International Conference on Global Trends in Engineering, Technology and Management (ICGTETM-2016)

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1 Taguchi and ANOVA Analysis of Dburring Procss Paramtrs of PP Mat Prajitsn G. Daml *, Dr. Vijaykumar P. Wani 2, Dr. Indrasingh D. Patil 3. Rsarch Scholar, North Maharashtra Univrsity, Jalgaon (MS) 2. Principal, MET s Institut of Enginring, Nasik. (MS) 3. Profssor and HOD, Dpt. of Biotchnology, SSBT s C.O.E.T., Jalgaon (MS) Abstract Th ffcts of control factors (paramtrs) wr dtrmind by xprimntal study by using Taguchi Fractional factorial dsign of dburring procss of Mat manufacturing procss. Th optimum procss paramtrs wr dtrmind basd on thir influnc on th output of womn workrs. This study involvs six factors viz. BMI, Poplital, Buttockkn lngth, Sat bas, Sat back rst and Room tmpratur wr invstigatd in this study. Th rspons/dpndnt variabl is workrs fficincy in trms of output. Taguchi s tchniqu was usd for xprimntation. Taguchi L27 orthogonal array (OA) was applid to valuat th ffct of thss paramtrs and signaltonois data usd for comput th importanc and thir ffct on th rspons paramtr. Th analysis of varianc (ANOVA) has bn usd to valuat a most favorabl rsult of th paramtrs. Th rsults showd that th sat bas was th most significant paramtr followd by BMI and th last influnc was room tmpratur in wintr sason. Exprimntal rsults ar providd to confirm th ffctivnss of this approach. Kywords: Ergonomic, Productivity, Taguchi mthod, orthogonal Array, SN ratio, ANOVA I. INTRODUCTION Ergonomics is concrnd with making th workplac mor fficint, comfortabl and saf. Effctiv application of rgonomic in work systm dsign can achiv a balanc btwn workr and task dmands. This can improv workrs fficincy, as wll as comfort and job satisfaction. Many rsarch studis hav shown positiv ffcts of applying rgonomic principls in a workplac dsign, machin dsign and tool dsign [3]. In small scal industris th workstations ar dsignd in a random mannr. Thy ar giving littl important to th workstation dsign and workrs lif [3]. Th physical dimnsions in th dsign of an industrial workstation ar of major imprtinnc from th point of viw of production fficincy and oprators physical and mntal comfort. Small changs in workstation can hav a considrabl impact on workr productivity and as wll as industrial halth and safty. Insufficint postur from an important dsignd workstation caus a static muscl fforts. It is dirctly ffct on prformanc and productivity. Th Taguchi tchniqu is powrful, suprior xprimntal dsign tool. It is simpl, fficint and systmatic approach to optimiz dsigns for prformanc, quality and cost. Taguchi approach to dsign of xprimnt in asy to adopt and apply for usrs with limitd knowldg of statistics [4]. In addition, through incurring minimum xprimntal coast, this approach improvd th quality charactristics rapidly and fficintly by rducing th ffct of sourc of variation. In th rapidly changing situation human is th most important and valuabl rsourc to play vry important rol in vry organization. A many studis hav bn carrid out from tim to tim to xamin th changs in th productivity. Studis hav also bn carrid out to analyz productivity tndncis in major manufacturing industris [5]. Whn any on work in sitting on a hard surfac without back rst or lumbr support, th ischial tubrosity (infrior protubrancs of th plvic bons) is activ, around which th plvic strap rotats du to wight of uppr body. This is th main rason to dvlop musculoskltal disordrs (MSDs) in womn workrs in th industry. It has bn rportd in rgonomics that squatting postur is vry tirsom [67]. Ergonomics studis in industrial workrs ar many, but th spcific study on th womn working has not bn carrid so far. In th prsnt study, Taguchi mthod of xprimntal dsign was applid to stablish rlationships btwn BMI, Poplital, Buttockkn lngth, Sat bas, Sat back rst, room tmpratur and workrs output. In this proposd mthod, statistical approach basd on Taguchi and Analysis of varianc (ANOVA) tchniqu had bn adoptd for obtaining th influnc of ach paramtrs. II. OBJECTIVES OF THE STUDY Th primary objctiv of this rsarch is to tak th collction of xisting situations of working mthod and to assss th industrial productivity in th changing industrial condition of th industrial units of Jalgaon MIDC, India. Whr th task of dburring (finishing) is prformd in a sitting position on hard floor with folding lgs at kn, in which workr is cutting th xtra lngths tubs with Blads. It is rptitiv and continuous for 8 hours (xcpt lunch brak) in working priod. In this condition, back and nck is bnd xcssivly and ISSN: Pag 57

2 posturs of diffrnt parts of body considrably dviat from nutral. Th spcific objctivs of th study wr:. To work out productivity of womn workrs on nw workstation. 2. To find out optimum combination of control variabl for maximum production. III. METHODOLOGY A. Taguchi Mthod Taguchi s dsign mthod is a powrful tool for optimization of th prformanc charactristic of a procss. Th aim of a Taguchi dsign xprimnt is to idntify and dsign th sttings of th procss paramtrs at optimiz lvl in thir rspctiv rang and ar last snsitiv to nois factors. Slction of control factors and thir lvls ar mad on th basis of som prliminary trial xprimnts conductd on th basis of singl variabl at a tim and also from litratur rviw. Th xprimnts wr basd on th basis of orthogonal array tchniqu. Using orthogonal array dsign th ffcts of multipl variabls on th prformanc charactristic can b stimatd simultanously whil minimizing th numbr of tst runs. Taguchi s approach has bn built on traditional concpt of DOE, such as full factorial, fractional dsign and orthogonal arrays basd on signal to nois ratio, robust dsign and paramtr and tolranc dsign. It is a powrful tool for dsigning high quality systms and provids a simpl, fficint and systmatic approach for optimizing th dsigns for prformanc, quality and cost. This mthod can rduc rsarch and dvlopmnt costs by studying a larg numbr of paramtrs. Taguchi suggstd a standard procdur for optimizing any procss paramtrs. Th stps involvd ar: Idntification of th nois factors and tst co nditions Idntification of th control factors and thir altrnativ lvls. Dsigning th xprimnt and dfining th d ata analysis procdur. Conducting th xprimnt. Analyzing th data and dtrmining th opti mum lvls of control factors. Prdicting th prformanc at ths lvls. In ordr to analyz th rsults, th Taguchi mthod uss a statistical masur of prformanc calld signal to nois ratio (SN ratio). Th SN ratio taks th man and th variability into account. Th SN quation dpnds on th critria for th quality charactristic to b optimizd. Aftr prforming th statistical analysis of SN ratio, ANOVA can b mployd in stimation of rror varianc and to judg th rlativ importanc of th control factors. This allows collction of ncssary data for dtrmining factors that ar mostly affcting th product quality with a minimum amount of xprimntation and thus saving tim and rsourcs [8]. a. Analysis of SignaltoNois (SN) ratio : In Taguchi mthod, th trm signal rprsnts th dsirabl valu (man) for th rspons and th trm nois rprsnts th undsirabl valu for th rspons. Taguchi uss SN ratio to masur th quality charactristic dviating from th dsird valu. Thr ar svral SN ratios availabl dpnding on th typ of charactristics i.. Smallrthbttr, Nominalthbttr and Highrthbttr. Th formula usd for calculating S/N ratio is givn blow. Smallr th bttr: it is usd whr th smallr valu is dsird. whr y = obsrvd rspons valu and n = numbr of rptitions. Nominal th bttr: it is usd whr th nominal and variation about that valu is minimum. whr µ = man and s = varianc. Highr th bttr: it is usd whr th largr valu is dsird. whr y = obsrvd rspons valu and n = numbr of rptitions Th SN ratio is dfind as, SN = 0 log (M.S.D.) whr M.S.D. is th mansquar dviation for th rspons charactristic.[9] B. Slction of Orthogonal Array: Tchniqus of arranging xprimnts undr multipl factors ar known as th Factorial DOE. This mthod hlps th rsarchrs in dtrmination of th possibl combinations of factors and th idntification of th bst combination and thir lvls. Howvr in industrial location it is vry costly procss to run larg numbr of xprimnts in tsting all combinations. Th Taguchi approach dscrib th plans in carrying out xprimnts and also standardizd th dsign of th xprimnt along with minimum numbr of factor combinations that would b rquird for tsting th influnc of factors [0]. C. Analysis of varianc (ANOVA) Th knowldg of th contribution of individual factors is a ky to dciding th natur of th control to b stablishd on a production procss. Th analysis of varianc (ANOVA) is th statistical action most commonly applid to th rsults of th ISSN: Pag 58

3 xprimnt to dtrmin th prcnt contribution of ach factor. Study of th ANOVA tabl for a givn analysis hlps to dtrmin which of th factors nd control and which do not. Onc th optimum condition is dtrmind, it is usually a good practic to run a confirmation xprimnt. It is, howvr, possibl to stimat prformanc at th optimum condition from th rsults of xprimnts conductd at a nonoptimum condition. It should b notd that th optimum condition may not ncssarily b among th many xprimnts alrady carrid out, as th OA rprsnts only a small fraction of all th possibilitis. Taguchi suggsts two diffrnt mthods to carry out th complt analysis. First, th standard approach is, whr th rsults of a singl run or th avrag of rptitiv runs is procssd for ANOVA analysis. Th scond approach, which h strongly rcommnds for multipl runs, is to us signal to nois ratio SN for th sam stps in th analysis. SN analysis dtrmins th most robust st of oprating conditions from variations within th rsults []. IV. EXPERIMENTAL STUDY A prliminary survy was conductd to idntify problms in mat manufacturing industris through qustionnair and intrviwing of 20 workrs. It was found that, du to awkward sitting postur many of th workrs had a problm of Musculoskltal disordr (MSD). It has bn rportd that, du to sitting on hard surfac without back lumbr support womn workr has many halth issu i.. Low back disordrs (LBD) [2]. It affct on thir working fficincy dirctly. For incrasing th working fficincy as wll as thir working position comfortabl, rsarchr applid th Taguchi optimization tchniqu and masurs th fficincy of workr in th form of output. This study was conductd in actual fild of work in th slctd industry. Exprimntations wr don in thr sasons to s th ffct of nvironmntal factors with othr six control factors. Th opration was prformd on fixd tabl and adjustabl chair. Th objctiv of th xprimnt is to find out optimiz th paramtrs of workstation in ordr to improv th fficincy of workr. In this study, an xprimntal mthod is proposd to fully undrstand ffcts of various paramtrs on fficincy of workrs. For this xprimntation, 95 womn workrs ar participatd. On adjustabl xprimntal workstation, th workr prformd thir normal dburring task in 27 xprimntal sssions of 45 min. Th st of xprimnt is th prsnt working conditions. Rsarchr considrs six paramtrs with thr lvls as indicatd in tabl for wintr sason bas on on variabl at a tim mthod. Onc th xprimntal dsign has bn dtrmind and th trials hav bn carrid out, th masurd rspons from ach trial can b usd to analyz th rlativ ffct of th diffrnt paramtrs. To dmonstrat th data analysis procdur, th L27 array is usd and xprimnt is rpatd thr tims. Man of rspons is considrd for SN ration calculation. Tabl Paramtrs and thir rang & lvls (for wintr sason) Sr. No. Symb ol Wi Paramt rs 2 L Buttock kn B: lngth Rang A: BMI L 2 Poplital C: 4 H bas D: Sat 5 H 2 E: Backrst middl from sat bas 6 R t tmpratu G: Room r l l l l V. RESULTS AND DISCUSSION A. Taguchi Mthod Th rsults of this rsarch ar basd on th cas study conductd on th production lin of th PP Mat manufacturing industry. On of th hypothsis is th fficincy of workr has a dirct rlation with stting position and BMI, buttockkn lngth, poplital, sat bas, back rst and room tmpratur. SN ratios ar calculatd for ach factor and lvl; thy ar tabulatd as shown blow in tabl 2. Taguchi rcommnds analyzing th man and SN ratio using a concptual approach that involvs graphing th ffct and visually idntifying th factor that appar to b important, without using ANOVA. Th SN ration graphs ar shown in figur no.. Tabl 2 Rspons Tabl for S/N Ratios for wintr sason (Largr is bttr) l A B C D E F Dlta Rank ISSN: Pag 59

4 Sour c D F Adj SS A Adj MS 72. F Valu 5.48 B C D P Valu contributi on E F Error Total From th rspons graph it can b sn that factor D has largr ffct on th prformanc. Factor F has a rlativly small ffct. Sinc a rspons variabl is th maximum output, this implis that th quality charactristics typ is a Largrthbttr. Th diffrnc btwn th highst and th lowst valus rprsnt th significanc of a factor; a ranking is don on all th factors. From rspons tabl 2, th highst valu of ach SN ratio for ach factor can b idntifid clarly as wll as most dominating factor is idntifid. Th highst valu of ach SN ratio for ach factor is usd to form optimum combination of lvl of ach factor. Th largr th dltas (Δ) valu for a paramtr, th largr th ffct th variabl has on th procss. This implis that factors D, A, and C ar mor important than th rst of th factors. This is bcaus th sam chang in signal causs a largr ffct on th output variabl bing masurd. B. Analysis of Varianc Effct of individual paramtrs on ntir procss and thir prcntag contribution of individual paramtrs can b wll dtrmind using ANOVA. MATHEMATICA softwar of ANOVA modul was mployd to invstigat ffct of procss paramtrs. Th frquncy tst (Ftst) is utilizd in statistics to analyz th significant ffcts of th paramtrs, which form th quality charactristics. Tabl 3 shows th rsult of ANOVA analysis of SN ratio for productivity. This analysis was carrid out for a lvl of significanc of 95% confidnc. Th last column of th tabl shows th contribution of ach factor in prcnt as th total variation, indicating its influnc on th rsult. Figur Main Effct Plot btwn SN ratios of ach paramtrs and lvl (for wintr sason) From th tabl 3 it is clar that, th Pvalu (0.006) of sat bas is significantly contributing towards productivity. ANOVA rsults closly match with Taguchi rsult. Tabl 3 on way analysis of varianc Figur 2 shows th contribution of ach paramtr on th productivity in prcntag. It is dmonstratd that sat bas has th most significant ffct on th output rspons i.. productivity. Othr significant paramtrs ar BMI and Poplital. 37% contribution 2% % 8% 36% 6% Figur 2 rlativ ffct of ach paramtr on productivity (%) C. Vrification Tst By statistical analysis, optimum lvl of paramtrs ar; A3 B2 C3 D2 E2 F. Most influncing paramtr is sat bas, which givs most significant ffct to productivity. VI. CONCLUSIONS In this study, th Taguchi mthod provids a systmatic and fficint mthodology for th dsign and optimization of control paramtrs. Th data analysis was prformd by Taguchi mthod in MINITAB statistical softwar, th optimum rlationship btwn paramtrs and lvls ar obtaind. Th optimum lvl of paramtr has bn obtaind with rspctiv th xprimntal priod i.. A3 B2 C3 D2 E2 F for wintr priod. Th rsult might vary for tst carrid out in diffrnt industry. ANOVA rsults closly match with Taguchi rsult. REFERENCES. M. Shaliza, K. Shahrul, M. Mohzani, O. Zalinda and S. Khairanum, 2006 Application of Quality Function Dploy mnt in Idntifying Ergonomics Programs for Malaysian, Th Effct of Ergonomics Applications in Work Systm on Mntal Halth of Visual Display Trminal Workrs Manufacturing Industris, Procdings in Intrnational Confrnc on Tchnology Managmnt, 45 Dcmbr 2006, A B C D E F ISSN: Pag 60

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