.S.)--University of Missouri--Rolla, 2007. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 6, 2007) Includes bibliographical references.

Chromium martensitic hot-work tool steel (AISI H13) is commonly used as die material in hot forming techniques such as die casting, hot rolling, extrusion and hot forging. They are developed to endure the severe conditions by high mechanical properties attained by a complex microstructure. Even though the hot-work tool steel has been improved over the years by alloying and heat treatment, damages still occur. Thermal fatigue is believed to be one of the most common failure mechanisms in hot forming tools. In this thesis tools used in hot forging and die casting were examined to determine damage, material response, thermal fatigue crack initiation and propagation. Different chromium martensitic hot-work tool steels, heat treated at four different austenitizing temperatures were experimentally tested in thermal fatigue and isothermal fatigue. The materials were then evaluated using X-ray line broadening analysis and transmission electron microscopy to explore the relation between fatigue softening and the change in microstructure. The high temperature fatigue softening was also simulated using an elasto-plastic, non-linear kinematic and isotropic model. The model was implemented in a numerical simulation to support the integration of die design, tool steel properties and its use. It was found that the dominant damage mechanisms in the investigated tools were thermal fatigue and that tool material experiences a three stage softening at high temperature loading. The primary stage was concluded to be influenced by the dislocation density and the second stage by the temper resistance i.e. carbide morphology. The microstructural changes during the softening stages were also connected to the non-linear kinematic and isotropic model. The general aim of this thesis is to increase the knowledge of the chromium martensitic hot-work tool steel damage, performance and microstructure.