Modeling of Pack-Carburizing Route by General Factorial Design of Experiment Abstract—This work modeled the influence of Na 2 CO 3 as an activator material in the pack-carburizing process of 1.5920 steel by General Factorial Design of Experiment (GFDE). Four different carburizing mixtures containing 0, 5, 10 and 15 wt. % of Na 2 CO 3 at 16 experiments have been used. The samples were carburized at 925°C for different time of 3, 5, 8 and 12 hrs. The Effective Case Depth (ECD) of treated samples was measured using a micro-hardness test. The activator content and carburizing time were considered as model factors. The optimal conditions to attain the maximum ECD were predicted by GFDE. The results indicated that by using activator amount of 11.5 wt. %, maximum ECD could be achieved, regardless of the carburizing time. The reasons for declining of ECD corresponding to the activator amount beyond the 11.5 wt. % were also discussed. Keywords— Pack-Carburizing; Activator; 1.5920 steel; Modeling; General factorial design of experiment. I. INTRODUCTION Surface hardening is a very important process for industrial applications. Machine components such as shafts, gears and cams often require a very hard surface that can resist wear and a soft, tough core that can withstand the impact stresses which occur during operation. An established method for the production of such a combination of hard case and soft, tough core is case hardening of steels through carburizing and quenching [1-3]. Carburizing is the addition of carbon to the surface of low carbon steels at temperatures generally between 850-950 °C (1560-1740 °F), at which austenite, with its high solubility for carbon, is the stable crystal structure. Hardening is accomplished when the high-carbon surface layer is quenched to form martensite [1,2]. As a result of this process a high-carbon martensitic case with good wear [4,5] and fatigue resistance [6,7] is superimposed on a tough low-carbon steel core. Carburizing steels for case hardening usually have base- carbon contents of about 0.2 wt.%, with the carbon content of the carburized layer generally being controlled between 0.8 and 1 wt.%. However, surface carbon is often limited to 0.9 wt.%, because so high carbon content can result in retained austenite and brittle martensite [6,8]. It has been reported [9] that the Martensite Finish Temperature (M f ) for carbon content greater than 0.65 wt.% value is below room temperature. It is well documented that many factors, such as time, temperature, and surface carbon influenced the final microstructure and properties of treated samples [10-15]. In contrast to the gas and liquid carburizing, solid carburizing is a minor commercial process. It requires more processing time. Obtaining greater case depths by increasing time cycles is costly due to increasing energy consumption [16]. Case depth can be increased exponentially by increasing the carburizing temperature, but this approach is also problematic in economic sense [17]. It has been reported that adding of some rock minerals [10, 18-21] or Rare Earths (RE) [22,23] in carburizer can accelerate the carburizing process. For example, Ogo et al. [18] observed that there was significant increase in the carburization rate of mild steel by the addition of river clam shell (mainly contains CaCO 3 ) to charcoal. Jimenez et al. [19] reported that addition of carbonates (BaCO 3 and Na 2 CO 3 ) to the metallurgical coke gave rise to an increase in the carburization rate and case depth which allowed the achievement of the required carbon concentration profiles more efficiently. From the industrial point of view, it is essential to find out the best combination of carburizing parameters to attain the maximum case depth. One of the most common and classical approaches employed by many experimenters is One-Factor-At-a-Time (OFAT), in which one factor is varied while all other variables or factors in the experiment are fixed. The success of this approach depends on guesswork, luck, experience and intuition. Moreover, this type of experimentation requires large resources to obtain a limited amount of information about the process [24-29]. OFAT experiments often are unreliable, inefficient, time consuming [30] and may yield false optimum condition for the process. The major disadvantage of the OFAT strategy is that it fails to consider any possible interaction between the factors [24-29]. An interaction is the failure of the one factor to produce the same effect on the response at different levels of another factor [27]. International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 www.ijert.org IJERTV3IS090900 (This work is licensed under a Creative Commons Attribution 4.0 International License.) Vol. 3 Issue 9, September- 2014 947 Hamed Khosravi* PhD Candidate, Faculty of Materials Science and Engineering, K. N. Toosi University of Technology, Tehran, Iran Mohsen Mirzaee Sisan Faculty of Materials Science and Engineering, K. N. Toosi University of Technology, Tehran, Iran Seyed Reza Elmi Hosseini PhD Candidate, School of Materials Science and Engineering, Shanghai Jiaotong University, Shanghai, China Mohsen Askari Paykani PhD Candidate, Department of Materials Science and Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran Zhuguo Li Professor, School of Materials Science and Engineering, Shanghai Jiaotong University, Shanghai, China