Table Feed Rate Research Articles

Implementation of hybrid CryoMQL sustainable lubri-cooling to enhance the grindability and surface integrity of tool steel

The current demand for surface finishing processes that are both technically proficient and environmentally friendly is increasing, necessitating the advancement of more efficient sustainable methods. Minimum quantity lubrication (MQL) provides excellent lubrication in the tool-work interaction but insufficient cooling impact. Besides, cryogenic enhances the chilling effect but has inadequate lubrication. This research revealed the synergistic impact of hybrid CryoMQL with eco-friendly Al2O3 NFs while grinding AISI D2 tool steel. CryoMQL facilitates the application of MQL-based soybean oil and deionized water (SO+DW) emulsion with 0.5 wt% and 1 wt% concentration of Al2O3 NPs and liquid nitrogen (LN2) through two individual nozzles in the cutting region. The results indicated that CryoMQL reduced grinding force (tangential force, Ft, and normal force, Fn), specific grinding energy (Ug), surface roughness (Ra), and grinding temperature (Tg) by 3.64–25.66 % in Ft, 3.52–12.87 % in Fn, 3.64–25.66 % in Ug, 8.81–25.02 % in Ra and 57.59–58.30 % in Tg, respectively, compared to MQL environment at 0.04 mm downfeed and 150 mm/s table feed rate. Eventually, it was observed that 1 wt% Al2O3 NFs improve Ft, Fn, Ug, Ra and Tg by up to 32.71 %, 20.33 %, 32.71 %, 23.55 %, and 6.81 % in comparison to 0.5 wt% Al2O3 NFs in the CryoMQL mode. The effectiveness of Al2O3 nanofluids with CryoMQL has resulted in good tribological conditions in the grinding zone with enhanced cooling/lubricating action of vegetable oil. Furthermore, negligible chip adhesion over finished surfaces was seen with 0.5 wt% and 1 wt% Al2O3 NFs under CryoMQL grinding. This study provides numerous scientific assistance in the automotive and tooling sectors, such as a better selection of environmentally friendly coolants and sustainable parameters for excellent surface properties, to provide the solution to highly complex and close tolerances of tool steel parts using CryoMQL finishing.

INVESTIGATION OF THE MACHINING PERFORMANCE OF ALUMINUM–BRONZE ALLOY IN WEDM USING TAGUCHI METHOD

Aluminum–Bronze alloys (Al-10%–Cu-balance) are difficult-to-machine cut alloys. Copper (Cu) metal itself is not suitable for machining. The machining performance of the Aluminum–Bronze alloy sample was investigated by the Wire Electric Discharge Machining (WEDM) method, which is among the non-traditional manufacturing methods used in conductive materials that are difficult to process. The aluminum–bronze sample with a diameter of 20[Formula: see text]mm was cut with 0.18[Formula: see text]mm molybdenum wire electrode. Table feedrate, pulse-on-time and pulse-space were used as experimental parameters. Surface roughness and energy consumption values were measured in WEDM process. According to Taguchi analysis and ANOVA results, it was determined that the pulse-on-time parameter was effective on the surface roughness and the table feedrate parameter was effective on the energy consumption.

Comparative Cutting Fluid Study on Optimum Grinding Parameters of Ti-6Al-4V Alloy Using Flood, Minimum Quantity Lubrication (MQL), and Nanofluid MQL (NMQL)

Titanium alloys have been of paramount interest to the aerospace industry due to their attractive characteristics. However, these alloys are difficult to machine and require grinding post-processes for quality assurance of the products. Conventional grinding takes a long time and uses a flood coolant-lubrication technique, which is not cost effective nor environmentally friendly. Several studies have been performed to prove the viability and benefit of using Minimum Quantity Lubrication (MQL) with vegetable or synthetic-ester fluids. This work aims to find the optimum grinding parameters of creep feed grinding Ti-6Al-4V with a green silicon carbide wheel, using a flood lubrication system with water-soluble synthetic oil, MQL with ester oil, and nano-MQL (NMQL) using alumina-nanopowder homogeneously dispersed within an ester oil. It is concluded that at 0.635 mm and 1.27 mm infeeds, the three lubrication methods performed similarly. At an infeed of 1.905 mm, MQL did not provide desirable quality, though NMQL and flood lubrication performed practically identically. At a cross feed of 0.254 mm, an infeed of 1.27 mm, and a table feed rate of 6.7 m/min, these grinding parameters provide a material removal rate of 2163 mm3/min with a surface roughness across (Ra) of 0.515 µm. These parameters provide the quickest material removal rate while still maintaining industrial quality. This conclusion is based on environmental, economic, and qualitative results.

Performance evaluation of mixture of groundnut oil and camel milk as cutting fluids on the surface of aluminium during turning

Performance of the mixture of the two extract (groundnut oil and camel milk) as cutting fluid will be evaluated at various proportion and at various speed and feed and on the surface finish of aluminium material as well as the tool life. Various percentage proportions of 80% groundnut oil to 20% camel milk, 60% groundnut oil to 40% camel milk, 40% groundnut oil to 60% camel milk, 20% groundnut oil to 80% camel milk. At each proportion the surface finish as well as tool life will be assessed and evaluated at various speeds and feed during turning on the lathe machine. The anticipated result for this experiment will determine which amount of the mixture proportion gives better surface finish and how much it affects the tool life; the study will also determine the effectiveness of the mixture content as cutting fluid on aluminium material.The Taguchi process optimisation suggested that in mixture ratio higher feedrate affect cutting speed and result to a higher value of surface roughness as the same spindle speed as clearly shows that in the Taghuci analysis response table for mixture of 80% camel milk to 20% groundnut oil. For the rest of the mixture i.e. 60% camel to 40% groundnut oil in the SN Ration Table feedrate tend to go higher at a lower cutting speed as analysed. From the result obtained at spindle speed of 58 rpm and 80%camel milk to 20% groundnut oil feed rate was found to be 34 m,cutting speed was 11600 rpm and surface roughness at 522 µm also at the spindle speed of 850 rpm feedrate was found to be 510 m,cutting speed at 1700 rpm and surface roughness of 1121 µm. At the spindle speed of 1240 rpm feed rate and feed rate was found to be 744 m and cutting speed 24800 rpm and surface roughness found to be 2385 µm respectively.

Machine Tool Equipped with a Counter Balance Feed Drive in the Z Direction with Right and Left Ball Screws and the Influence of Anisotropic Mechanical Behavior on Small-Diameter Drilling Processes

In recent years, electronic devices have become lighter, thinner, shorter, smaller, and more multifunctional, motivating micro drilling technology to become more sophisticated. To meet the demands of electronic applications, this paper proposes a drilling machine tool with a counterbalance vibration control mechanism. In this report, focusing on the timing of table feed rate changes during drilling, drilling experiments were conducted using four drilling paths while changing the table movement direction and feed rate along the machining path. The accuracy of the positions of the drilled holes and condition of the drill edge after drilling were then evaluated.

Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II

This work addresses the prediction and optimization of average surface roughness (Ra) and maximum flank wear (Vbmax) of 6061 aluminum alloy during high-speed milling. The investigation was done using a DMU 50 CNC 5-axis machine with Ultracut FX 6090 fluid. Four factors were examined: the table feed rate, cutting speed, depth of cut, and cutting length. Three levels of each factor were examined to conduct 81 experiment runs. The response parameters in these experiments were measurements of Ra and Vbmax. We applied a two-pronged approach that combines machine learning (ML) and a Nondominated Sorting Genetic Algorithm (NSGA-II) to model and optimize Ra and Vbmax. Four ML models were used to predict Ra and Vbmax: linear regression (LIN), support vector machine regression (SVR), a gradient boosting tree (GBR), and an artificial neural network (ANN). The input variables were the significant factors that affect the surface quality and tool wear: the feed rate, depth of cut, cutting speed, and cutting time. Several quality metrics were employed to quantify the performance of the models, such as the root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). As a result, SVR and ANN were found to have the best predictive performance for Ra and Vbmax. These models and the NSGA-II-based approach were then employed for multiobjective optimization of cutting parameters during high-speed milling of aluminum 6061. Fifty Pareto solutions were found with Ra in the range of 0.257 to 0.308 µm and Vbmax in the range of 136.198 to 137.133 μm. Experimental validations were then conducted to confirm that the optimum solution was within an acceptable error range. More precisely, the absolute percentage errors for Ra and Vbmax were 2.5% and 1.5%, respectively. This work proposes an effective strategy for efficiently combining machine learning techniques and the NSGA-II multiobjective optimization algorithm. The experimental validations have reflected the potential for applying this strategy in various machining-optimization problems.

Investigation of the machining performance of ferritic ductile cast iron in WEDM using response surface methodology

Wire electrical discharge machining (WEDM) technology is a special electrothermal processing method that can precisely production of parts with variable stiffness with sharp edges or production of complex geometric parts which are difficult to produce by traditional manufacturing methods. It has an important place in production sector in terms of low energy consumption. In this study, the relationship between processing parameters on surface quality on the ferritic ductile cast iron (GGG-40) material in WEDM process with molybdenum wire was investigated by Response Surface Methodology (RSM). The aim of this study is to determine the optimum process parameters for low-cost production of GGG-40 material with sharp-edged and complex geometry parts using the WEDM method. In experimental works, surface roughness, and process time were investigated using table feedrate, pulse on time, and pulse space as cutting parameters. The surfaces obtained as a result of the experiments were evaluated in terms of surface quality with Scanning Electron Microscopy (SEM), and surface roughness device. According to the findings, it has been observed that the surface roughness has increased with increasing table feedrate, and pulse on time, and surface roughness decreased with pulse space increasing. Also, it is understood that pulse on time is the most important factor effecting surface quality. It has been found that the process time depends on only the table federate where they are inversely proportional. As result of RSM analysis, optimum cutting parameters were obtained in terms of lowest surface roughness, lowest process time and best time/performance condition on both parameters for ferritic ductile cast iron in WEDM process.

Comparative studies of variation in cutting conditions and cutter nomenclature on the surface morphology and the integrity of slot milled nimonic 263 alloy

Cutter nomenclature and machining conditions has invoke critical impact on the machining behavior and surface integrity of machined samples. In this investigation, the slot milling operation has been performed under various cutter terminology or nomenclature (cutter with the RRA of −7°, 0° and 7°) and cutting conditions (spindle speed, table feed and MQL flow rate) to analyze its resulting outcome on the surface morphological features such as surface roughness (Sa), skewness (S sk ) and kurtosis (S ku ), etc Because the examination of these characteristics are important and significant to analyze the behavioral changes of asperities such as decohesion, wear resistance and adhesion, etc during in its relative motion. Additionally, the plasticity index and surface morphology of machined samples are helps to predict the variation in surface morphology under various machining behavior and through this study, it is found that the interactive effect of MQL flow rate and table feed offer higher and significant impact over the surface characteristics followed by the MQL flow rate during slot milling process.

Mathematical and MATLAB based process optimization by simulated annealing algorithm for wire electrical discharge machining of EN31

The inevitability to machine hard materials and intricate shapes that are hard to be worked by traditional methods have stressed the need for non-traditional manufacturing processes specifically Wire Electro Discharge Machining (WEDM). WEDM encompasses intricate processes that include heating as well as cooling. The working parameters include pulse on time, pulse off time, table feed rate, flushing pressure, wire tension, wire velocity etc. has to be preferred suitably so that an optimized result can be attained. A single constraint has been chosen for the purpose of optimization to maximize the Metal Removal Rate (MRR). In this work a gear was machined out of EN31 material using the WEDM process and the process parameters such as pulse on time, peak current, wire feed rate and machining speed have been optimized using Simulated Annealing Algorithm and also using MATLAB based optimization. Simulated Annealing (SA) based optimization has been established to optimize the parameters in order to improve MRR. The objective function for metal removal rate is obtained based on the mathematical model.

Impact of nozzle design on grinding temperature of hardened steel under MQL condition

Minimum Quantity Lubrication (MQL) system has successfully replaced the conventional cooling system of machining with its remarkable advantages and environment friendly nature. However, application of MQL in grinding has faced more complications to reduce cutting temperature than other regular machining processes (milling, turning). In this study, a modified nozzle was designed to increase the effectiveness of MQL in grinding operation. The performance of modified nozzle was compared with the conventional nozzle in terms of grinding temperature. Experiment was conducted with a set number of input parameters (hardness, depth of cut, table feed rate) and results revealed that lower temperature was always observed in modified nozzle assisted grinding. Finally, a Response Surface Methodology (RSM) model was developed to optimize the machining input parameters for achieving lowest grinding temperature. Higher value of regression coefficients proved the acceptability of the optimization model.

Experimental Assessment of Effect of Backlash Control Parameters on Quadrant Protrusions of Circular Tests for CNC Machine Tools

Backlash, friction, and servo lag factors often result in protrusion or segment difference phenomenon in the moving speed reversal of a machine tool’s moving table. This phenomenon can be improved by adjusting the backlash control parameters of the machine tool controller, but the control parameters must vary with the feed rate and payload of the moving table. Therefore, this study performed the circular test process for CNC machine tools, and used different feed rate, radius, and payload motion conditions to discuss the effect of backlash control parameters on quadrant protrusions. First, this study used parameter-range reduction combined with the Taguchi method and the binary search algorithm to search for the optimal backlash control parameters in the parameter setting range, so that the machine tool could have preferable quadrant protrusion performance when executing circular tests. Afterward, the correlation of the moving table feed rate, radius, and payload to the quadrant protrusion was analyzed according to the experimental results. The results indicated that the machine tool moving table feed rate had the most apparent effect on quadrant protrusions, and the relationship between the payload and quadrant protrusion was influenced by the moving table feed rate and circular radius simultaneously.

Nanofluid-based Minimum Quantity Lubrication (MQL) Face Milling of Inconel 625

Machining with minimum quantity lubrication (MQL) has gained widespread attention to boost machining performance of difficult to machine materials such as Ni-Cr alloys, especially to reduce the negative impact of conventional flooded machining on environment and machine operator health. The present study is aimed to evaluate MQL face milling performance of Inconel 625 using nano cutting fluid based on vegetable oil mixed with multi-walled carbon nanotubes (MWCNT). Experiments were designed with 2-level factorial design methodology. ANOVA test and desirability optimisation method were employed to arrive at optimised milling parameters to achieve minimum tool wear and machined surface quality. Experiments were performed under nanoparticles based minimum quantity lubrication (NMQL) conditions using different weight concentrations of MWCNT in base oil: 0.50, 0.75, 1, 1.25 and 1.5 wt. %; and pure MQL environment (without nanoparticles). The optimal MQL milling parameters found are cutting speed: 47 m/min, table feed rate: 0.05 mm/tooth and depth of cut: 0.20 mm. The results revealed improvement in the surface finish (Ra) by 17.33% and reduction in tool flank wear (VB) by 11.48 % under NMQL face milling of Inconel 625 with 1% weight concentration of MWCNT in base oil compared to pure MQL machining conditions.

Prediction of specific grinding forces and surface roughness in machining of AL6061-T6 alloy using ANFIS technique

PurposeOptimisation of grinding processes involves enhancing the surface quality and reducing the cost of manufacturing through reduction of power consumptions. Recent research works have indicated the minimum quantity lubrication (MQL) system is used to achieve near dry machining of alloys and hard materials. This study aims to provide an experimental analysis of the grinding process during machining of aluminium alloy (Al6061-T6). MQL nanofluid was used as the lubricant for the grinding operations. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality was studied. Adaptive neuro-fuzzy inference system (ANFIS) prediction modelling was used to predict the specific normal force, specific tangential force and surface quality, the ANFIS models were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further study shows that both the specific grinding forces and surface roughness are inversely proportional to the nanofluid concentration. Also, the depth of cut and table feed rate were found to have a directly proportional relationship with both the grinding forces and surface roughness. Moreover, higher MQL air pressure was found to offer better delivery of the atomised nanofluid into the grinding region.Design/methodology/approachGrinding experiments were performed using MQL nanofluid as the lubricant. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality has been studied.FindingsThe grinding process parameters were optimised using Taguchi S/N ratio analysis, whereas the prediction of the response parameters was done using ANFIS modelling technique. The developed ANFIS models for predicting the specific normal force, specific tangential force and surface quality were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further findings show that both the specific grinding forces and surface roughness are inversely proportional to the percentage of nanoparticle concentration in the lubricant. Also, the depth of cut and table feed rate were found to exhibit a direct proportional relationship with both the grinding forces and surface roughness, while high MQL air pressure was observed to offer more efficient delivery of the atomised nanofluid into the grinding region.Practical implicationsThe work can applied into manufacturing industries to prevent unnecessary trials and material wastages.Originality/valueThe purpose of this study is to develop an artificial intelligent model for predicting the outcomes of MQL grinding of the aluminium alloy material using ANFIS modelling technique.

Optimization and characterization of friction surfaced coatings of ferrous alloys

Abstract In the present work, the scientists were successful in obtaining a friction surfaced coating of mild steel over mild steel, mild steel over stainless steel (AISI 304) and stainless steel over stainless steel using a low-cost conventional milling machine. A 22 factorial method with three replications was used to design the experiments. The influence of variation in rotational speed (1400 rpm and 1000 rpm) and table feed rate (4.17 mm/s and 2.67 mm/s) on coating width, thickness and interface temperature of the coating and substrate was investigated. Multi-response optimization was performed and the developed model was validated by confirmatory experiments. The results showed that, with an increase in rotational speed and table feed rate, width and thickness of the coating decreases, while temperature increases. An infrared (IR) camera provided thermographs that elaborated the distinct stages of heat dissipation during the process of coating formation. The bond integrity and strength of the coating was analyzed by bend tests and Vickers micro hardness test. The results revealed that a higher hardness value was obtained at the interface of the coating as compared to coating and interface.

Performance evaluation of rotary mechanism characteristics by response surface methodology in cylindrical wire electrical discharge turning

Cylindrical wire electrical discharged turning (CWEDT) is currently used for machining hardened and delicate cylindrical parts due this process neglects the issues in electrode wear and cutting force in removing the materials. Recently, many researchers have focused on investigating the CWEDT machine parameter for obtaining desired machining parts quality. However, the characteristics of the rotary mechanism itself has potential to influences of the parts quality. Therefore, the objective of this study is to evaluate the rotary mechanism characteristics on surface roughness and material removal rate (MRR). The investigation of the characteristics of rotary mechanism consists rotational spindle speed, radial depth of cut, table feed rate, workpiece overhang and spindle direction. Central composite design (CCD) of response surface methodology (RSM) as experimental design that was employed to analyse the result and generated a mathematical prediction model. The experimental results showed the feed rate is the dominating factor for surface roughness and depth of cut is dominating for MRR. The models found significant for the both responses and reliable with experimental result with prediction error less than 7%. The prediction of multi-response optimization values for surface roughness and MRR are 4.525 μm and 19.147 mm3/min, respectively.

Optimization of Surface Roughness and Metal Removal Rate in End Milling using Taguchi Grey Relational Analysis

Objectives: The objective of the present work is to assess the effects of machining parameters in milling on surface roughness and metal removal rate of AISI H11 steel. It is used in the manufacturing industries for making die casting moulds, extrusion dies, moulds for glass industry, punches, piercing tools, mandrels etc. Methods/Statistical Analysis: The objective of the study was carried out by machining experiments which were conducted on CNC vertical milling machine whose maximum speed was 6000 RPM. Design of experiments based on Taguchi grey relational analysis with three independent factors (cutting speed, feed rate and depth of cut), three levels L27 orthogonal array has used to develop relationships for predicting surface roughness and metal removal rate. Findings: The surface roughness was measured using surface roughness tester (Mitutoyo surftest-4) and the averages were calculated to obtain the surface roughness of the samples. Metal removal rate was calculated using the formula in terms of width of cut, depth of cut and table feed rate. Improvements: Model significance tests were conducted using ANOVA table and effects of various parameters were investigated.

Experimental Investigation and Modeling of Single Point Incremental Forming for AA5052-H32 Aluminum Alloy

Single point incremental forming (SPIF) is highly flexible sheet metal forming process used for small quantity production and new product development. The product with high strength, good surface finish, and higher formability has paramount importance in industrial and marine applications. SPIF has been carried out on AA5052-H32 aluminum alloy which has high strength and difficulty in the conventional forming process. The response characteristics such as surface roughness \(({R}_{\mathrm{a}})\) and maximum forming angle \((\varnothing _{\mathrm{max}})\) were evaluated by considering the independent process parameters such as spindle speed, table feed rate, step depth, tool diameter and sheet thickness through the design of experiments. The step depth and sheet thickness are the most influencing parameters for average surface roughness and maximum forming angle, respectively. It is found that neither the surface roughness nor the forming angle of formed sheets feels the effects of spindle speed significantly. An empirical relation has been formulated, and experiments were carried out to verify the reliability of the developed regression model.

Optimization of MQL flow rate for minimum cutting force and surface roughness in end milling of hardened steel (HRC 40)

The present work focuses on the performance modeling of hard milling to attain an optimum parameter setting for the minimum cutting force and surface roughness. Furthermore, it was attempted to compute the minimum quantity lubricant flow rate precisely, besides the cutting speed and table feed rate, by adopting Grey-based Taguchi method and composite desirability function. The experimental data was collected by end milling of hardened AISI 4140 steel using carbide cutter under dry and minimum quantity lubrication conditions according to Taguchi L 16 orthogonal array. The predictive model of the responses was formulated by using response surface methodology. The analysis of variance revealed that the table feed has the maximum influence on cutting force, and the flow rate of lubricant has the highest effect on surface roughness. The parameter setting at lower table feed, higher cutting speed, and 150-ml/h lubricant flow yield the minimum value of the responses. Finally, the results of confirmation test verified the adequacy and supremacy of the optimization models; however, Grey-based Taguchi method induced a better optimization.

Investigations on Surface Milling of Hardened AISI 4140 Steel with Pulse Jet MQL Applicator

In this article, an experimental investigation was performed in milling hardened AISI 4140 steel of hardness 40 HRC. The machining was performed in both dry and minimal quantity lubricant (MQL) conditions, as part of neat machining, to make a strong comparison of the undertaken machining environments. The MQL was impinged int the form of pulse jet, by using the specially developed pulse-jet-attachment, to ensure that the cutting fluid can be applied in different timed pulses and quantities at critical zones. The tool wear, cutting force and surface roughness were taken as the quality responses while cutting speed, table feed rate and flow rate of the pulse were considered as influential factors. The depth of cut was kept constant at 1.50 mm because of its less significant effects and the straight oil was adopted as cutting fluid in pulse-jet-MQL. The effects of different factors, on the quality responses, are analyzed using ANOVA. It is observed that MQL applicator system exhibits overall better performance when compared to dry milling by reducing surface roughness, cutting force and prolonging tool life but a flow rate of 150 ml/h has tremendous effects on the responses. This investigation and afterward results are expected to aid the industrial practitioner and researcher to adopt the pulse-MQL in high speed milling to prolong tool life, reduce tool wear, diminish cutting force generation and promote better surface finish.

Study of Peck drilling of borosilicate glass with μRUM process for MEMS

Right selection of process parameters is the most important decision to achieve superior quality of micro hole such as less edge chipping, less taper of hole and accurate diameter of drilled hole on brittle ceramic materials. Peck drilling methodology has been adopted to drill 1mm thick borosilicate glass (bk7) material and a mathematical formula has been derived to estimate material removal rate (MRR) in peck drilling. Present work correlated inter-relationships of various μRUM machining parameters namely spindle speed, distance traverse in each stroke; feed rate, vibration amplitude and vibration frequency on edge chipping area, taper and cutting force using response surface methodology (RSM) for peck drilling operation. The experimental results revealed that spindle speed, distance traverse in each stroke; table feed rate, vibration amplitude and vibration frequency significantly affected the edge chipping area and taper size; while distance traversed in each stroke and table feed rate affected the cutting force. The validation of the developed model showed that the edge chipping area, taper and cutting force of μRUM of borosilicate glass could be estimated with reasonable accuracy using second order models. Trust region method for nonlinear minimisation was used to find the optimum level of parameters for minimising edge chipping area. Optimised parameters were used to realise actual job and carried out 114 numbers of Ø300μm hole drilling on bk7 work material successfully.