Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2013, Article ID 362601, 9 pages http://dx.doi.org/10.1155/2013/362601 Research Article Ameliorated Austenite Carbon Content Control in Austempered Ductile Irons by Support Vector Regression Chan-Yun Yang, 1 Liou-Chun Chang, 2 Hooman Samani, 1 and Ryohei Nakatsu 3 1 Department of Electrical Engineering, National Taipei University, San Shia District, New Taipei City 23741, Taiwan 2 Mechanical Engineering and Chemical Technology, British Columbia Institute of Technology, BC, Canada 3 Department of Electrical and Computer Engineering, National University of Singapore, Singapore Correspondence should be addressed to Hooman Samani; hooman@mail.ntpu.edu.tw Received 3 February 2013; Accepted 5 April 2013 Academic Editor: Chang-Hua Lien Copyright © 2013 Chan-Yun Yang et al. his is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Austempered ductile iron has emerged as a notable material in several engineering ields, including marine applications. he initial austenite carbon content ater austenization transform but before austempering process for generating bainite matrix proved critical in controlling the resulted microstructure and thus mechanical properties. In this paper, support vector regression is employed in order to establish a relationship between the initial carbon concentration in the austenite with austenization temperature and alloy contents, thereby exercising improved control in the mechanical properties of the austempered ductile irons. Particularly, the paper emphasizes a methodology tailored to deal with a limited amount of available data with intrinsically contracted and skewed distribution. he collected information from a variety of data sources presents another challenge of highly uncertain variance. he authors present a hybrid model consisting of a procedure of a histogram equalizer and a procedure of a support-vector-machine (SVM-) based regression to gain a more robust relationship to respond to the challenges. he results show greatly improved accuracy of the proposed model in comparison to two former established methodologies. he sum squared error of the present model is less than one ith of that of the two previous models. 1. Introduction Austempered ductile iron (ADI) is a specialty heat-treated material that takes advantage of the near-net shape technol- ogy and low-cost manufacturability of ductile iron castings to make a high-strength, low-cost, and excellent abrasion- resistant material. ADI has become an established alternative in many applications that were previously the exclusive domain of steel castings, forgings, weldments, powdered metals, and aluminum forgings and castings [1–6]. his material has been also proven to perform very well under diferent wear mechanisms such as rolling contact fatigue, adhesion, and abrasion [7, 8]. Considering the low-cost, design lexibility, lexible machinability, high strength-to- weight ratio and good toughness, wear resistance, and fatigue strength of ADI, its usage now is extended into marine application with increasing interest in the study of corrosion and coating of ADI [5, 9–12]. ADI is obtained by heat treating process of ductile irons to have bainite as matrix, which consists of strong bainitic ferrite platelets and tough high-carbon retained austenite, along with spheroidal graphite nodules [1–3]. he typical microstructure of ductile irons, shown in Figure 1(a), includes spheroidal graphite nodules and matrix surrounding them. he bainitic matrix of an austempered ductile iron [8] is illustrated in Figure 1(b). A signiicant amount of retained austenite is presented as the shape of ilms and blocks in the matrix. he heat treatment for developing bainite matrix includes two steps. First, ductile irons are heated to austenization temperature (  ) around 1550–1750 ∘ F to change the original matrix into austenite and then quenched down to the bainite formation temperature range (450–750 ∘ F) for one to three hours when bainitic ferrite grows isothermally at the expense of austenite before cooling down to ambient temperature [1– 3, 13, 14]. he austenization reverses the matrix structure to high temperature austenite phase and in the meantime determines the initial carbon concentration in austenite ( 0  ) before austempering process, since the graphite modules