# Surface Roughness Analysis in the Hard Milling of JIS SKD61 Alloy Steel
## 1 Introduction  
JIS SKD61 is a hot-work die steel that is widely used in the mold and die manufacturing industry. It is often utilized to manufacture hot extrusion dies, casting molds, and forging dies due to its significant toughness, high hardness, and sufficient resistance to high temperature fatigue properties. Generally, a mold and die manufacturing process consists of rough machining, heat treatment, and then a finish grinding operation. This process is both costly and time-consuming. Furthermore, the quality of the machined surface produced by the grinding operation is prone to thermal damage [1]. Nowadays, in order to enhance production and product quality in the mold and die manufacturing industry, the finishing grinding process is often replaced by a hard milling operation; this way, the product cycle time can be decreased, productivity increased, and the quality of finished products can be significantly improved [2]. Nevertheless, the JIS SKD61 hardened alloy steel is often acknowledged as a difficult machining material because of its high strength and work hardening rates. Thus, to achieve the best surface quality, highest productivity, and lowest cost, the cutting conditions must be considered and chosen properly whenever hard milling is involved. Recently, many researchers have effectively applied the Taguchi method to optimize the surface roughness during hard machining processes. For instance, [PERSON] _et al_. [3] optimized the cutting conditions and developed an experimental equation for surface roughness during milling with (Ti, Al)N-TiN coated inserts of AISI (American Iron and Steel Institute) H13-hardened alloy steel by use of the Taguchi method. The result of their research indicates that the surface roughness under the optimized cutting parameters is less 0.25 \(\upmu\)m. [PERSON] _et al._[4] studied the toroidal milling of hardened SAE (Society of Automotive Engineers) H13 alloy steel using the minimum quantity of lubricant (MQL) technique. Their result indicates that the surface roughness value is 0.8 \(\upmu\)m. [PERSON] [5] used the Taguchi method for optimizing input variables such as cutting speed, feed rate, depth of cut, and tool's nose radius in the hard turning of AISI 8660 steel with PVD (Physical vapour deposition)-coated ceramic tools. The result reveals that the value of surface roughness is about 1.5 to 2 \(\upmu\)m. [PERSON] and [PERSON] [6] obtained surface roughness of 1.17 \(\upmu\)m under the optimal machining condition during hard turning of AISI 4140 with coated carbide cutting tools. Furthermore, [PERSON] _et al._[7] optimized the surface roughness during hard turning of AISI H11 steel with TiN coated mixed ceramic insert by RSM. All experiments were designed by use of the Box-Behken method. With optimized machining conditions, they achieve a surface roughness of 0.56 \(\upmu\)m. [PERSON] and [PERSON] [8] reported the development of a mathematical model and the multiple objective optimization for surface quality when turning AISI 304 steel based on Taguchi and RSM analysis. On the other hand, many authors have successfully combined RSM with a genetic algorithm (GA) to produce an effective methodology for determining the optimum cutting conditions [9; 10; 11; 12]. They developed experimental models with the RSM and then applied the GA to identify the optimal machining process parameters for the surface finish. With a neural network approach, many researchers have investigated the effects of machining parameters on the surface roughness [13; 14]. With most of the researchers mentioned above, the cutting process parameters for hard machining were chosen according to the experience of researchers. They ignored the dynamic parameters of machine tools which significantly affect the surface roughness in machining. Given the nature of these approaches, this did not completely reflect the aspects of machining process. It is known that the machine tool system is often affected by chatter vibrations during milling operation.