Analyzing Product Attributes using Logical Framework of Quality Function Deployment (Phase I): Concept and Application

Transcription

1 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr Analyzing Product Attributs using Logical Framwork Quality Function Dploymnt (Phas I): Concpt and Application Dvndra Singh Vrma Dpartmnt mchanical Enginring Institut Enginring & Tchnology Dvi Ahiya Univrsity, Indor Dr. Ashsh Tiwari Dpartmnt mchanical Enginring Institut Enginring & Tchnology Dvi Ahiya Univrsity, Indor Abstract Quality function dploymnt (QFD) is a customrdrivn quality managmnt, product and srvic dvlopmnt systm for achiving highr customr satisfaction. This papr suggst a six stp modl for Hous Quality (HOQ), th first and most important phas QFD, th outcom which is prioritizd Voic rs (VOCs) that can b calculatd with th hlp Rlativ importanc customrs, r comptitiv analysis and Improvmnt Ratios. In th proposd modl, a 9 point scal is usd to masur th voic customrs (VOCs) and thir rlativ importanc. Th customr comptitiv analysis is conductd and th probabilitis ach VOC for all th comptitors ar considrd to assss th standing ach comptitor vis-à-vis individual VOC. Normalization VOCs has bn don using mathmatical formula. A thorough xplanation is givn to undrstand th concpt and applicability th modl to a Sauc manufacturing company. Without loss gnrality th proposd modl can b usd to gt th prioritizd VOCs for any product. 1. Introduction Dynamic businss nvironmnt mphasizs th nd to undrstand diffrnt dcisions and practics for a firm to improv its comptitiv position. In viw divrs and dynamically changing scnario, customrs xpctations hav bcom mor important for th companis. In this papr an attmpt has bn mad to dvlop a modl for planning matrix th HOQ. This papr also prsnts a systmatic approach to th QFD procss. An illustrativ study and analysis has bn carrid out to xplain th application th proposd modl. Chan[1] (2004) has proposd a systmatic approach to Quality Function Dploymnt. A firm has to continuously follow th customrs xpctations and try to mak th changs in th product to provid maximum customr satisfaction. Quality Function Dploymnt (QFD) has gaind xtnsiv support for product planning and dvlopmnt dcisions. 2. QFD STEPS and OVRVIEW Akao, Y. [2] has mntiond that QFD is a widly usd customr drivn dsign and manufacturing tool originatd in Japan in th lat Convrsion Voic customrs into Tchnical paramtrs (TR) th product to gt th maximum customr satisfaction within th limitd rsourcs is th objctiv QFD. Hausr J.R.[3] (1988) indicats that QFD utilizs four sts matrics calld Hous Quality (HOQ) to rlat Voic rs (VOC) to product planning, part dploymnt, procss planning and manufacturing oprations. Th QFD systm has bn dividd into four phass, ach phas s important outputs, gnratd from th phas s inputs, ar convrtd into th nxt phas as its inputs. So ach phas can b dscribd by a matrix WHATs and HOWs. Planning matrix QFD has two principal parts: Th customr portion and th Tchnical Portion [4]. Th basic input customr portion is Voic rs (VOC). VOC can b obtaind by various mthods lik focus groups, qustionnair, intrviws and customr survy tc. Most VOC in HOQ procss is gnratd from human bings prcptions and linguistic assssmnts that ar quit subjctiv and vagu. 3. Hous Quality Modl (HOQ Th stags involvd in HOQ modl ar dtaild as blow. Fig. 1 shows th block diagram th modl. STEP I: Th first stp is to idntify & collct th VOCs using any markting survy mthod lik Qustionnair, Focus Groups, Individual Intrviw, tc. In our study w hav usd Qustionnair survy

2 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr mthod to rach th customrs. Th VOCs collctd using th mthod mntiond abov can b groupd rlatd into a catgory using Affinity Diagram (Amrican Supplir Institut,[5] 1994; Bossrt[6], J.L., 1991; Cohn, L. [7]1995). Griffin A.[8] (1993) has suggstd a mthod arranging random data into natural and logical groups can also b usd. STEP II: To dtrmin th rlativ importanc ratings VOCs basd on customrs prcptions.suppos that through appropriat ways, K customrs hav bn slctd and M VOCs ar dnotd as V 1, V 2,..V M. Th Rlativ Wightags VOCs can b obtaind by using th 5 point scal importanc shown in scal (1) basd on th data collctd from th customrs (Elmor P.E.,[9] 1975; Millr G.A.,[10] 1965; Olsson U[11]., 1979). Markt Rsarch Improvmnt Ratio rs Markt Survy VOC Wightags to VOC Prioritizd VOC r comptitiv valuation Normalizd Wight for ach VOC I------I------II------I-----II-----I------II-----I II (1) vry low low modrat high vry high Th rlativ prcptions customrs for all th VOCs ar shown by scal (1). Th rlativ importanc VOC can b xprssd in th matrix form as blow.lt for th VOC V M, customr K allocats a rlativ importanc rating g mk, as shown in matrix A: M Input for Phas II Fig. 1: Proposd Modl. K k V 1 g 11 g 12 g1k g mk = V 2 g 21 g 22 g 2k V 3 g 31 g 32.. g 3k (A) g k = (1/m) g mk m=1 whr m = 1,2,3, M & k= 1,2,3, K (2) g g is th global avrag which signifis th avrag prcptions all th customrs K with rspct to all th VOCs (V M ).It can b calculatd using quation (3). M K g g = (1/ MK) g mk (3) whr k = 1,2,3, K - V M g m1 g m2 g mk Rlativ Normalizd rating for V M can b calculatd from quation (1) K V m = (1/k) (g mk / g k ) * g g m = 1,2,3, M (1) k=1 Whr g k i s th avrag individual VOC for K customrs can b calculatd using quation (2). Equation (1) on simplification givs normalizd rlativ importanc wights for ach VOC and can b rprsntd by vctor V. V = (V 1, V 2, V 3 V M )

3 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr SETP III: Th nxt stp is to conduct r ptitiv Analysis. Th customrs prcptions rgarding ach VOC hav bn takn and th customrs compar ach brand with rspct to diffrnt VOC. This customr comptitiv analysis can b shown in matrix B. Suppos thr ar L brands oprating in th businss. Lt C 1 b our brand. r K supplis a rating x mk on company C l s prformanc in trms V M using scal (1). Th prformanc rating all th companis C L on VOCs, V M can b rprsntd sparatly in th matrix form (B). K K V 1 x 1l x 12.. x 1k X = V 2 x 2l x 22 x 2k -----(B) V M x ml x m2 x mk Th normalizd importanc rating (I R ) company C L can b obtaind using quation (4) K I R = 1/k (x mk / x k ) * x g (4) k=1 whr m = 1,2,3, M Whr x k is th avrag individual VOC for company in concrn givn by K customrs can b calculatd using quation (5). x g is Global avrag th importanc rating all th VOC for panis. x g can b valuatd using quation (6) M x k = (1/m) x mk (5) m=1 whr m = 1,2,3, M & k= 1,2,3,----K. M K x g = (1/ MK) g mk whr k = 1,2,3, K. ---(6) Th normalizd importanc rating I R all th companis can b shown in matrix (C). C 1 V 1 I Rl1 C 2 C L I Rl2 I R1L I R = V 2 I R2l I R22 I R2L -- (C) V M I Rml I Rm2 I Rml Th normalizd customr comptitiv matrix will giv th rlativ comptitiv stats all th comptitors with rspct to ach VOC. This will provid information ach company s position for all VOC. Th normalizd importanc in th matrix shows th standing ach company for ach VOC. Th probabilitis corrsponding to diffrnt VOCs for individual company can b calculatd. Th company which has highst probability for a particular VOC spcifis th comptitiv advantag in trms that VOC. Th company which has th last probability in a particular VOC signifis th nd/scop for improvmnt in that VOC. Th probabilitis for ach VOC for focusd company ar calculatd with rspct to comptitors.for th final importanc rating on customr comptitiv analysis mor wightag has to b assignd to that VOC which has got last probability. Prioritization VOC can b don by calculating th invrs probabilitis for ach VOC. Th VOC which has th highst valu will b on th top Priority. Th invrs Probabilitis company in concrnd with rspct to all VOCs and comptitors can b dnotd by a vctor C P. C P = (C P1, C P2, C P3, C PM ) Whr C P1, C P2 tc ar th invrs probabilitis ach VOC for company in concrn. SETP IV: This stp dtrmins th company on concrn s currnt Prformanc Goal. Th prformanc goal for all th VOC can b st. Ths goals can b st ralistically by th company which is th outcom many managrial dcisions. Assum that for V M, a propr prformanc goal (a m ) has bn st using scal (1). Thus th pany has a Goal Prformanc vctor in trms th VOCs dnotd as a. a = (a 1, a 2, a 3,...a m )

4 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr Each goal prformanc lvl should not b lowr than currnt prformanc lvl. Th improvmnt ratio for V M can b dnotd by U M. Th U M can b calculatd by quation (7). U M = a m / x m (7) using scal 1. Tabl 1(a) shows th rlativ importanc about th VOCs. Tabl 1(a): rs prcption on th Rlativ Importanc Th improvmnt ratios can b dnotd by vctor U. U = (u 1, u 2 u m ) STEP V:Th nxt stp is to dtrmin th importanc ratings all VOCs. Th final importanc rating VOC for th company in concrn can b a simpl summation rlativ importanc (V), ptitiv Probability (C P ) and improvmnt Ratio (U). Th final Importanc Rating VOC is dnotd by F, and can b calculatd by quation (8). F = (V+ C P + U) (8) Voic mrs VOC 1 r(1) Modrat r(2) VOC 2 Vry r(3) r(4) Vry Modrat Vry r(5) Vry Modrat On simplifying th quation (8) th final importanc wightag ach VOC can b dtrmind and highr priority should b assignd to highr valu th importanc wightags. Th outcom quation (8) will b th prioritizd VOC. 4 ILLUSTRATIVE EXAMPLES Th modl can b undrstood with th hlp following illustration. Hr a brand a Sauc manufacturing company is slctd to illustrat th concpts and computations. Sauc manufacturing company dnotd as C 1 wishs to improv th sals in th rgion in rspons to th comptition. STEP I: Th first stp for th company C 1 is to idntify its targt markt. This can b don by using appropriat Markt Rsarch tchniqu as discussd arlir. Hr w assumd that th company has alrady idntifid its targt markt, for th illustrations purpos fiv customrs bn slctd to conduct th HOQ analysis i.. K= 5. With th hlp Focus Groups, intrviws, qustionnair, tc ths fiv customrs idntifis fiv Voic rs (VOCs) for th product undr considration, i.., Sauc. Ths ar: Packaging, Lif, Viscosity, Colour and Tast. STEP II: : All VOCs will not b prcivd alik by all th customrs. Th K customrs i.. 5 ar askd to giv thir prcptions on th rlativ importanc VOCs VOC 3 Modrat Modrat Vry VOC 4 Low Modrat VOC 5 Vry Low Modrat Modrat Modrat Low Low Th customrs prcptions on th rlativ importanc ar linguistics in natur and can b convrtd in to crisp numbrs using scal 1. Tabl 1(b) shows th convrtd rlativ importanc into crisp numbrs. Tabl 1(b): rlativ importanc rating th 5 VOCs basd on th fiv customrs Voic mrs r(1) r(2) r(3) r(4) r(5) VOC VOC VOC VOC VOC

5 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr Th normalizd rlativ importanc ratings for all th Tabl 2(b): r comptitiv analysis VOCs i.. V M can b computd using quation 1 and 2.Equation (1) on simplification givs normalizd rlativ importanc wights for ach VOC and can b rprsntd by vctor V. Voic mrs mr(1) mr(2) mr (3) mr(4) mr( 5) V = (V 1, V 2, V 3 V M ), i.. V= (7.55, 5.32, 6.1, 4.50, 6.93) Stp III: This stp involvs th customr comptitiv valuation. Th sauc manufacturing company C 1 has idntifid thr major comptitors i.. C 2, C 3, C 4 ach which mak similar typ sauc. In ordr to undrstand th sauc markt and company s rlativ position in th markt and to finally find out th prioritis th VOCs for furthr improvmnt, th pany C 1 asks fiv customrs to asss rlativ prformanc its own brand with comptitiv brands. VOC VOC VOC VOC VOC for scond company Tabl 2(c): r comptitiv analysis for third company Th customr comptitiv analysis for four companis is shown in tabl 2(a-d). Tabl 2(a): r comptitiv analysis for first company Voic mrs r(1) r(2) r(3) r(4) r(5) Voic mrs r(1) r(2) r(3) r(4) r(5) VOC VOC VOC VOC VOC VOC VOC VOC VOC VOC

6 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr Tabl 2(d): r comptitiv analysis for fourth company Voic rs mr(1) mr(2) mr(3) mr(4) mr(5) VOC VOC importanc rating on customr comptitiv analysis mor wightag has to b assignd to that VOC which has got last probability. Our study is mainly for th company 1 i.. C 1 thrfor probabilitis for ach VOC for C 1 has to calculatd with rspct to comptitors. Th invrs Probabilitis pany (C 1 ) our concrn with rspct to all VOC and comptitors can b dnotd by vctor C P i.. first column th Probability matrix. Tabl 4: Probability Matrix VOC Voic rs pany(1) pany(2) pany(3) pany(4) VOC C 1 C 2 C 3 C 4 VOC VOC Th normalizd customr comptitiv valuation for four companis by fiv customrs can b obtaind by quation 4, 5 and 6.Th normalizd customr comptitiv valuation can b rprsntd in normalizd importanc matrix as shown in tabl 3. Tabl 3: Normalizd Rlativ Importanc Matrix Voic rs pany(1) C 1 pany(2) C 2 pany(3) C 3 pany(4) C 4 VOC VOC VOC VOC Th invrs th probabilitis for company C 1 is rprsntd by vctor C P. C P = (C P1, C P2, C P3, C P4 ) VOC VOC VOC VOC VOC Th normalizd importanc in th matrix shows th standing ach company for ach VOC. Th probabilitis ach VOC for ach company can b calculatd & shown in Probability matrix (P) Tabl 4. Th company which has highst probability in a particular VOC spcifis th comptitiv advantag in that VOC for th company. Th company which has th last probability in a particular VOC spcifis th nd/scop for improvmnt in that VOC. For th final Aftr calculating th invrs probabilitis ach VOC for pany C 1 is. STEP IV: Cp = (3.768, 5.689, 4.813, 5.548, 5.694) Basd on th rsourcs availabl and th rlativ prformanc th four companis on 5 VOCs, company C 1 can st improving goals on ach VOC to bttr satisfy th customr nds. C 1 dcids th prformanc goals on th VOC using scal 1. Th currnt prformanc th company C 1 is dcidd on th basis customr valuation i.. rlativ prcptions.thus th pany C 1 has a Goal Prformanc vctor in trms th VOCs dnotd as vctor a. a = (a 1, a 2, a 3 a m )

7 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr This st goals is shown tabl 5. It is notd all th goal prformanc lvl should b highr than C 1 s currnt prformanc. Tabl 5: Improvmnt Ratios VOCs A X U VOC VOC VOC VOC VOC Tabl 6: Normalizd Valus V, C P and U VOCs V C P U VOC VOC VOC VOC VOC Th final wightags ach VOC obtaind as shown blow in tabl 7. Tabl 7: Final Wightags ach VOC Th improvmnt ratios can b dnotd by vctor U. U = (u 1, u 2 u m ) Th valu U can b calculatd using quation 6, th rsult is: U = (1.135, 1.214, 1.537, 1.158, 1.001) Stp V: Th nxt stp is to put th valus V, C P and U in quation 7. F = (V+ C P + U) VOCs V+ C P + U VOC VOC VOC VOC VOC On putting th valus V, C P, U and normalizing th matrix. Th normalizd valu V, C P and U will b usd in quation 7 to gt th final priority VOC as shown in tabl 6. Th top priority will b assignd to th VOC baring th highst wightag. Tabl no. 8 shows th final Prioritizd Voic r for company

8 Intrnational Journal Enginring Rsarch & Tchnology (IJERT) Vol. 2 Issu 10, Octobr Tabl 8: Final Prioritizd Voic rs critrion among othr critria to mak th stratgic dcision Product Modification or Slction Targt Markt. VOICE OF CUSTOMERS VOC5 (TASTE) VOC3 (COLOUR) VOC4 (LIFE) VOC1 (VISCOSITY) VOC2 (PACKAGING) PRIORITY I II III IV V REFERENCES [1]Chan Lai Kow and Ming Lu Wu (2004). A systmatic approach to quality function dploymnt with a full illustrativ xampl, Elsvir, 33 (2), [2] Akao, Y. (1990). Quality Function Dploymnt: Intgrating r Rquirmnts into Product Dsign (translatd by Glnn Mazur), Productivity Prss, Cambridg, MA, [3]Hausr J.R., Clausing D. (1988). Th Hous Quality, Harvard Businss Rviw May -Jun Tabl 8 indicats th prioritis th Voic rs for company 1, i.. TASTE has to givn on th Top Priority has to b assignd to Tast th Sauc, th company has to improv th Tast th sauc to dal with th comptition, Th company has to mak th ncssary changs in th Colour th sauc as pr th Voic rs, Th company has to improv th Lif th Sauc so that it can b usd for th long priod. As it indicats in tabl 8 th VOC Viscosity and Packaging ar at th fourth and fifth position rspctivly in th priority it mans that th company is on a rlativly advantagous position as compard to its comptitors and no improvmnt is rquird in th short run for ths two VOCs. Th company has to mak th stratgis for th improvmnt in Tast, Colour and Lif attributs th sauc to gain th substantial markt shar in th rgion. 5. CONCLUSIONS Th proposd modl givs th prioritizd Voic rs rquird for th product as an outcom th Planning Matrix Hous Quality. Ths prioritizd VOCs will b an input for th Part Dploymnt phas Quality Function Dploymnt. Th scond phas i.. th parts Dploymnt phas QFD will provid th ncssary changs in th parts to dploy th rquird Voic rs. Th pany can considr this Prioritizd Voic r as a [4] Day Ronald G (1996). Quality Function Dploymnt, Linking a company with Its rs, Tata McGraw- Hill Publishing pany Limitd, ASQC Quality Prss, 20. [5] Amrican Supplir Institut, (1994). Quality function dploymnt (srvic QFD): 3- day workshop. Darborn, MI: ASI Prss. [6] Bossrt, J.L., (1991). Quality function Dploymnt: a practitionr s approach, ASQC Quality Prss, Milwauk, WI. [7] Cohn, L. (1995). Quality function dploymnt: how to mak QFD work for you, Addison- Wsly, Rading, MA. [8] Griffin, A., and Hausr, J.R. (1993). Th voic customr, Markting Scinc 12 (1), [9] Elmor, P.E., and Bggs, D.L. (1975). Salinc concpts and commitmnt to xtrm judgmnts in rspons pattrn tachrs, Education 95 (4), [10] Millr, G.A. (1965). Th magic numbr svn, plus or minus two, Psychological Rviw 63, [11]Olsson, U. (1979). On th robustnss factor analysis against crud classification th obsrvations, Multivariat Bhavioral Rsarch 14,