Minimum Surface Roughness Research Articles

Experimental Investigation on Surface Characteristics of Finish Hobbed Gear using Grey Relational Analysis

Introduction: Spur gears are important for transferring motion and power among shafts. The surface characteristics of these gears are important for their life and smooth operation. To improve profitability and customer satisfaction, a study was conducted to analyze the surface quality of spur gears produced through CNC hobbing machining. Objectives: The objective this investigation is to conduct experimental trials to estimate the best hobbing parameters to minimize surface roughness and microgeometric deviations. In this investigation, effect of varying cutting speed and feed rate on surface finish have been reported. Methods: An experiment are conducted according to Taguchi L9 experimental design. Grey Relational Analysis is performed to estimate the optimum machining parameters. Results: The experimental finding reveals, at cutting speed 400 rpm, the feed rate 8 mm/min, and depth of cut 3.91 mm gives good quality of surface (Ra 0.5530). The gear hobbing process has increased to a greater level of performance. The roughness of the flank surface and microgeometry deviations decreases with an increase in hob cutter speed. Conclusions: This ultimately reduces the inherent vibrations between the hob cutter and the gear blank, thus minimizing microgeometric deviations. The variation in feed rate was noticed and had a very significant impact on the efficiency and surface quality of the gear. The study recommends that a cutting speed of 400 rpm is the most effective for obtaining the best results.

Surface Finish Optimization of Vapor Smoothened PLA Fabricated Parts with Microstructural Analysis

Additive Manufacturing (AM) is a product creation method done layer-by-layer. This process tends to create an unwanted feature known as staircase effect. Vapor smoothing is considered a viable solution for polymer-based AM products to minimized surface roughness. Research literature concerning vapor smoothing of polylactic acid (PLA) parts generally limited unlike its ABS counterpart. This research aims to identify optimum level for both chamber temperature and exposure time of the AM product. Two methods were used to compare their outputs with one another. The two methods are surface roughness tester and optical microscopy. The results provided an impressive 50.88 and 62.72% improvement based on the two test methods. Lastly, a contour-plot was generated to provide future users a guideline if they want to conduct research similar study.

The influence of combination of surface roughness and nanostructure of adhesive on the strength of adhesively bonded joints

Nowadays, adhesively bonded joints are frequently employed in engineering designs as they enable the manufacture of joints with great strength while remaining light. These joints used in aviation sectors, where lightness and reliability are important, are generally designed to join metal-metal, metal-composite and composite-composite adherends. The surface roughness of the adherends with its degree and the way the adhesive interacts with the surface are the most crucial parameters in these applications. In the current work, surface roughness and normal stress strength of nano-composite adhesive in butt joint subjected to tensile loading were investigated. DP460 liquid structural epoxy from 3 M was used as adhesive, AA2024-T3 aluminum alloy as adherend, Graphene-COOH and Carbon Nanotube-COOH as nanostructures while sandpaper and sandblasting methods were used for introducing roughness to the adherend surfaces. A two dimensional axisymmetric FE model was developed to get an insight about the joint failure. When the failure load obtained from experiments was examined, an increasing trend in maximum force values was noticed with an increase in surface roughness, but this increase in joint strength decreased when the surface roughness increased to very high values. In addition, minimum surface roughness reduces the adhesive's adhesion to the surface, thus reducing the normal stress strength of the joint. When 1 % Graphene-COOH nanostructure was added to the adhesive, the ultimate normal stress of the joints increased from 9 % to 21 %. However, when the same percentage of Carbon Nanotube-COOH was added, the increase was from 27 % to 62 %. Different normal stress values of the joints were obtained using by sanding and sandblasting methods even though the roughness resulting from the two treatments was similar.

Multi-Objective Process Parameter Optimization of Ultrasonic Rolling Combining Machine Learning and Non-Dominated Sorting Genetic Algorithm-II.

Ultrasonic rolling is an effective technique for enhancing surface integrity, and surface integrity is closely related to fatigue performance. The process parameters of ultrasonic rolling critically affect the improvement of surface integrity. This study proposes an optimization method for process parameters by combining machine learning (ML) with the NSGA-II. Five ML models were trained to establish relationships between process parameters and surface residual stress, hardness, and surface roughness by incorporating feature augmentation and physical information. The best-performing model was selected and integrated with NSGA-II for multi-objective optimization. Ultrasonic rolling tests based on a uniform design were performed, and a dataset was established. The objective was to maximize surface residual stress and hardness while minimizing surface roughness. For test specimens with an initial surface roughness of 0.54 µm, the optimized process parameters were a static pressure of 900 N, a spindle speed of 75 rpm, a feed rate of 0.19 mm/r, and rolling once. Using optimized parameters, the surface residual stress reached -920.60 MPa, surface hardness achieved 958.23 HV, surface roughness reduced to 0.32 µm, and contact fatigue life extended to 3.02 × 107 cycles, representing a 52.5% improvement compared to untreated specimens and an even more significant improvement over without parameter optimization.

Research on bubble-free Si/SiC hydrophilic bonding approach for high-quality Si-on-SiC fabrication

The electrical device fabricated by the Si-on-SiC substrate exhibits superior heat dissipation and minimal RF loss. However, a common challenge in hydrophilic direct bonding is the inevitable formation of bubbles at the Si/SiC interface, which compromises material utilization efficiency. To address this issue, a multi-bonding process was introduced in this research. Experimental findings revealed that this method effectively mitigated interfacial bubble formation, especially when incorporating a multi-step annealing–separating–bonding approach, yielding even more promising results. Ultimately, a bubble-free 3 × 3 cm2 Si-on-SiC substrate was fabricated. Material characterization techniques confirmed the high crystal quality and minimal surface roughness for the Si functional layer. Transmission electron microscopy further revealed the presence of an amorphous oxide layer (∼3.5 nm) at the interface, devoid of any defects or nanovoids. It is believed that with its excellent physical properties, Si-on-SiC will have a broader application prospect in extreme environments.

Enhancing the Quality of MOF Thin Films for Device Integration Through Machine Learning: A Case Study on HKUST‐1 SURMOF Optimization

AbstractMetal–organic Frameworks (MOFs), especially as thin films, are increasingly recognized for their potential in device integration, notably in sensors and photo detectors. A critical factor in the performance of many MOF‐based devices is the quality of the MOF interfaces. Achieving MOF thin films with smooth surfaces and low defect densities is essential. Given the extensive parameter space governing MOF thin film deposition, the use of machine learning (ML) methods to optimize deposition conditions is highly beneficial. Combined with robotic fabrication, ML can more effectively explore this space than traditional methods, simultaneously varying multiple parameters to improve optimization efficiency. Importantly, ML can provide deeper insights into the synthesis of MOF thin films, an essential area of research. This study focuses on refining an HKUST‐1 SURMOF (surface‐mounted MOF) to achieve minimal surface roughness and high crystallinity, including a quantitative analysis of the importance of the various synthesis parameters. Using the SyCoFinder ML technique, thin film surface quality is markedly enhanced in just three generations created by a genetic algorithm, covering 30 distinct parameter sets. This method greatly reduces the need for extensive experimentation. Moreover, the results enhance the understanding of the vast synthesis parameter space in HKUST‐1 SURMOF growth and broaden the applications of MOF thin films in electronic and optoelectronic devices.

Ultrasonic peening-waterjet composite surface modification of 7075-T6 aluminum alloy for residual stress release and transformation mechanism

The release and transformation mechanism of residual stress contributes to the improvement of metal materials' processing and performance, enhancing their structural stability, surface integrity, and fracture resistance. This paper focuses on the Ultrasonic Impact Treatment-Solid Particle Entrainment by Waterjet (UIT-SPEWJ) composite surface modification of 7075-T6 aluminum alloy, investigating the effects of UIT-SPEWJ process parameters (jet pressure and target distance) on the alloy's surface quality, roughness, microhardness, residual stress, and the evolution mechanism of microstructure. The results indicate that the 7075-T6 aluminum alloy modified by UIT-SPEWJ mainly exhibits a "meteorite crater" effect, accompanied by significant smearing and ploughing phenomena. Surface roughness shows a trend of first decreasing and then increasing with the rise of jet pressure and target distance. The minimum surface roughness, 0.852 μm, is achieved at a jet pressure of 25 MPa and a target distance of 7.5 mm. The microhardness of the samples modified by UIT-SPEWJ gradually decreases from the surface to the substrate with increasing depth. The hardened layer depths of the samples UIT-SPEWJ-1–6 after modification are approximately 174 μm, 226 μm, 200 μm, 196 μm, 176 μm, and 172 μm, respectively. After UIT, SPEWJ, and UIT-SPEWJ surface modifications, the surface of 7075-T6 aluminum alloy mainly exhibits compressive residual stress (CRS). The surface residual stress σ_srs of samples modified by UIT and SPEWJ are approximately 195.161 and 215.752 MPa, respectively. The surface residual stresses of UIT-SPEWJ-1–6 samples are significantly improved to 277.089, 529.499, 393.615, 459.261, 368.084, and 220.635 MPa, respectively, with UIT-SPEWJ-2 sample having the highest surface residual stress, which is 2.7 and 2.4 times that of UIT and SPEWJ modified surfaces. Samples modified by UIT-SPEWJ present significant dislocation phenomena, and the precipitated phases mainly include the needle-like metastable phase η', as well as the equilibrium phase η (MgZn2) with a rod-like structure. At lower jet pressures and larger target distances, the 7075-T6 aluminum alloy exhibits a continuous PFZ with a size of approximately 12–23 nm. As jet pressure increases and target distance decreases, discontinuous grain boundary precipitate bands appear, sized around 8–17 nm. Moreover, when the jet pressure is 25 MPa and the target distance is 7.5 mm, the grain boundary precipitated phases are more dispersed.

Experimental evaluation of tribo-performances of bump foil journal bearing with different materials of foil

In this paper, the bump foil journal bearing (FJB) is developed with five different foil materials: Inconel X750 (IN-X750), Stainless steel 316 (SS316), Beryllium copper (BC), Spring steel EN42J (SP EN42J) and Phosphor bronze (PB). A complete fabrication process is described in detail, along with the design of fixtures, to develop the bump FJB. This fabrication process includes various machining operations such as milling, rolling, cutting, threading, forming etc. The forming load versus deflection curve is obtained for all the foil materials with the metal forming operation. After fabricating it, the load-deflection test is performed to evaluate the structural characteristics (stiffness, energy dissipation and damping coefficient) of these developed bump FJB. Further, the tribological characteristics of bump FJB such as wear rate and surface roughness are evaluated by the experimental study. Moreover, the interface temperature of bump FJB is also captured by using the thermal imager. This study shows that the metal forming operation is the most challenging step among all the fabrication steps of bump FJB Among all the foil materials, the minimum wear rate and maximum surface roughness of bump FJB are observed for the IN-X750. The maximum spring-back effect in bump FJB is found for the Spring steel EN42J. These results demonstrate that the maximum energy dissipation and stiffness of bump FJB are observed for the Phosphor bronze and Inconel-X750 respectively. In addition, the damping coeffcient of bump FJB is evaluated.

Analisa Kekasaran Permukaan Baja ST 37 Hasil Proses Milling Vertikal Akibat Variasi Proses Permesinan dan Media Pendingin

Minimum surface roughness in the machining process affects the quality of a material. Likewise with the results of the Vertical Milling process. One of the things that influences surface roughness in the milling process is the selection of machining parameters. Apart from selecting machining process parameters, another thing that influences surface roughness is the presence of coolant. The aim of this research is to determine the surface roughness results of ST37 steel due to variations in cutting speed, feed speed and coolant discharge during the vertical milling process. Data testing uses multiple linear regression. The research results show that the influence of the feeding speed parameter has the greatest influence and the smallest influence is on the coolant discharge, where the results of the regression test results are Ra = 100.636 *(v)-0.577 *(vf)0.159 *(q)-0.245 with a value R Square is 0.846 or 84.6%.

Cleaning mechanisms during post chemical mechanical polishing (CMP) using particle removal of surfactants via a citric acid-based solution

With the development of circuit integration technology, the requirements for defects in copper interconnects have become more stringent. The residual SiO2 particles on the copper surface can seriously affect circuit performance and require more efficient and thorough removal. This article investigates the effects of a novel cleaning solution composed of citric acid (CA), alkyl polysaccharide glycosides (APG1214), and dodecylbenzene sulfonic acid (LABSA), aimed at improving the removal efficiency of SiO2 and maintaining the integrity of copper surface. The optimal concentrations of APG1214 and LABSA were determined through contact angle and surface tension analysis. It was found that when APG1214 (2000 ppm) and LABSA (1000 ppm) were combined in a 3:2 vol ratio in CA solution (0.6 wt%), the highest particle removal efficiency (99.5 %) could be achieved while minimizing surface roughness. The results of scanning electron microscopy (SEM) and atomic force microscopy (AFM) confirmed these findings. Combining quantum chemical calculations, new insights into the mechanism of action of different components in clean solutions have been proposed: 1. Similar to CA, LABSA and APG1214 demonstrate a strong affinity for copper, synergistically facilitating the cleavage of Cu-Si bonds. 2. Alternating adsorption of LABSA and APG1214 on free silica particles prevents their re-adsorption onto copper surfaces. 3. Furthermore, their orderly adsorption on copper mitigates the corrosive chelation effect of CA, providing a protective mechanism. These findings are pivotal for the development of advanced, multifunctional cleaning solutions.

Multi-objective optimization of turning process parameters and wood sawdust contents using response surface methodology for the minimized surface roughness of recycled plastic/wood sawdust composites

The objective of this work was to investigate the effect and optimization of turning parameters such as spindle speed, feed rate, and depth of cut as well as wood sawdust content on the roughness quality of wood-plastic composites (WPCs). The Box–Behnken design and response surface methodology were used in experiments. Three roughness parameters, namely average roughness (Ra), root mean square average of roughness (Rq), and average maximum height (Rz) were employed to evaluate the surface quality of WPC samples. Based on the findings of the experiments, the Ra, Rq, and Rz values reduced with increasing spindle speed in a range of 430 to 1030 rpm, whereas the values increased when increasing the feed rate in a range of 0.05 to 0.15 mm/min. Also, an increase in depth of cut ranging from 1 to 3 mm and WPCs with a higher amount of wood sawdust in a range of 30 to 50 wt% raised their surface roughness. Finally, optimal conditions for the turning of the WPCs were determined to comprise a spindle speed of 781 rpm, a feed rate of 0.05 mm/min, a depth of cut of 2.8 mm, and wood sawdust content of 30 wt% with the highest desirability score of 1.000. Under such conditions, the sample had Ra, Rq, and Rz values of 1.8, 2.2, and 11.3 µm, respectively. The optimal conditions for turning can be used to effectively process different WPC products into various shapes.

Improvement of UV resistance and mechanism in polypropylene wax on wood surface through maleic anhydride and β-nucleating agent modification

In China, beeswax is commonly used to protect hardwood surfaces through hot waxing, and is widely utilized in wood furniture and buildings. However, beeswax, with its low melting point and high cost, is prone to being destroyed and falling off, and has a short-term protective effect on wood under ultraviolet (UV) light. Polypropylene wax (PPW), with its low cost and high melting point, holds potential for application in wood protection. The introduction of maleic anhydride enhanced the combination of PPW and wood, resulting in excellent surface properties. Additionally, the β-nucleating agent (WBG-II) induced PPW to form β crystal structure, further enhancing the UV barrier property of the wax coating. After UV irradiation, the surface properties of the hot-waxed wood using the modified polypropylene wax exhibited minimal changes, including color, adhesion, hydrophobicity, and surface roughness. The chemical structure, crystalline structure, and surface morphology were analyzed by FTIR, XRD, and SEM to reveal the photodegradation mechanism of the surface wax coating. The results demonstrated that the co-modification of polypropylene wax by maleic anhydride and WBG-II has a positive effect on the long-term protection of wood substrate, providing a reference for wood protection, particularly for dark and precious wood, and helping to reduce deforestation.

Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite

Optimizing electric discharge machining (EDM) for aluminum/SiCp metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting process economy and elevating product costs. The research aims to find the optimal combination of process parameters which include pulse on-time, pulse current, duty cycle (%), gap voltage, sensitivity and flushing pressure for EDM of Al/SiCp-MMC using a copper electrode for the selected response factors such as material erosion rate and surface roughness, Ra. The experiments were designed using the central composite design of response surface methodology and an advanced optimization technique known as Teaching–learning-based optimization (TLBO), is applied to find the optimal combination of process parameters to obtain maximum material erosion rate subject to the desired range of surface roughness (SR), Ra. The combination of the high pulse on-time (i.e. 150 μs) and high pulse current (i.e. 12A) results in high material removal rate with deep craters on the machined surface clearly visible in SEM images contrasting the minimized surface roughness at lower values of pulse on-time (50 μs) and the pulse current (4A). Pulse on - time (Ton) is found to be the most significant factor for material erosion rate and surface roughness with percentage contribution of 70.86 and 54.9 respectively for optimization of the response. The regression models were developed at 95% confidence level for material removal rate and surface roughness with R2 value of 0.93 and 0.95 respectively signifying high degree of accuracy in predicting the response. Confirmation tests conducted to check the adequacy of the established models revealed that the percentage error between the predicted and experimental responses is found to be within acceptable levels. Electron discharge machining of the aluminium metal matrix composite at the optimized conditions could provide economical aspect in the aerospace and automobile industry.

Experimental investigation on electric discharge-assisted surface modification of Ti6Al4V with comparative analysis between different polarities in ecofriendly dielectric deionised water

ABSTRACT Electric discharge machining (EDM) is the most widely used non-conventional machining process for machining difficult-to-cut materials in complex geometries and intricate cavities with less cost. The main problem associated with EDMed part is its increased surface roughness (SR). This article made an attempt on surface modification of Ti6Al4V by reducing SR with different polarities of EDM in deionised water, an eco-friendly dielectric. Experiments were performed on both straight and reverse polarities in full factorial with varying two factors (voltage and current) in two levels. The substrate processed with the reverse polarity possesses minimum (1.26 µm) SR of about 2.15 times than that of the straight polarity (2.64 µm) at the parametric conditions of 60 V, 10 A and 100 µs. Enhanced microhardness (300–450 HV1) and specific wear rate (2.4 × 10−4 mm3/Nm) were observed with the straight polarity due to the microstructural changes along with higher SR and defects. Contact angle analysis reveals that both straight and reverse polarity processed parts are hydrophilic in nature. Reverse polarity can be used as an effective tool for surface modification with less SR and defects and with slight increase in microhardness (300–400 HV1) and specific wear rate (2.6 × 10−4 mm3/Nm). The presence of enriched titanium oxide (rutile) observed on the reverse polarity surface increases its applicability, especially in biomedical industries.

Experimental Study on Parameters Optimization of Selective Laser Melting 316L Stainless Steel Based on the Response Surface Methodology

Abstract The use of 3D printing technology can prepare flexible and varied special-shaped complex structures while realizing resource-saving and cost reduction. For this purpose, a 316L stainless steel sample was formed by selective laser melting technology, and the quality of samples was optimized by the Box–Behnken surface response method. Taking the surface roughness Sa as the response value, a regression analysis of four parameters of selective laser melting (laser power, scanning speed, scanning spacing, and scanning strategy) was designed using design expert software. The results showed that the scanning spacing and scanning speed have the greatest influence on the surface roughness, while the laser power and scanning strategy have no significant influence on the surface roughness. Meanwhile, the established surface roughness response surface model is effective and can be used for quality optimization of 316L structural trim. When the laser power was 185 W, the scanning speed was 615 mm/s, the scanning spacing was 110 μm and concentric scanning strategy was adopted, the surface adhesion powder was less, and the minimum surface roughness Sa was 9.001 μm.

Multi-objective optimization of machining variables for wire-EDM of LM6/fly ash composite materials using grey relational analysis

Abstract With the enhancement in science and technology, necessity of complex shapes in manufacturing industries have become essential for more versatile applications. This leads to the demand for lightweight and durable materials for applications in aerospace, defense, automotive, as well as sports and thermal management. Wire electric discharge machining (WEDM) is an extensively utilized process that is used for the exact and indented shaped components of all materials that are electrically conductive. This technique is suitable in practically all industrial sectors owing to its widespread application. The present investigation explores WEDM for LM6/fly ash composites to optimize different process variables for attaining performance measures in terms of maximum material removal rate (MRR) and minimum surface roughness (SR). Taguchi’s L27 OA design of experiments, grey relational analysis, and analysis of variance (ANOVA) were employed to optimize SR and MRR. It has been noted from ANOVA that reinforcement (R) percentage and pulse on time are the most influential aspects for Grey Relational Grade (GRG) with their contributions of 28.22 and 18.18%, respectively. It is found that the best process variables for achieving the highest MRR and lowest SR simultaneously during the machining of the composite are gap voltage of 30 V, pulse on time of 10 µs, pulse off time of 2 µs, wire feed of 8 m/min, and R of 9%. The predicted GRG is 0.84, and the experimental GRG value is 0.86. The validation experiments at the optimized setting show close agreement between predicted and experimental values. The morphological study by optical microscopy revealed a homogenous distribution of reinforcement in the matrix which enhances the composite’s hardness and decreases the density.

Enhancing machining accuracy of banana fiber-reinforced composites with ensemble machine learning

Through innovative predictive modeling, this study advances Abrasive Water Jet Machining (AWJM) for banana fiber-reinforced biocomposites. Utilizing Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) models, hyperparameters are meticulously tuned for predicting Surface Roughness (Ra), Material Removal Rate (MRR), and Kerf Angle (Ka). Optimal configurations are identified, such as 3–6-6–4-1, 3–5-5–4-1, and 3–5–4–4-1 for ANN models, and 250, 100, and 50 units for LSTM models. Beyond individual models, the study explores stacking ensemble models, merging ANN and LSTM strengths with a Linear Regression final estimator, showcasing robust performance validated with high R-squared values. Regression models from Design Expert 13 contribute to understanding process parameter-outcome relationships. Optimized input parameters offer insights into minimizing surface roughness and kerf angle while maximizing MRR. This holistic approach, integrating advanced machine learning and ensemble learning, enhances predictive accuracy for banana-reinforced biocomposites, providing a versatile framework for diverse materials processing applications.

Optimizing the SPIF parameters for enhancing microhardness and surface quality in Inconel 625 superalloy components

Inconel 625, a high-strength superalloy with excellent corrosion resistance, discovers wide applications in critical sectors such as aerospace, nuclear, marine, and petrochemical. Single-Point Incremental Forming (SPIF) has appeared as an adequate fabricating process for shaping superalloy components. This work used a systematic approach, implementing Response Surface Methodology (RSM) to explore the influence of SPIF process variables, including tool nose diameter, step size, tool spindle speed, and wall angle, on microhardness (MH) and surface roughness (SR). The experimental results have been analyzed to determine the influencing process variables and their optimal settings, which simultaneously enhance MH and reduce SR of Inconel 625 superalloy truncated cones using analysis of variance and the desirability function analysis approach. The most significant parameters that influence MH and SR were TND and SS, respectively. The development of quadratic models for MH and SR has been completed successfully. The maximum MH of 486.8 HV and minimum SR of 0.432 µm have been obtained at the optimal parametric setting of TND = 15 mm, SS = 0.4 mm, TSS = 900 rpm, and WA = 57.5° with the desirability values for MH, SR and combined are 0.832, 0.933, 0.881 respectively. The F-value of the MH model = 109.18 and SR Model = 78.24 implies that both models are significant and both models have excellent prediction strength. The percentage error between predicted and actual values of MH and SR in confirmation run results is less than 5 %.

The internal modified layer structure of silicon carbide induced by ultrafast laser and its application in stealth dicing

Silicon carbide (SiC) is widely applied in high-power electronic devices due to its excellent properties. Stealth dicing (SD) as one of the dicing methods, exhibits the advantages of few thermal surface damage and low edge-chipping. In this study, we use an ultrafast laser to induce the modified layer structure inside the SiC wafers. The effects of laser processing parameters on the modified layers are studied. The formation mechanism of the modified layer and its influence on SD are analyzed. The result shows that the number of modified layer structures is mainly determined by the moving velocity. The different modified layer structures will affect the surface roughness of the SD cross-section and critical fracture load of the 4H–SiC wafers. Finally, we achieved the high-quality SD of SiC wafers, and a cross-section with the minimum surface roughness is approximately 381 nm.

Experimental Investigation and Optimization of Coaxiality Error Analysis with CNC Turning Process on Delrin for Assembly Fit

This paper mainly deals with the machining operation like turning operation, Material Removal Rate and Surface Roughness are the important parameter which is to be considered for quality product. The material selected for the experiment is DELRIN 500. Turning is one of the important processes that is widely used to create cylindrical components and it is also used for surface finish the product to make it smooth. Nowadays, plastic materials are widely used for making variety of components. To make a component with high dimensional accuracy, turning operation is used. The main concerns of turning are tooling cost and the effect of process on machinability characteristics. It can be seen that the output responses value has a minimum roughness average and a high degree of geometrical quality precision. High degree surface finish is induced by medium speed, feed rate, and small nose radius. The coaxial error was minimized by using medium speed, feed and larger nose radius. Experimentally found that third specimen (RPM -750) (FEED -0.08 mm/Rev) and (NOSE RADIUS 0.8) obtained minimum geometrical error along with minimum Surface roughness. Delrin is a crystalline plastic that offers an excellent balance of properties that bridge the gap between metals and plastics. Delrin possesses high tensile strength, creep resistance and toughness. It also exhibits low moisture absorption