OPTIMIZATION OF DRILLING PARAMETERS ON AUSTENITIC STAINLESS STEEL (AISI 316) USING TAGUCHI'S METHODOLOGY

Transcription

1 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 Research Paper ISSN Vol., No. 4, October, IJMERR. All Rights Reserved OPTIMIZATION OF DRILLING PARAMETERS ON AUSTENITIC STAINLESS STEEL (AISI ) USING TAGUCHI'S METHODOLOGY M Sundeep * M Sudhahar, T T M Kannan, P Vijaya Kumar 4 and N Parthipan 5 *Corresponding Author: M Sundeep msundeep0@gmail.com Metal removal Techniques is a mature technology involving several disciplines of sciences. It is a continuously change in line with strategies material developments though out the manufacturing industry worldwide and also developing the metal cutting industry. This paper aims to make an experimental investigation on drilling behavior of Austenitic stainless Steel (AISI ) and attempt made to optimize the process parameters using L9 Orthogonal array design of experiment of Taguchi methodology. The process parameters of spindle speed, feed rate and drill diameter are influenced by surface roughness and Metal removal rate during Drilling operations. The main objectives of this research paper to identify lowest thrust force and more metal removal rate (MRR) of drilling process through experimental analysis and theoretical calculations using Analysis of Variance (ANOVA). The result of the experiments indicates cutting speed play a dominating role in surface roughness and Metal removal rate in drilling process parameters. Keywords: Austenitic stainless steel, Drilling parameters, Surface roughness, MRR, Taguchi method, ANOVA INTRODUCTION The cutting temperature directly influences the hole sensitivity (hole diameter, perpendicularity, and cylindricity), surface roughness, and tool wear. The experimental and numerical investigation of the temperature changes that occur on the cutting tool during the material removal processes is a traditional concern. In the aero space industry depending on the application hole quality is very important and response process variable outputs. at interest are the important and quality characteristics of holes this experimental investigation process are analyzed to PG Scholar, Department of Mechanical Engineering, Prist University, Thanjavur, India. Assistant Professor, Department of Mechanical Engineering, Ponnaiyah Ramajayam Engineering Collage, Thanjavur, India. Assistant Prefessor, Department of Mechanical Engineering, Prist University, Thanjavur, India. 4 Professor, Department of Mechanical Engineering, Prist University, Thanjavur, India. 5 Assistant Professor, Department of Mechanical Engineering, Kumarasamy of College of Engineering, Karur, India.

2 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 spindle speed, feed rate and different drill diameter are as input parameter. Mustafa Kurt, Yusuf kanak et al performed experiment on Al 04 alloy material uses in different drilling holes on optimization of cutting parameters for surface finish and hole diameter accuracy (009) 40: DOI 0.007/s , Eyup Bagci - Babur ozcelik et al conducted using two different work piece materials AISI 040 steel and Al T5 the effect of dry Drilling operations and drill temperature investigated (00) : 0-7 DOI 0.007/s , Eyup Bagci - Babur ozcelik et al performed experimental on Al7075-T5 material investigated in drill temperature inserting the coolant (oil) hole Tin/TiAlN carbide drills(figure ) using taguchi method a minimum number of trails (00) 9: 9- -DOI 0.007/s N Naveenraj and and K Sooryaprakash et al., performed experimental on GFRP material to optimization of process parameter for cracks in drilling the thrust force and torque of drilled hole by using ANSIS.0 work bench software. Stone and Krishnamurthy utilized a neural network thrust force controller to minimize delaminating during drilling. Surface roughness is a widely used index of product quality and in most cases a technical requirement for mechanical products. A statistical technique, using orthogonal arrays and analysis of variance, has been employed to investigate the influence of cutting parameters in machining. The, feed rate, drill and work piece material, drill point angle are the drilling parameters which highly affect the performance measures, the main concepts to determine thrust force, torque, metal removal rate and surface finish Austenitic stainless steel(aisi ). EXPERIMENTAL SETUP Specimen Material Austenitic stainless steel (AISI ) (Figure ). Stainless steel does not readily corrode, rust or stain with water as ordinary steel does, but despite the name it is not fully stain-proof, most notably under low oxygen, high salinity, or poor circulation environments. It is also called corrosion-resistant steel. Specific Properties Excellent toughness Excellent corrosion resistance Excellent Heat Resistant Good Wear Resistant Minimum crack tendency High Hardenabilty Figure : Twist Drill (TiAlN Coated) 9

3 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 Table : Experimental Level Figure 4: Work Piece Set up to Tool Holder Level Drill diameter (mm) (Rpm) Feed rate (mm/rev) Figure : Radial Drilling Machine Figure 5: Drilling Operation on Specimen Figure : AISI Steel Specimen Figure : Drill Tool Dynamometer 90

4 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 Figure 7: Chips Collection for Various Drill Size Figure : Final Drilled Work Piece arrays to study the entire factor space with only a small number of experiments. (Table )Taguchi robust design method is a powerful tool for the design of a high-quality system. The three steps in a processes and product s development system design, parameter design, and tolerance design. In system design, the engineer uses scientific and engineering principles to determine the fundamental configuration. In the parameter design step, the specific values for system parameters are determined (Table & 4). Tolerance design is used to determine the best tolerances for the parameters. The levels were assigned randomly and the limits used were determined from preliminary experiments. Steps Applied In Taguchi's Optimization Method Table : L9 Orthogonal Array Select the quality characteristics Select noise and control factors TAGUCHI METHODOLOGY The traditional experimental procedures are too complicated and not easy to use. A large number of experimental works have to be carried out when the number of process parameters are increase. To solve this problem, the Taguchi method uses a special design of orthogonal arrays to study the entire parameter space with only a small number of experiments conducted. (Table )Taguchi methods use a special design of orthogonal Select Taguchi orthogonal array Conduct experiments surface roughness Analyze results: (signal-to-noise ratio) Predict optimum performance Confirmation experiments 9

5 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 Table : S/N Ratio of Surface Roughness Trail No Designation A B C A B C A B C A B C A B C A B C A B C A B C A B C Cutting Speed Feed rate Drill dia Sl. No Cutting speed (rpm) Table : Drilling Parameters With Response Factor Feed rate (mm/rev) Drill dia (mm) Thrust force (kgf) Torque (kgm) Surface finish (µm) MRR (mm/ min) Figure 9: S/N Ratio for Surface Roughness Table 4: S/N Ratio of Metal Removal Rate Level Feed rate Drill dia Delta Rank Table 5: Drilling Parameters Level Delta Rank Feed rate Drill dia Anova ANOVA stands for analysis of variance a statistical model meant to analyze data. A statistical method for making simultaneous comparisons between two or more means a statistical method that yields values that can be tested to determine whether a significant relation exists between variables. The Table 7: Analysis of Variance for Surface Roughness Sources DF Seq SS Adj MS Adj MS F P Feed Rate Drill diameter Error Total 45 9

6 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 analysis of variance model examines the association between nominal predictor variables and a continuous outcome variable. The predictor variables are sometimes called factors or independent variables. The outcome variable may be also referred to as the dependent variable. The ANNOVA model is a univariate model. The Statistical technique for determining the degree of difference or similarity between two or more groups of data s based on the on the comparison of the average value of a common component (Table ). Figure 0: Interaction Plot in Drilling Parameters optimum material removal rate under dry environment.. Using mm drill cutting speed 50 rpm and feed rate 0.0 mm produce good surface roughness under dry environment.. Always Produce lowest thrust force of machining under dry environment.(table 5) 4. Using mm drill cutting speed 00rpm and feed rate is 0.0mm produce lowest torque. kgm with lowest thrust force kgf under dry environment. 5. S/N ratio shows more values in surface roughness influence dominating parameters while drilling.(figure 9 and Table ). CONCLUSION In this experimental work, taguchi's design has used to optimize the drilling parameters of Austenitic Stainless steel (AISI-) for different drill size under dry environment, it concludes. RESULTS AND DISCUSSION This experimental work of mach inability characteristics of Austenitic stainless steel (AISI ) are analyzed by various cutting parameters like thrust force, torque, surface roughness and material removal rate (Table 5). Drilling test has been conducted using different size drill diameter under dry environment. The test results are the following.. Using mm drill, cutting speed 50 rpm and feed rate 0.0mm produce. More material removal rate occur at cutting speed 50rpm and feed rate 0.0 mm using mm drill tool. (Figure 0).. Good surface finish is obtained at 0.0 feed rate and cutting speed 50 rpm using mm drill tool. (Figure 7).. Lowest thrust forces occur at cutting speed 00 rpm and feed rate 0.0mm using mm drill tool. 4. Lowest torque produced at cutting speed 00rpm and feed rate 0.0mm using mm drill toll. 5. Austenitic Stainless steel (AISI-) steel produces good machinability 9

7 Int. J. Mech. Eng. & Rob. Res. 04 M Sundeep et al., 04 during drilling operations under dry environment. (Figures 4 & 5). Austenitic Stainless steel (AISI-) produce good surface finish during drilling operations under dry environment. REFERENCES. Agapiou J S (99), Design Characteristics of New Types of Drill and Evaluation of their Performance Drilling Cast Iron. I. Drill with four major cutting edges, Int J Mach Tools Manuf, Vol., pp Basile S A (99), Modeling Transverse Motions of a Drill Bit for Process Understanding, Precis Eng, Vol. 5, pp Bronson B (9), The Making and Selling of Wootz, a Crucible Steel of India. Archeomaterials, Vol., No., pp Chen WC and Tsao CC (999), Cutting Performance of Different Coated Twist Drills, J Mater Process Technol, Vol., pp Dasch JM, Ang CC, Wong CA, Cheng YT, Weiner AM and Lev LC (00), A Comparison of Five Categories of Carbon-based Tool Coatings for Dry Drilling of Aluminum, Surf Coat Technol, 00: Degarmo E Paul and Black J T Kohser (00), Ronal Materials and Process in Manufacturing Wiley, P.9 ISBN Furness R J, Wu CL and Ulsoy A G (99), Statistical Analysis of the Effects of Deed, Speed, and Wear on Hole Quality in Drilling, J Manuf Sci Eng, Vol., pp Joseph R Davis (995), They are Introduced in Properties of Different Materials, Tool Material in ASM International. Handbook Committee ASM International, Technology & Engineering. 9. Kalidas S, DeVor R E and Kapoor S G (00), Experimental Investigation of the Effect of Drill Coatings on Hole Quality Under Dry and Wet Drilling Conditions, Surf Coat Technol, Vol. 4, pp Nouari M, List G, Girot F and Gehin D (005), Effect of Machining Parameters and Coating on Wear Mechanisms in Dry 4 Int J Adv Manuf Technol (009) 40:45-49 Int J Mach Tools Manuf 45: Ross P J (99), Taguchi Techniques for Quality Engineering, McGraw-Hill International Editions, Singapore.. Srinivasan S and Griffiths D (004), South Indian Wootz: Evidence for Highcarbon Steel from Crucibles from a Newly Identified Site and Preliminary Comparisons With Eelated Finds, Material Issues in Art and Archaeology- V, Materials Research Society Symposium Proceedings Series, Vol. 4.. Srinivasan S and Ranganathan S (997), Wootz Steel: An Advanced Material of the Ancient World. Bangalore: Indian Institute of Science. 4. William Wingate (979), Fireplay Arrow ISBN