Intelligent Assembly/Disassembly System with a Haptic Device for Aircraft Parts Maintenance

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1 Intelligent Assemly/Disssemly System with Hptic Device for Aircrft Prts Mintennce Christind nd Jungwon Yoon Mechnicl nd Aerospce Engineering nd ReCAPT, GyeongSng Ntionl University, Jinju, Gyeongnm , Kore Astrct. This pper presents the development of n intelligent Assemly/Disssemly (A/D) system with the utiliztion of hptic device. The development ws imed to ssist the A/D process of ircrft prts mintennce with n intelligent lgorithm. A comprehensive methodology is presented y n intelligent lgorithm generting the est sequence for the ssemled/disssemled prts. For this purpose, genetic lgorithm ws chosen ecuse of its effectiveness nd comptiility deling with the A/D sequencing prolem. Furthermore, A/D process of the prts will lso e clculted in the genetic lgorithm process, which will show the effectiveness of the lgorithm. Moreover, the concept of oth nturl nd rtificil constrints re pplied to generte the pth plnning of the ssemled/disssemled prts. It is elieved tht the comintion of hptic, optimized sequence lgorithm nd intelligent pth plnning will increse efficiency for the overll ircrft prts mintennce process. Keywords: Hptic, Genetic Algorithm, Nturl nd Artificil Constrint, Aircrft Prt Mintennce. 1 Introduction The implementtion of Virtul Relity (VR) technologies such s the medicl nd A/D fields, is incresing. The improvement of VR technologies promises right future for the efficiency of the A/D process, including the mintennce of ircrft prts. Since the physicl ojects re represented in digitl form with VR technologies, users do not need to hve rel oject for the simultion of the process. From tht point of view, the efficiency cn e incresed ecuse of the elimintion of rel oject. Furthermore, the development of VR technologies is lso supported y the development of hptic technologies. Nowdys, some hptic devices re ville nd widely used such s Phntom fmilies [1] from SenseAle TM Corportion nd Omeg x TM from the Force Dimension Corportion. Hptic devices give touch sensing y force-feedck mechnism. Through this mechnism, n opertor will feel the result of collision force. Corresponding uthors. Y. Shi et l. (Eds.): ICCS 2007, Prt II, LNCS 4488, pp , Springer-Verlg Berlin Heidelerg 2007

2 Intelligent Assemly/Disssemly System with Hptic Device 761 The mintennce process itself enefits from dvncements in the VR interfce, since the mintennce process involves mny A/D tsk nd depending on the mount of prts involved. A mintennce simultion could e held to oserve the scheme of mintennce tsk y simulting the process in virtul environment (VE). Borro et l. hve developed the system for the mintinility simultion in eronutics. They comined hptic device to the system nd keep the user s movements sme s those tht occur when testing physicl mock-up [2]. Similr work hs lso een suggested y Svl et l. [3]. Another reserch focused on the development lnguge, such s Virtul Fixture Assemly Lnguge (VFAL) [4]. This lirry could e used to construct vrious virtul fixture series with grphic nd force guidnce rules, mking the low-level hptic nd grphic rendering detils trnsprent to the developers. Gllntuci et. l hve reserched the A/D plnning y using fuzzy nd genetic lgorithms [5]. They utilized genetic lgorithm (GAs) to generte the optiml sequence for A/D tsk. Our reserch focuses on the development of A/D system for the ircrft prt mintennce process. We propose comintion of the utiliztion of hptic device nd n intelligent lgorithm for prt sequence genertion. We utilized genetic lgorithm s n optimiztion method to optimize prt sequence genertion. Even though some reserches lredy hve een suggested this for the prts sequence genertion, they didn t consider the utiliztion of hptic device. Nturl nd rtificil constrint concepts re pplied in this pper. Nturl nd rtificil constrint concepts hve een widely pplied in the rootics field. Even though there hs een extensive reserch [6-7] on the constrints in the hptics field, there hs not een detiled study on its pplicility to ircrft prt mintennce. This pper descries the development of the intelligent system for the ircrft prts mintennce with hptic informtion. 2 Description of Aircrft Prt Mintennce System The schemtic of A/D system is shown in Figure 1. The system consists of hptic device (Phntom omni), Virtul Environment (VE), nd trined opertor. The hptic device cn e considered s n pprtus where n opertor inputs the ction for the mnipulted oject. This device hs only three degree of freedom (3-DOF), so it cn not generte torque. The communiction occurred i-directionlly etween the hptic device nd the VE through fire-wire cle. The mnipulted ojects re ircrft prts with scle model, which ws mde in CAD softwre nd sved s the VRML (Virtul Relity Mchine Lnguge) file formt. After the oject ws trnsferred to VE, the opertor could then mnipulte the oject during the scheme of the mintennce tsk. In the future trils ccording to the design, the movement mde y the opertor will e constrined long to the suggested pth. As the opertor looks t VE, he/she will feel the guidnce force from rtificil nd nturl constrints. The rtificil nd nturl constrints will guide the opertor to put the prt in the right position, using the suggested pth. The virtul environment ws uilt sed on the OpenInventor TM grphic lirry, collision detection lirry, pth plnning lgorithm, nd n optiml sequence genertion lgorithm. Those components work together to mke the ircrft prt mintennce system efficient.

3 762 Christind nd J. Yoon () Schemtic of A/D System () An opertor Fig. 1. An intelligent A/D system for ircrft prts mintennce 3 Aircrft Mintennce System Algorithm The overll system lgorithm is shown in the flowchrt in Fig. 2. First of ll, the system should check the hptic device through the device initiliztion, verify the initil position of hptic stylus, nd then confirm whether collision detection is eing performed or not. This step ws imed to decide which prt will e the first position in the sequence. This procedure gives freedom to the opertor to set the first suitle prt s he/she wish. Since the collision detection lirry only retrieves the coordintes of the colliding polygons nd points, the contct configurtion needs to e reconstructed y considering the possile comintion of surfce fetures etween two odies [6]. For collision detection, the functions from grphic API (Appliction Progrmming Interfce) Open Inventor re utilized [8]. After the first prt of the lgorithm is recognized, we cn perform the optiml sequence genertion. The genetic lgorithm (GAs) is pplied in this step. The GAs lgorithm egins y defining the optimiztion vriles, the cost function, nd the cost [9]. The cost function is function tht shows the reltion etween the optimiztion vrile nd the prmeter for evlution of the prolem solution. The cost is difference etween the ctul solution nd the desired solution. Optimiztion vriles re the vriles tht should e optimized to rech optiml solution for the cse model. The optimiztion vriles re rrnged in chromosome form. A cluster of chromosome is clled s popultion. The optimiztion vriles re sequence order (S), direction of ech prt (O), nd used tool for ech prt (T). where : [ S O T ] chromosome = (1)

4 Intelligent Assemly/Disssemly System with Hptic Device 763 S = ( s s s ) = prt sequence 1 O = ( o o o ) = T = ( t t t ) = used tool for ech prt 1 1 n n = numer of s s s n n prt prt orienttion The evlution of disssemly sequence ws relized y using cost function [5]: Cost function = f chromosome) = ( w l) + w ( N 1 o) + w ( N g 1) (2) ( where the prmeters of the cost function were set to l, o, nd g tht vriles re the mximum length of fesile sequence, the orienttion chnge numer, the gripper chnge numer, respectively. Then, every prmeter ws ssocited with the weight w. Fig. 2. System lgorithm of the intelligent A/D system The use of these cost function prmeters re quite representtive for the cse such s the mintennce tsk. In the mintennce tsk, the numers of orienttion chnges nd tool chnges will ffect the efficiency of overll mintennce process. An nlogy cn e mde to descrie the effect of the cost function prmeters for the overll efficiency. A gripper is tool used to do one tsk of the A/D tsks, wheres the orienttion chnges represent how mny step we needed for doing one tsk in A/D tsk list. It needs to e restted in this cse, tht the est sequence is list of prts in the ssemled order which hve the highest cost function vlue. The rnking for chromosomes will e generted in every genertion (itertion). Rnking is mde y sorting the cost vlue for ech chromosome. Some portion of popultion will e destroyed to give spce for new offspring. This process is clled

5 764 Christind nd J. Yoon nturl selection. Selection rte (X rte ) determines the mount of chromosomes tht still exists fter the nturl selection process. The selection rte is set to 50%. The reltion etween the existing chromosomes (P keep ) nd the numer of popultion (P) is shown in (3). Pkeep = X rte P (3) Then, the numers of the empty spce or the disppering chromosomes re shown in (4). Pdispper = P P keep (4) Hlf of the popultion will dispper nd will e replced y new offspring. The disppered chromosomes (P dispper ) re chromosomes tht hve low cost vlues. In ech genertion, GAs opertor: crossover nd muttion re pplied to produce new offspring. By pplying the GAs opertor, the fitness of the chromosomes cn e incresed. Crossover is process mtching of some nodes in one chromosome to nother chromosome. The results of the crossover process re two new offspring. In this pper, the crossover process is sed on prtilly mtched crossover (PMX) tht ws introduced y Lzzerini et.l with more dvncement clled MPMX [10]. Prents re tken from the existing chromosome (P keep ). The pir of prents re rndomly selected from the existing chromosomes (P keep ). Then, three numers re rndomly selected. Let,, nd l represent the strting nodes for the first nd the second chromosomes, nd the length of the mtching portion, respectively. For exmple: the chromosomes re S A nd S B, l = 4, = 3, = 7, n = 10. S S C C A B [ s4 s5 s8 s1 s9 s2 s6 s10 s7 s3 o4 o5 o8 o1 o9 o2 o6 o10 o7 o3 t4 t5 t8 t1 t9 t2 t6 t10 t7 t3] [ s7 s3 s2 s8 s5 s6 s9 s1 s4 s10 o7 o3 o2 o8 o5 o6 o9 o1 o4 o10 t7 t3 t2 t8 t5 t6 t9 t1 t4 t10 ] After the crossover A B [ s2 s5 s9 s1 s4 s10 s6 s8 s7 s3 o2 o5o9 o1 o4 o10 o6 o8 o7 o3 t2 t5 t9 t1 t4 t10 t6 t8 t7 t3] [ s7 s3 s4 s10 s5 s6 s8 s1 s9 s2 o7 o3 o4 o10 o5 o6 o8 o1 o9 o2 t7 t3 t4 t10 t5 t6 t8 t1 t9 t2 ] Then, the offspring (C A nd C B ) will fill the empty spce in the popultion, replcing the disppering chromosome (P dispper ). A muttion opertor is necessry to increse possiilities for getting etter offspring. Muttion is held y modifying the chromosomes individully. The nodes re selected rndomly. If genertion hs reched the cost function threshold, the genertion should e stopped. The most optiml sequence for A/D tsk will e suggested to the opertor. It is worth remrking tht the optiml sequence is conducted sed on the first prt recognition lgorithm chosen y the opertor. When provided with sufficient informtion, the system will generte the guidnce pth for the opertor, which will guide the opertor for the est prt sequence of the mintennce tsk. In order to sense the guidnce force, rtificil nd nturl constrints re pplied to the opertor through the pth. The fundmentl ide of using the force field is tht ech oject in virtul environment is surrounded y repulsive force field [7]. Since we lredy know the trget position of our prt position, the

6 Intelligent Assemly/Disssemly System with Hptic Device 765 force field of whole environment cn e clculted to ssist the opertor to rech the trget position. We cn prescrie the trget position for ircrft prts. During the ssemly tsk, trget position will e the est position for ech prt in Crtesin coordinte relted to the geometry constrint of the ssemled prts. In disssemly tsk, trget position is sfe plce (position) in Crtesin coordinte where we will put the prt for the finl position. The force pplied for the guidnce is summtion etween the rtificil nd nturl constrint. The following reltion summrizes the force implementtion [6] : Constrint totl (x,y,z) = Constrint nturl (y) + Constrint rtificil (x,z) (5) The constrint long the plne x nd z is used to guide the oject to rech the prescried trget position, wheres the nturl constrint is the constrint tht nturlly comes from the oject. After one prt hs reched the trget position, nother guidnce pth for nother prt will e suggested to the opertor. This process repeted until ll prt reches their trget positions. The sequence of tsk sed on the results of the optiml sequence genertion. 4 Experiment nd Result To implement optiml sequence genertion, some experiments were conducted to test the lgorithm. As shown in Fig. 3, An opertor ttempted to disssemle the ssemled prt. To ccomplish the disssemly tsk, prmeters such s gripper nd direction of prt were involved in cost vlue clcultion. While in [5] the numer of fesile sequence ws involved, this tril did not involve tht prmeter in this experiment. Assume the possiility of escpe prt direction only limited to the +z nd z direction. The gripper ws ville in five types. Tle 1. Aville Gripper Prt Aville Gripper 1 G 1,G 2,G 3 2 G 2,G 3,G 4 3 G 1,G 3,G 4 4 G 3,G 4,G 5 5 G 3,G 4 6 G 5 7 G 1,G 2,G 3 8 G 2,G 3,G 4,G 5 9 G 1,G 2,G 3,G 4 10 G 5 Initil popultion consisted of 100 individuls. The numer of genertion ws limited to 50 genertion. In every genertion, mximum nd verge cost vlue ws clculted. Below re the mximl cost vlue fter 100 tril ttempting. In every genertion, mximum nd verge cost vlue ws incresed (Fig. 3) This indicte tht

7 766 Christind nd J. Yoon solution is getting etter from genertion to genertion. The finl solution suggested for disssemly sequence re Becuse the cost function did not involve numer of fesile su-sequence nd fesile su-sequence modules, so there is non-fesile su-sequence in suggested solution. () Mximum cost function () Assemled prt for experiment (c) Averge cost function (d) Assemled prt drwing for experiment Fig. 3. Experiment result nd picture of ssemled prt 5 Conclusion In this pper, we hve suggested the frmework of the intelligent ssemly/disssemly system for ircrft prts mintennce tsk. The lgorithm nd components of the system which del with the complexity of the sequence selection y n optimlized method hve een descried in this pper. Some results hve een showed refer to the selection of optiml sequence. In future works, su-sequence module will e involved in the clcultion of cost vlue to void non fesile susequence pper in sequence solution. Furthermore, novel lgorithm nd strtegy in the hptic utiliztion hs een developed.. In other words, this system could e prototype of n efficient system for the purpose of ircrft prt mintennce tsks. Since this is n ongoing reserch, further developments nd inputs re desired to increse the effectiveness of the system.

8 Intelligent Assemly/Disssemly System with Hptic Device 767 Acknowledgement This work ws supported y the Kore Reserch Foundtion Grnt funded y the Koren Government (MOEHRD) (KRF J09902) nd ws supported y NURI Project. References [1] 4:23 pm. 26/12/2006 [2] Diego Borro, Jon Svll, Aiert Amundrin, Jorge Jun Gil, Alejndro Grci-Alonso, Luis Mtey, A Lrge Hptic Device for Aircrft Engine Mintinility, IEEE Computer Grphics nd Applictions, vol. 24, no. 6, pp , Nov/Dec [3] Jon Svll, Diego Borro, Jorge Jun Gil, Luis Mtey, Description of Hptic System for Virtul Mintinility in Aeronutics, IEEE Interntionl Conference on Intelligent Roots nd Systems, Lussne, Switzerlnd, Octoer [4] Alex B. Kung, Shhrm Pyndeh, Bin Zheng, Frnk Henigmn, Christine L. McKenzie, "Assemling Virtul Fixtures for Guidnce in Trining Environments," hptics, pp , 12th Interntionl Symposium on Hptic Interfces for Virtul Environment nd Teleopertor Systems (HAPTICS'04), [5] L. M. Glntucci; G. Percoco & R. Spin, Assemly nd Disssemly Plnning y using Fuzzy Logic & Genetic Algorithms, Interntionl Journl of Advnced Rootic Systems, volume 1 Numer, 2004 [6] Dniel Gleno nd Shhrm Pyndeh, Artificil nd Nturl Force Constrints in Hptic-ided Pth Plnning, IEEE Interntionl Workshop on Hptic Audio Visul Environments nd their Applictions, Ottw, Cnd, 1-2 Octoer 2005 [7] Dongo Xio nd Roger Huold. Nvigtion Guided y Artificil Force Fields, Proceedings of ACM CHI 98 Conference on Humn Fctors in Computing Systems, vol. 1, pp ACM SIGCHI, Addison Wesley, April 1998 [8] Open Inventor 6, Mercury Computer System, 2006 [9] Rndy L. Hupt nd Sue Ellen Hupt, Prcticl Genetic Algorithms 2nd Edition, John Willey nd Sons, USA, 2004 [10] Lzzerini B., Mrcelloni F., A Genetic Algorithm for generting Optiml Assemly Plns, Artificil Intelligence in Engineering, Vol. 14, pp , 2000