Using Industrial Robots to Manipulate the Measured Object in CMM
Transcription
Using Industrial Robots to Manipulate the Measured Object in CMM
ARTICLE International Journal of Advanced Robotic Systems Using Industrial Robots to Manipulate the Measured Object in CMM Regular Paper Samir Lemes1,*, Damir Strbac1 and Malik Cabaravdic1 1 Mechanical Engineering Faculty, University of Zenica, Zenica, Bosnia and Herzegovina * Corresponding author E-mail: [email protected] Received 10 Oct 2012; Accepted 24 Apr 2013 DOI: 10.5772/56585 © 2013 Lemes et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Coordinate measuring machines (CMMs) are widely used to check dimensions of manufactured parts, especially in the automotive industry. The major obstacles in automation of these measurements are fixturing and clamping assemblies, which are required in order to position the measured object within the CMM. This paper describes how an industrial robot can be used to manipulate the measured object within the CMM work space, in order to enable automation of complex geometry measurement. Keywords Industrial Robot, CMM, Measurement 1. Introduction In today’s global market, the importance of correct, reliable and comparable measurements is the key factor for achieving quality in activities and procedures in every area of industry. Calibration, testing and measurement are necessary elements in the development process or progress in many disciplines of science and industry. The majority of modern industrial measurements can be categorized as GDT (Geometrical Dimensioning and Tolerancing). Increasingly, measurements obtained by coordinate measuring machines (CMM) are being used. www.intechopen.com CMMs are measuring devices with high measuring speed. Positioning and rotation of the measured object are always performed manually in the work area of the coordinate measuring machine. The object, with defined dimensions, shape and measuring surfaces, is measured and controlled from several different sides. The measured object needs to be positioned in certain positions relative to the measuring device, which requires complex and time-consuming actions. Each change of position also requires a certain time, which can cause increased costs in control and production processes. In order to reduce these costs, several options for positioning a measured object inside the working area of a CMM using an industrial robot have been considered. In a modern industrial environment the majority of robots are automated systems controlled by computers. Industrial robots have one or more robotic arms, control devices with memory, and sometimes use sensors for data acquisition. They usually support the manufacturing process by positioning objects during machining or welding, transportation, various technological operations, automatic assembly, etc. They are also sometimes used for pre-process, process and post-process control. Industrial robots are widely used in processes which require high quality and productivity. Int.Strbac j. adv.and robot. syst., 2013, Vol.Using 10, 281:2013 Samir Lemes, Damir Malik Cabaravdic: Industrial Robots to Manipulate the Measured Object in CMM 1 Research along these lines has been conducted by Santolaria and Aguilar [1]. They conducted a survey about the development of kinematic modelling of robotic manipulators and articulated arm coordinate measuring machines (AACMM), taking into consideration the influences of the chosen model on procedure parameters. Their optimization algorithm included the terms linked to the accuracy and repeatability of the procedure presented. The algorithm follows the simple optimization scheme of data obtained by investigation in several spheres of objects placed at various positions within the working area of both systems. The majority of research mostly concentrates on differences in the influences on measurement uncertainty in Coordinate Measuring Machines. Lawford [2] observed dysfunctional CMS software with unknown measurement uncertainty and compared its influence with measurement results. He also investigated the prescribed testing algorithms and the checking of industrial software, testing by comparison with given algorithms. This yielded solutions to similar problems. Fang, Sung and Lui [3] observed the influence of measurement uncertainty from CMM calibration and temperature in the working environment. If the measurement uncertainty in CMM calibration is reduced, this will also reduce the measurement uncertainty of the machine itself. They also pointed out the importance of temperature balance in the working environment before the measurement is performed, i.e., the temperature should be controlled in order to fit CMM working specifications. CMM uncertainty can be reduced using highly precise instruments such as a laser interferometer. One of the first papers about CMM error compensation was presented by Zhang et al. [4]. They described the error compensation on bridge-type CMM, which resulted in an improvement of accuracy by a factor of 10. They also presented the correction of vector of equally distributed points in the measured volume. Software error compensation has been reported by a number of authors. Ferreira and Liu [5], for example, developed the analytical model for geometric errors of the machining assembly; Duffie and Yang [6], meanwhile, invented a method to generate the kinematic error function from volumetric measurement error using a vectorial approach. Robot-CMM integration was performed for the first time by the Mitutoyo Company [7]. They developed a software module in order to adjust the actions of CMM and robotic handling machines used for manipulation of measured parts. Mitutoyo has released the source code in the hope that third party software vendors will be able to use it as a basis to develop products. To the authors’ knowledge, 2 Int. j. adv. robot. syst., 2013, Vol. 10, 281:2013 at the time of writing no achievements have been made in this direction. Hansen et al. [8] estimated measurement uncertainty of a hybrid system consisting of an Atomic force microscope attached to a coordinate measuring machine, using linear combination of these two components. Although Hansen et al. also combined two devices, their approach nevertheless differs from ours: we use one system to position the measured object, while they used a twocomponent system to perform the measurement. Aggogeri et al. [9] used simulation and planned experimentation to assess the measurement uncertainty of CMMs. They identified and analysed five influence factors, and showed that simulation can successfully be used to estimate CMM uncertainty. Weckenmann et al. [10] investigated how measurement strategy affects the uncertainty of CMM results. They defined the measuring strategy in relation to “operator influence”, which has been neglected in other research. This work showed that measuring strategy influences CMM uncertainty, and that scanning capabilities of modern CMMs, using significantly a larger number of touch points, overcome this influence. Wilhelm et al. [11] also investigated the influence of measurement strategy, which they defined as the “task specific uncertainty”. They also showed that virtual CMM, using Monte Carlo simulation, can be used to estimate uncertainty. Nevertheless, although these authors mentioned that part fixture influences uncertainty, they did not analyse this thoroughly. Feng et al. [12] applied the factorial design of experiments (DOE) to examine measurement uncertainty. They also studied the effect of five factors and their interaction, and showed that there is statistically significant interaction between speed and probe ratio. They also showed that uncertainty is minimized when speed is highest, stylus length is shortest, probe ratio is largest, and the number of pitch points is largest. Piratelli-Filho and Giacomo [13] proposed an approach based on a performance test using a ball bar gauge and a factorial design technique to estimate CMM uncertainty. They investigated the effect of length, position, and orientation in work volume on CMM measurement errors. The analysis of variance results showed a strong interaction between the orientation and measured length. Unlike the mentioned studies, the goal of the research presented here was to assess whether robots can be used to position the measured object in complex measuring systems, using measurement uncertainty analysis and estimating the factors affecting it. www.intechopen.com 2. Problem deescription Fig. 1 show ws a typical assembly used to clamp p the uires measured ob bject in a CMM. Such a system requ multiple meeasuring and d clamping operations w when different feaatures of thee measured object are b being measured, eespecially if the t geometry y is complex and some portion ns are inacceessible by CM MM probes. SSuch products sho ould be measu ured in multiplle steps. Figure 1. Typiccal fixturing asssembly for CMM M measurementts The major time-consu uming task in coordiinate measuremen nt of complex x geometry with w CMMs iis to choose the position of the t measured d object and d the optimal comb bination of prrobe stylii, wh hich often preevent the touch p probes from coming c into contact with h the measured ob bject. The obsscured surface es are difficu ult to reach withou ut repositionin ng the measu ured object. E Every repositioning g of the meaasured objectt introduces new error sourcess in the measu urement. Our idea is to usee the industrial rob bot to manipu ulate the measured object, i. e., to position it au utomatically. were easurements w In order to ttest this possiibility, the me conducted w with three diffeerent systems: 1. 2. 3. Measurin ng fixed objecct with CMM only; o Measurin ng with comp plex-CMM-robot system , with fixed maass of measureed object; Measurin ng with com mplex CMM-ro obot system, with variable mass of meassured object. on to use thee measurement uncertaintty to It is commo quantify thee quality off the measu urement proocess. Therefore, w we decided to t estimate itt for these tthree systems, and d to compare th hem with the uncertainty oof the robot and thee CMM as statted by the man nufacturers. 2.1 Hypothesees In order to p prove whetheer it is possib ble to use a roobot, with structurrally and tech hnologically liimited option ns, in procedures o of precise meaasurement wiith a CMM, aat the beginning off the research the following g three hypoth heses were set: www.intechopen.com • • • Hypothesis 1: 1 It is possiblee to use the first generation n robot with five degrees oof freedom fo or positioning g measured object on CMM.. Hypothesis 2: Uncertain nty of meassurement forr complex CM MM-robot meeasuring syste em is within n limits of alllowed uncerttainty of mea asurement off CMM. nty of meassurement forr Hypothesis 3: Uncertain complex CM MM-robot meaasuring system m depends on n measured object mass. nalysing thee These hypothesses were teested by an asurement un ncertainty of tthe complex CMM-robott mea mea asuring syste em, comparin ng them wiith limits off allowed measurin ng uncertaintyy of CMM (hy ypotheses 1 & 2) an nd by varying g mass of meaasured object to t analyse thee mea asurement un ncertainty wh hen the masss is changed d (hyp pothesis 3). Other O influen nces, such ass geometricall erro or, deformatio on, thermal eerror, measurring strategy,, prob be movement speed duringg measuremen nt, measuring g dyn namics, workp piece propertiees, vibrations, temperaturee chan nge, etc., were e not considereed in this rese earch. 2.2 Objective O The primary obje ective of this research was to open new w posssibilities in this field and too encourage im mprovementss in the capabilities of CMM M machines in terms off shorrtening the prrocedure and reducing the measurementt cyclle duration. We W tried to p point out the possibility off com mbining differe ent structurall solutions on n modern and d preccise equipmen nt in order too achieve fastt, reliable and d preccise measurem ment, and thu hus improve technical t and d tech hnological cap pabilities in industry, pro oduction and d reseearch areas wh here CMMs arre commonly used. u 3. Ex xperiment desscription 3.1 Equipment E used d The coordinate measuring m macchine Zeiss Co ontura G2 7000 Aktiv with tactiile probing ssystem was used in thiss urement ran nge: 700x100 00x600 mm,, reseearch (measu mea asurement un ncertainty acccording to ISO 10360-2:: MPE E_E = (1.8+L/3 300 μm, MPE__P = 1.8 μm). a rotating oof the measured object wass The positioning and ually, inside the CMM’ss workspace,, perfformed manu whiich tended to take t a consideerably long tim me. In order to o shorrten this time, to reduce th he positioning g error and to o min nimize other errors, an ed ducational rob bot with fivee degrees of fre eedom was used: Rob bot RV-2AJ,, nufactured by Mitsubishi Ellectric–Melfa robots, Japan.. man The measuremen nt uncertainty of this robott is not stated d t manufactu urer; the onlyy comparable parameter iss by the repeeatability, sta ated to be ±00.04 mm. Th he robot is a statiionary roboticc system, with h programmed d motion path h and d automatic determination oof the target. Samir Lemes, Damir Strbac and Malik Cabaravdic: Using Industrial Robots to Manipulate the Measured Object in CMM 3 3.2 Conditionss 3.4 Positioning P All measurem p wiith the condittions ments were performed and capacitties availablee at the la aboratory at the University o of Zenica. The T tempera ature during the experiment was 21°C. The workp piece and C CMM measuring ellements were cleaned prior to measurem ment in order to reemove possiblle contaminan nts. There werre no were other machin nes in the viicinity of the CMM; nor w there any oth her vibration sources s (excep pt the CMM’ss and robot's own n vibrations). Prior to measurement, m the calibration off the measurin ng tools and measuring m sysstem was perform med using 25 mm ceramic reference sph heres manufactured by Zeiss, using u the calib bration proceedure defined by C CMM softwaree Calypso. The robot’s posittion compared d to CMM was w limited by y the robot’s arm-re each limit or it its workspace.. Accordingly,, the robot was possitioned and fiixed in an opttimal position.. n Thiss position wass defined by rrelative angullar rotation in the arm’s joint, and a the positi tion and orien ntation of thee ppers in the sp pace, ensuringg correct performance of thee grip giveen assignmentt. The robot w was attached to t the CMM’ss gran nite table usin ng Z-shaped p profile elements with firm m screew connections. ntrol of the robot r was seemiautomatic. The controll Con prog gram (direct programming p g) for piece po ositioning wass follo owed with manual m launch hing, starting the program m for each e single measuring m phaase. After the robot r trapped d the measured object with the pneumatic grripper, it wass n moved into a position enaabling measurrement with a then sing gle stylus sysstem, makingg all geometrical featuress easiily accessible by all touch h probes assembled in thee stylu us system. 3.5 Geometrical G feaatures Figure 2. Calib bration with ceramic reference sphere. s 3.3 Measured object The measureed object wass selected to have geomettrical features typ pically found in coordinatte measurem ments: planes, conees, and cyliinders. The material of the measured ob bject was no ot of great importance, i ssince temperature deviations were neglig gible (laboraatory m fo orce (200 mN)) did conditions), aand typical measurement not deform tthe object. Thee object was made m of PVC C and the surface w was metalized,, reducing surrface roughneess to a minimum. Fig. 3 shows the t four featurres measured. Ø 42,5 Ø 39,0 a b c 7 d 12 R1 5 Ø 43,0 4 Ø 60,0 Ø 72,0 Dim mensional me easurements were repeate ed a certain n num mber of time es on previiously described surfacess defiining differen nt workpiecce geometries. For each h partticular surface, the dimen nsions were measured 255 timees, under the same conditioons, in order to compensatee rand dom errors. The number off measuremen nts (the size off the sample) was determined d acccording to th he significancee the probability y of failing to o leveel of the test α = 0.01 and th deteect a shift of one standard d deviation β = 0.01 0 for a two-sideed test, assum ming normall distribution and known n stan ndard deviatio on [14]. The planar featurres were meassured by sets of 250 pointss distributed circularly, and conical features weree asured by me easuring two circles, each consisting off mea 250 points, at distances of 1 m m mm (cone "b") and 3 mm (con ne "c") from th he edges, in orrder to avoid filleted f edges.. The measuremen nt results weere used to estimate thee asurement unccertainty, as a measure of validity v of thee mea resu ults and confirrmation of hyp potheses 1 and d 2. ure was identical, but with h For hypothesis 3, the procedu o measured oobject. The firrst measuring g incrreased mass of cyclle was perforrmed on a C CMM with th he measuring g objeect fixed on th he CMM’s graanite table. Th he second and d third d cycles were e measured byy the complex x CMM-robott systtem. ow the planess and cones used u to definee Figss. 4 and 5 sho the dimensions to o be measured d. Figure 3. Meassured object witth defined geom metrical featuress (a - top plane o of cone, b - coniccal portion with h larger angle, c conical portion n with smaller angle a and d - top p plane of cylind der) 4 Int. j. adv. robot. syst., 2013, Vol. 10, 281:2013 www.intechopen.com Cone 1 Plane "a" Plane "d" Cone 2 Figure 4. Geom metric features measured m by CM MM. Figu ure 6. Robot arm m position 1. Figure 5. Meassured features in n CMM softwarre. The measureed dimensionss were defined d as follows: – – – – Diameteer d1 is the inteersection of plane ”a” and cone 1 Diameteer d2 is the inteersection of co one 1 and conee 2 Diameteer d3 is the inteersection of plane ”d” and cone 2 Height H is the distan nce between pllanes ”a” and ”d”. Figu ure 7. Robot arm m position 2. Sincce the measure ed object’s maass was consta ant during thee firstt two measurring cycles, th he mass of the t measured d objeect was increa ased by addin ng mass m = 600 6 g (Fig. 8).. The third measurring cycle wass conducted with w increased d ults were comp pared with th he first cycle. masss and the resu 4. Experimen nt In the first measuring cy ycle, the mea asured object was positioned an nd fixed to th he CMM’s measuring table,, and in the second d cycle the position p of the e measured oobject was defined by the robott’s arm positiion (i.e., auxiiliary ding the meassured elements in tthe robot’s arrm were hold object) insid de the CMM M’s coordinate e space. Betw ween me a every single measurementt in this measu uring cycle cam m fro om one positioon to phase of the robot’s arm movement back again. Coordinates of the robot’s arrm in another and b both positio ons were defined by the e robot’s offf-line programming in such a way that the robot could d be manually and that position memorized. A After positioned m ot’s operating this, the robo g speed was defined. d Sincee the robot repeateed this operattion for each measurementt, the robot’s repeaatability was ±0.04 mm. Figs. 6 and 7 sshow the first and tthe second rob bot arm positiions, respectiv vely. www.intechopen.com Figu ure 8. Measuring g object with ad dditional mass. 5. Measurement M results r Mea asurement results are shown n in Table 1. Samir Lemes, Damir Strbac and Malik Cabaravdic: Using Industrial Robots to Manipulate the Measured Object in CMM 5 Measure-men nt Measured vaalues (mm) No. Diameter Diameter Diameter d3 d1 d2 1. 39.0485 42.5430 42.9402 4 2. 39.0482 42.5432 42.9400 4 3. 39.0484 42.5430 42.9401 4 4. 39.0483 42.5431 42.9401 4 5. 39.0485 42.5433 42.9404 4 6. 39.0484 42.5432 42.9405 4 7. 39.0484 42.5434 42.9407 4 8. 39.0486 42.5436 42.9408 4 9. 39.0486 42.5436 42.9410 4 ... ... ... ... 23. 39.0481 42.5439 42.9405 4 24. 39.0481 42.5440 42.9404 4 25. 39.0487 42.5437 42.9409 4 Mean valu ue 39.0484 x1m 42.5436 42.9407 4 Standard 0.00026 0.00038 0.00043 0 deviation Max 39.0487 42.5444 42.9415 4 Min 39.0478 42.5430 42.9400 4 Absolute range E1 0.0010 0.0014 0.0015 Heigh ht H 18.80070 18.80065 18.80067 18.80068 18.80072 18.80070 18.80071 18.80072 18.80073 ... 18.80071 18.80081 18.80074 18.80074 5.2 Statistical S analy ysis 0.000050 18.80082 18.80065 The first step in statistical anaalysis was to question thee mality of disstribution of the measurement results.. norm Kurrtosis of all ressults was betw ween -1.40 and d 0.54, and thee skew w ranged betw ween -0.99 annd 0.72. For 25 5 samples, thee stan ndard error off the skew is 0.49 and stan ndard error off the kurtosis is 0.9 98; therefore, bboth skew and d kurtosis aree d error, and we w can assumee lower than twice the standard mal distributio on of measureed data. norm 0.00017 Table 1. Resullts of first measu uring cycle - me easuring object ffixed on CMM's meaasurement tablee 5.1 Measurem ment uncertaintyy The declared d measuremen nt uncertainty of the CMM u used in this experriment is 1.800 μm. In all th hree cases theere is Type A stand dard measurement uncertaiinty, which eq quals standard dev viation times coverage c facto or 2. The stan ndard measuremen nt uncertaintiees of three me easurement cy ycles are shown in n Table 2 and Fig. F 9. Measured value Diameter d1 Diameter d2 Diameter d3 Height H 6 e that all meaasurements in the first casee We can conclude n the CMM’ss exprressed lower uncertainty tthan stated on calib bration certifiicate. The meeasurement results r in thee seco ond case show w that measu urement uncerrtainty of thee systtem CMM-ro obot is signiificantly larg ger than thee decllared uncerta ainty of the C CMM. In the e third cycle,, wheere the CMM--robot system m was used to o measure thee objeect with increased m mass, the measurementt uncertainties are larger than th the declared uncertainty u off n those in the e second case.. the CMM, but still lower than Thiss means that increased maass of the me easured objectt sligh htly reduced uncertainty. T This phenome enon could bee expllained by the increased inerrtia of the measured object,, whiich stabilizes the system an nd leads to more m accuratee resu ults. o distribution ns for measured values off The histograms of diam meter d1 (Figss. 10 and 11) illustrate the normality off distribution. The distributionss of most oth her measured d ues have a sim milar shape. valu Standard d measurement uncertainty u (μm m) Case 1 Case 2 Case 3 only CMMCMM-robot C witth CMM robot added mass 0.53 12.33 3.86 0.76 12.98 4.69 0.86 10.92 3.95 1.00 9.72 4.17 Table 2. Stand dard measuremeent uncertainty in i three measurring C 2. measurring on CMM-roobot cycles: 1. meassuring only on CMM; system; 3. meaasuring on CMM M-robot, with ad dditional mass. Figu ure 10. Histogram of distributioon of diameter d1 (Casse 2: CMM-robot) with fitting nnormal distributtion.. Figure 9. Comp parison of meassurement uncertainties (μm). Figu ure 11. Histogram of distributioon of diameter d1 (Casse 3: CMM-robot + added mass)). Int. j. adv. robot. syst., 2013, Vol. 10, 281:2013 www.intechopen.com mea asurement for complex CMM MM-robot meassuring system m is within the limits of allowed un ncertainty off mea asurement of CMM”) C shoulld be rejected, since P-valuee for both one-tail and two-tail are significan ntly lower thee n critical value e of t-variable for sample size 25, α being g than eith her 0.05 or 0.01. D and d proposed furthher research 5.3 Discussion Figure 12. Boxplots of diameteer d1 reveal no outliers. o Kolmogorov--Smirnov tesst was used d to check the difference in n the means of o results obttained in the first (measuremen nts performeed on fixed measured oobject using only C CMM) and in the second measurement m ccycle (measuremen nt obtained by y the system robot-CMM).. The results for all four measured m geometrical vaalues own in Table 33. (diameters d1 to d3 and heiight H) are sho d1 Mean CMM only Mean CMM-robot Variance CMM only Variance CMM-robot D CMM only p-value CMM only D CMM-robo ot p-value CMM-robot t Stat P(T<=t) 1-tail t Critical 1-taiil P(T<=t) 2-tail t Critical 2-taiil d2 d3 Alth hough this exa ample shows that it is posssible to use an n indu ustrial robot to o extend the m manipulation capabilities off a co oordinate measuring machin ne, some impo ortant aspectss shou uld be consid dered. The exxperiment pe erformed had d som me disadvantag ges, which aree summarized d below. Disa advantages th hat could havve affected the accuracy off resu ults included: 1. H 39.0484 mm 39.0278 mm 6.97E-08 mm 3.80E-05 mm 0.166 42.5436 mm 42.5194 mm 1.46E-07 mm 4.21E-05 mm 0.107 42.9408 mm 42.9214 mm 1.86E-07 1 mm 2.98E-05 2 mm 0.091 18.88075 mm 18.88238 mm 2.48E E-07 mm 2.36E E-05 mm 00.129 0.458 0.920 0.980 00.771 0.109 0.116 0.201 00.151 0.912 0.871 0.235 00.585 2. 3. 16.7275 18.5872 17.6842 -16.77088 4.94E-15 4.69E-16 1.43E-15 1 2.24E E-15 2.4992 (α<0.01), 1.71 11 (α<0.05) 9.89E-15 9.38E-16 2.87E-15 2 4.48E E-15 2.7997 (α<0.01) , 2.06 64 (α<0.05) Table 3. The reesults of the staatistical Kolmogorov-Smirnov ttest (significance leevel p < 0.05) an nd t-Test: Two-S Sample Assumin ng Unequal Variaances (α<0.01, Hypothesized H Mean Difference 00). 4. As the comp puted p-value is greater tha an the significcance level 0.05, w we cannot rejeect the null hy ypothesis H0 (the sample follow ws a Normal distribution). d Levene’s tesst confirmed d that varian nces in the two observed casses are differen nt. Therefore the t Welch’s t--Test, Two-Sample Assuming Unequal Variances, was performed in n order to cheeck the differe ence in the m means of the resullts obtained in the first and the seccond measuremen nt cycles. of the t-Test, shown in Ta able 3, lead too the The results o conclusion that Hypo othesis 2 (“Uncertainty ( of www.intechopen.com 5. Conditions of university laaboratory Better equip pment, laborratory completeness and d application of highest m measuring sttandards can n he quality off provide bettter conditionss and thus th measuremen nt results. The bonding CMM and rob obot ation of the rrobot with th he CMM wass The combina achieved as described in n this paperr because off technical and d construction on capacity constraints. In n order to incre ease stability aand measurin ng precision off the robot, it is possible tto use different designs off e using compleex binding ele ements, which h bearing table can enable the CMM and roobot to bind ass a single unit.. Vibrations caused by thee robot’s insttability on itss bearing table (light consstruction, high h position off g robot’s graviity centre by z axis, wheels on bearing base, etc.). uction of bearin ng table and a Larger and heavier constru stronger link k to the groun und would po ossibly reducee vibrations du uring movemeent of movablle elements off the robot or CMM. C The con nfiguration wh here the robott was fixed to the t ground, w without a physiical connection n to the CMM M granite tablee, drastically increased thee system’s stabiility and reducced vibrations. Limited reach of the roboot’s arm due to t its position n relative to the CMM. M and robott By using a different deesign of CMM nt type of robo ot, it would bee binding, or even a differen possible to increase thee overlapping workspacee i thee zones of the robot and thee CMM, thus increasing h. robot’s reach Mechanical impacts on C CMM which occur whilee shifting posiition of meassuring probe in phase off measuring ne ew geometricaal feature (surrface). The design of the CM MM used can cause thee appearance of certain m mechanical im mpacts when n changing me easuring phasee. These impa acts can causee vibration inccrease in thee robot’s arm m, particularly y when at full stretch. s Samir Lemes, Damir Strbac and Malik Cabaravdic: Using Industrial Robots to Manipulate the Measured Object in CMM 7 Future research in this area should be performed with different configuration, with a more robust robot chassis, and with more positions examined. Another improvement would be to synchronize the software for CMM manipulation and the software for robot manipulation, providing real automation of the measurement process. – A deeper and more detailed measurement uncertainty analysis, using both Type A and Type B errors, and taking into consideration correlation of influence factors, should also be performed, in order to give a more general foundation for testing the complex measurement systems. 7. Acknowledgements 6. Conclusion The principal idea of this paper was to extend the possibilities for automating the measurement process with coordinate measuring machines. The obstacle most often encountered with CMM measurements are limitations of geometry, requiring more measurement sequences in order to reach difficult places on the measured object. It is possible to perform measurements of such objects, but manual repositioning of the measured object, including redefinition of the local coordinate system, slows down the process. If an industrial robot is used to manipulate the measured object, such a process could be automated. The ultimate goal is to keep the measurement uncertainty within allowable limits The measurements of the dimensions of the measured object were conducted by complex CMM-robot measuring system, with movements performed between each single measurement. These results were compared with the results obtained by measuring the same object fixed in the CMM. The measurement results in these two cases were different; one of the reasons for this could be the slight impacts and vibrations that were obvious during every movement phase between measurements. Although the obtained measurement results still have great accuracy and precision, they do not meet the criteria of the CMM’s prescribed measurement uncertainty. It can be concluded that it is possible to conduct measurements using complex CMM-robot measuring systems, but the measurement results are dictated by the measurement uncertainty of the least accurate component of the system, which in this case was the industrial robot. Significant differences and deviations in measurement results can be confirmed by comparing obtained measurement results with results measured on an object with a different mass. This confirms the significant influence of variation in the mass of the measured object on the measurement uncertainty of the complex CMMrobot measuring system. It can be argued that it could still be possible to confirm hypothesis 2, assuming the fulfilment of certain conditions such as: 8 Int. j. adv. robot. syst., 2013, Vol. 10, 281:2013 – Different design of CMM and robot combination, which would reduce impacts and vibrations occurring in CMM operation; Use of newer and more advanced generations of robots with greater capacity, stiffness, accuracy, repeatability, etc. This research was supported in part by the Ministry for Education and Science of the Federation of Bosnia and Herzegovina. 8. References [1] J. Santolaria, J.J. Aguilar, Kinematic Calibration of Articulated Arm Coordinate Measuring Machines and Robot Arms Using Passive and Active SelfCentering Probes and Multipose Optimization Algorithm Based in Point and Length Constrains, Robot Manipulators New Achievements, A. Lazinica and H. Kawai (Ed.), ISBN: 978-953-307-090-2, InTech, 2010 [2] B. 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