CAE-ECM system for electrochemical technology of parts and tools

Journal of Materials Processing Technology 107 (2000) 293±299CAE-ECM system for electrochemical technology of parts and toolsJerzy Kozak * , Lucjan Dabrowski, Konrad Lubkowski, Marek Rozenek, Robert SøawinÂskiInstitute of Manufacturing Engineering, Warsaw University of Technology, ZOWE, Al.Niepodleglosci 222, 00-663 Warsaw, PolandAbstractThis paper presents the concept and prototype of a computer aided engineering (CAE) system that can be used to solve different task ofelectrochemical machining (ECM), such as: tool-electrode design, selection of optimal machining variant and input machining parametersoptimization. The system uses computer simulation software that was developed for various kinds of ECM operations like: electrochemical(EC) sinking, EC milling, EC smoothing, ECM-CNC with a universal electrode and numerically controlled electrode movement, etc. Theresults of computer simulation of different ECM processes and results of experimental veri®cations are also presented in the paper.# 2000 Elsevier Science B.V. All rights reserved.Keywords: Electrochemical machining; Electrode design; Computer simulation; Experimental veri®cation1. IntroductionElectrochemical machining (ECM) is an effective way ofmanufacturing of complex shaped parts. It is used for varietyof materials, including those that are hard to machine bymeans of traditional metal cutting. Various variants of theECM like: electrochemical sinking, ECM with numericallycontrolled tool-electrode movement, ECM with orbitingtool-electrode, pulse ECM, electrochemical smoothing,electrochemical deburring are used in industrial practice.All of them are characterized by high ef®ciency and lack ofwear of tool-electrode. Moreover, surface of workpiecemachined by any of ECM processes is of high qualityand stress free. Therefore, use of ECM for production ofdies, parts of turbine and high compression engines, medicalimplants, parts for electronic and military industries, etc. iswell justi®ed.Although attractive for reasons stated above implementationof ECM may not be easy. Two major dif®culties that areencountered during ECM process preparation involve toolelectrodedesign and machining input parameters selection.Very often in order to achieve desired output, labor and timeconsumingtrial-and-error method has been used to adjustshape of tool and set of parameters. Due to prohibitive costsof such approach research centers and different companieshave been tying to develop means to reduce this cost andlead-time to production. One of them that can be applied at* Corresponding author. Tel.: ‡48-22-6288110; fax: ‡48-22-6607520.E-mail addresses: jkozak@meil.pw.edu.pl (J. Kozak), ld@meil.pw.edu.pl(L. Dabrowski).the earliest stages of ECM process design is computersimulation.Mathematical model of the ECM consists of a set ofnonlinear partial differential equations with complex boundaryconditions, e.g. moving boundary on machined surfaceof a workpiece. Its high complexity causes that in order toobtain reliable results for particular technological task it isnecessary to perform complex numerical calculations. CAE-ECM system, presented in this paper, has the ability necessaryto evaluate such complex models for various tasks inECM.CAE-ECM system has been designed to help to solvefollowing technological problems: simulation of the workpiece shape change during machiningwith a fixed tool-electrode profile including accuracyanalysis, tool-electrode design for a required workpiece shape, simulation of ECM smoothing process, determination of basic characteristics of different variantsof the ECM process (ECM with rotating electrode, pulseECM, ECM with vibrating electrode, etc.).Scheme of structure of CAE-ECM system is shown inFig. 1. Selected parts of the CAE-ECM system are discussedbelow.2. Simulation of electrochemical shapingIn ECM, there is no physical contact between electrodes(tool and workpiece). Shape of workpiece after ECMdepends on geometry of tool-electrode as well as on ®nal0924-0136/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.PII: S 0924-0136(00)00685-3

294 J. Kozak et al. / Journal of Materials Processing Technology 107 (2000) 293±299 initial shapes of tool-electrode ( f ) and workpiece (F 0 ); initial positions of electrodes; hydrodynamic parameters; others that are necessary for numerical calculations likerequired accuracy, etc.The main task in ECM shaping, regardless of variant, is tocalculate electric ®eld distribution in machining area, in amedium of varying electrical conductivity, with complexprocesses occurring on the surfaces of the electrodes andwith shape change of machined surface during course ofmachining. Relations between main factors occurring duringECM are shown schematically in Fig. 2. Since properties ofelectrolyte depend on temperature and gas-phase concentration(mainly on concentration of hydrogen generatedduring machining) which distributions depend on velocityand pressure ®elds as well as on current density, ECMprocesses have to be described by set of mass, heat andelectric charge transfer equations. In presented CAE-ECMsystem, temperature (T) distribution and void (gas) fraction(b) are calculated for direction along the path of electrolyte¯ow as well as in direction normal to the ¯ow. Assumptionsused for modeling can be found in [3]. As a result currentdensity distribution can be estimated with much higheraccuracy that has a tremendous impact on tool designprocess and workpiece shape change estimation. Also,more accurate calculations of T and b distributions allowto estimate limiting speed of machining above whichECM process becomes unstable what, in turn, leads toFig. 1. Structure of CAE-ECM system.gap between tool and workpiece. The ®nal gap (S) distributiondepends on tool-electrode shape, kinematics oftool-electrode, electrical and hydrodynamic parameters ininterelectrode gap during machining and on a form of basiccharacteristics of anodic dissolution for given material±electrolyte arrangement.The main goal of computer simulation is to calculate,along and across the electrolyte ¯ow and at given instance oftime, the following quantities: interelectrode gap distribution (S ) which is equivalent todetermination of the shape of workpiece, distributions of fields of: temperature (T ), volumetric gasphaseconcentration (b), velocity of electrolyte (w), staticpressure ( p), electrical current density ( j ) in the interelectrodegap and velocity of dissolution (V n ).The set of input parameters for simulation consists of: properties of electrolyte and workpiece material; feed rate of tool-electrode (V f );Fig. 2. Relations between main factors occurring during ECM.

J. Kozak et al. / Journal of Materials Processing Technology 107 (2000) 293±299 295of electrodes, are very important in ECM input parametersselection. The input parameters should always be chosensuch that the maximum temperature of electrolyte neverreaches its boiling point. One-dimensional model, in whichonly average values of T (Fig. 5b), and b across the gap canbe calculated, may not be accurate enough to properlyestimate the maximum temperature. Use of input parametersfrom simulation that underestimated electrolyte temperaturefor actual machining may lead to short-circuit betweenelectrodes, and what follows, to damage of tool and workpiece.Ability of CAE-ECM system to predict workpiece shapeafter machining was veri®ed experimentally. ECM sinkingof workpiece made of WNL tool steel (0.55% C, 0.7% Mn,2% Si, 0.7% Cr, 1.6% Ni, 0.25% Mo) was performed. Watersolution of NaNO 3 of 15% was used as electrolyte. Machiningwas performed for feed rates V f ˆ 0:6, 0.8, 1.0 mm/min,working voltage U ˆ 16 V and electrolyte gap inlet pressurep 0 ˆ 0:6 MPa. Tool-electrode used in experiment wasdesigned using the CAE-ECM system.In Fig. 6, actual and calculated workpiece shapes usingthe CAE-ECM are shown. The areas where the biggestdifference between the shapes was observed are magni®edin Fig. 7.Experimental veri®cation showed good agreementbetween theoretical and actual results. The analysis ofaccuracy of machined workpieces showed that maximumshape error is less than 0.02 mm or 5% of the gap size. Theerror is greater near the inlet of the electrolyte. This error canbe attributed to the approximate distribution of the electrolyte¯ow and electrical ®eld estimation at the electrolyteentrance region of the gap.3. Tool-electrode designFig. 3. Simulation algorithm.critical states with electrical discharges. The mathematicalmodel of the ECM process used in presented CAE-ECMsystem is described in [3]. Simulation algorithm is shown inFig. 3.Examples of simulation of ECM shaping are shown inFig. 4a and b. In Fig. 4a, results for simulation of ECM withconstant feed rate are shown. In Fig. 4b, results for machiningwith additional oscillations of tool-electrode are presented.Additional harmonic movement of tool-electrodesigni®cantly improves conditions in interelectrode gap thatresults in much greater dimensional accuracy of the process.In these ®gures, subsequent graphs illustrate anode-workpieceshape evolution in time.Electrolyte temperature distributions across the interelectrodegap at the point where electrolyte exits the gap (whereit reaches its highest temperature) are shown in Fig. 5a and b.The two maxima that can be observed in Fig. 5a in proximityIn order to obtain a desired shape of workpiece withincertain accuracy and for a given set of ECM input parametersthe tool-electrode needs to be properly designed andmanufactured. In such a design, ®nal interelectrode gapdistribution was uneven.In CAE-ECM system iterative trial-and-error method isused for tool-electrode design. At ®rst initial, approximatepro®le of tool-electrode is calculated on the basis of theso-called ``cosine law'', using constant electrochemicalproperties of material±electrolyte arrangement [1,2]. Next,simulation of ECM using the approximated shape of toolelectrodeis performed and errors obtained between F i anddesired F shapes of workpiece are calculated, DF ˆ F i F.Then, the tool shape is corrected using weighted valuesof the errors and another simulation is performed. Thisiteration cycle is repeated until some accuracy criterionis satis®ed. During iteration process software checks ifphysical conditions of machining are within imposed limitssuch as T < T max ; b < b max ; w < w max , etc. has to betaken into account.

J. Kozak et al. / Journal of Materials Processing Technology 107 (2000) 293±299 297Fig. 5. (Continued ).In Fig. 8, results of experimental veri®cation of ECM with¯at electrode are shown. In this ®gure shape deviations forthe surface that was machined with corrected, using theCAE-ECM system, electrode are shown. It is important tomention here that these errors before correction were 10times bigger and their values were about 97% of gap size.After correction their values dropped to about 5% of gap size.4. Dimensional accuracy analysis of ECM shapingTo illustrate dimensional analysis of ECM shaping,results for ECM of a turbine blade are presented. For givenanode (workpiece) pro®le, marked with thin line in Fig. 9,tool-electrode shape was calculated using the CAE-ECMsystem as shown using thick line in the same ®gure.Calculations were performed using following set of inputparameters: workpiece material: Inconel alloy; electrolyte: 13% water solution of NaNO 3 ; electrochemical machinability: K v ˆ 1:64 2:13 exp…0:03i† mm 3 =A min, where i is a current density inA/cm 2 ; voltage U ˆ 12 V; total overpotential E ˆ 3V;Fig. 6. Actual and calculated pro®les (solid line) comparison.Fig. 7. Areas of the greatest differences between actual and calculatedshapes (solid line).

298 J. Kozak et al. / Journal of Materials Processing Technology 107 (2000) 293±299Fig. 8. Experimental veri®cation of ECM with ¯at electrode. sinking feed rate V f ˆ 1mm=min; inlet electrolyte velocity w ˆ 10 m=s; outlet pressure p k ˆ 0:1 MPa; accuracy of calculated tool-electrode shape DF ˆ 2 mm.Calculated distributions of S, w, p, T, b and i as functionsof distance along the electrolyte ¯ow (with x ˆ 0 at the inlet)are shown in Fig. 10. The change in interelectrode gapwidth, S, results from blade's feather pro®le change aswell as from change of physical conditions along electrolyte¯ow.To evaluate in¯uence of ECM input parameters on interelectrodegap distribution (or, in other words, on workpieceshape error distribution) computer simulations for differentvalues of voltage, feed rate and inlet electrolyte velocitywere performed. Following values for these parameters wereused: inlet electrolyte velocity w ˆ 5, 10 and 15 m/s; voltage U ˆ 8, 12, 16 V; feed rate V f ˆ 0:75, 1.00, 1.50 mm/min.Fig. 9. Tool and blade pro®le.Some results for these simulations are shown in Fig. 11.The biggest values of gap width, S(x), occur at the pointwhere electrolyte exits that gap. They result from electrolytea conductivity change that is caused by temperature and gasfraction increase. Decrease of inlet velocity of electrolytecauses decrease of gap width at the electrolyte outlet.Gap width signi®cantly depends on pressure at the outletthat can be seen from graphs in Fig. 11 for p k ˆ 0:10 and0.15 MPa.Fig. 10. Calculated distributions of S, w, p, T, b and j as functions ofdistance along the electrolyte ¯ow.Fig. 11. Gap width for different input parameters.

J. Kozak et al. / Journal of Materials Processing Technology 107 (2000) 293±299 299Much more pronounced in¯uence on y coordinate of thepro®le have working voltage, U, and electrode feed rate, V f .As an example, in¯uence of feed rate on shape deviation isshown in Fig. 13.Results show that stabilization of these parameters isnecessary during machining. During ECM their valuesshould be maintained as close as possible to their nominalvalues, i.e. values that were used for tool-electrode design.Fig. 12. Distribution of pro®le deviations with respect to reference pro®leblp5 for different electrolyte velocities.5. ConclusionsThe presented CAE-ECM system can be useful forprocess planing for different variants of ECM. It can beused for process analysis, tool design and parameters selection.Presented results for ECM sinking showed goodagreement between theoretical predictions and actual experimentalresults. Conclusion can be made that this software``CAE-ECM'' has great potential to be used in industryapplications.AcknowledgementsFig. 13. Distribution of pro®le deviations with respect to reference pro®leblp5 for different electrode feed rates.Increase of outlet pressure causes signi®cant increase ofgap width that can be explained by decrease of concentrationof gas phase. Changes of pro®les in y direction with respectto reference pro®le, blp5, for different electrolyte velocitiesare shown in Fig. 12. Despite signi®cant changes of inletvelocity the maximum difference between pro®les wasrelatively small (