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Article
Publication date: 14 September 2022

Murat Tunç, Hasan Gökkaya, Gökhan Sur and Ali Riza Motorcu

The purpose of the paper is to investigate photochemical machining characteristics of stainless steel (AISI 304-SS304) parts with a novel design are investigated experimentally…

Abstract

Purpose

The purpose of the paper is to investigate photochemical machining characteristics of stainless steel (AISI 304-SS304) parts with a novel design are investigated experimentally from the aspect of process parameters. The effects of phototool pattern geometry, ultraviole (UV) exposure time and etching time on of AISI 304 were evaluated.

Design/methodology/approach

The designed semi-automated photochemical manufacturing (PCM) equipment consists of 4 units, which include UV exposure, etching, developing and surface cleaning units. Experimental procedure has been designed via Taguchi method. Results were evaluated via Analysis of Variance (ANOVA) method.

Findings

Etching time is the most effective factor in PCM quality of AISI 304 stainless steel. Surface roughness is sensitive to geometrical pattern of the phototool for PCM of AISI 304 UV exposure time is less influential on the PCM quality for stainless steel.

Research limitations/implications

The designed PCM equipment prototype is not fully automated, which requires automation for part replacements into units. The effects of the temperature inside chemical processing units on process characteristics cannot be evaluated due to equipment limitations. The effects of surface cleaning time inside surface cleaning unit are not analyzed.

Originality/value

The utilized PCM equipment is semi-automated equipment, with which the process parameters such as etching time, surface cleaning time, UV exposure time and developing time can be controlled. Different from literature, the effects of phototool pattern geometries on the photochemical machining quality parameters are evaluated for the processing of AISI 304. The effects of processing parameters on dimensional accuracy, which is not common in the literature for AISI 304 stainless steel, are also evaluated.

Details

Multidiscipline Modeling in Materials and Structures, vol. 18 no. 5
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 30 September 2020

Gökhan Sur and Ömer Erkan

Drilling of carbon fiber reinforced plastic (CFRP) composite plates with high surface quality are of great importance for assembly operations. The article aims to optimize the…

Abstract

Purpose

Drilling of carbon fiber reinforced plastic (CFRP) composite plates with high surface quality are of great importance for assembly operations. The article aims to optimize the drill geometry and cutting parameters to improve the surface quality of CFRP composite material. In this study, CFRP plates were drilled with uncoated carbide drill bits with standard and step geometry. Thus, the effects of standard and step drill bits on surface quality have been examined comparatively. In addition, optimum output parameters were determined by Taguchi, ANOVA and multiple decision-making methods.

Design/methodology/approach

Drill bit point angles were selected as 90°, 110° and 130°. In cutting parameters, three different cutting speeds (25, 50 and 75 m/min) and three different feeds (0.1, 0.15 and 0.2 mm/rev) were determined. L18 orthogonal sequence was used with Taguchi experimental design. Three important output parameters affecting the surface quality are determined as thrust force, surface roughness and delamination factor. For each output parameter, the effects of drill geometry and cutting parameters were evaluated. Input parameters affecting output parameters were analyzed using the ANOVA method. Output parameters were estimated by creating regression equations. Weights were determined using the analytic hierarchy process (AHP) method, and multiple output parameters were optimized using technique for order preference by Similarity to An ideal solution (TOPSIS).

Findings

It has been determined from the experimental results that step drills generate smaller thrust forces than standard drills. However, it has been determined that it creates greater surface roughness and delamination factor. From the Taguchi analysis, the optimum input parameters for Fz step tool geometry, 90° point angle, 75 m/min cutting speed and 0.1 mm/rev feed. For Fd, are standard tool geometry, 90° point angle, 25 m/min cutting speed and 0.1 mm/rev feed and for Ra, are standard tool geometry, 130° point angle, 25 m/min cutting speed and 0.1 mm/rev feed. ANOVA analysis determined that the most important parameter on Fd is the tip angle, with 56.33%. The most important parameter on Ra and Fz was found to be 40.53% and 77.06% tool geometry, respectively. As a result of the optimization with multiple criteria decision-making methods, the test order that gave the best surface quality was found as 4–1-9–5-8–17-2–13-6–16-18–15-11–10-3–12-14. The results of the test number 4, which gives the best surface quality, namely, the thrust force is 91.86 N, the surface roughness is 0.75 µm and the delamination factor is 1.043. As a result of experiment number 14, which gave the worst surface quality, the thrust force was 149.88 N, the surface roughness was 3.03 µm and the delamination factor was 1.163.

Practical implications

Surface quality is an essential parameter in the drilling of CFRP plates. Cutting tool geometry comes first among the parameters affecting this. Therefore, different cutting tool geometries are preferred. A comparison of these cutting tools is discussed in detail. On the other hand, thrust force, delamination factor and surface roughness, which are the output parameters that determine the surface quality, have been optimized using the TOPSIS and AHP method. In this way, this situation, which seems complicated, is presented in a plain and understandable form.

Originality/value

In the experiments, cutting tools with different geometries are included. Comparatively, its effects on surface quality were examined. The hole damage mechanism affecting the surface quality is discussed in detail. The results were optimized by evaluating Taguchi, ANOVA, TOPSIS and AHP methods together.

Details

Engineering Computations, vol. 38 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

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