Determination of Integrated Risk Degrees in Product Development Project

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1 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA Determnaton of Integrated sk Degrees n Product Development Project D. W. Cho., J. S. Km., and H. G Cho. Abstract Wth the rapd enhancement of product functons and performances, the cycle of technologcal nnovaton s becomng shorter. Accordngly, t s dffcult to meet varous customer needs due to ncreased development costs and the shortened development perod. Ths also has a sgnfcant mpact on establshng corporate strateges. Successful product development s essental to the survval of a company n the compettve market. A company needs to dentfy the dverse rsk factors that mght occur n the development process, measure how much they wll affect the development process, and create strateges and tactcs to counter them. Aganst ths backdrop, ths paper draws upon the possble rsks n the product development project and presents how to measure these rsk degrees and the ntegrated rsk degrees of the whole project n order to more effectvely manage them. In other words, the paper shows how to determne the mpact values of rsks n each development phase, the probablty of rsk occurrences and the rsk degrees and how to calculate the ntegrated rsk degree of each phase. Index Terms product development project, mpact value, probablty of rsk occurrences, rsk degrees, ntegrated rsk degrees I. INTODUCTION A product development project can determne the success and falure of the manufacturng ndustry. However, many companes see such projects as extremely dffcult tasks because of the hgh nvestment costs and chances of falure. Approxmately 80 % of globally-conducted product development projects fal whle they are n progress. Even the 0% of completed projects took more costs and tme than expected []. That was because they faled to recognze the rsks and rsk degrees n advance and there was no systematc way to effectvely deal wth the rsks that occurred n the mddle of the project. Fg. Integrated processes for product development As seen n Fg., a product development project s evolvng nto an ntegrated process of varous concepts []. Successful product development requres total qualty management for qualty mprovement, change management to deal wth nternal and external changes, rsk management aganst rsk occurrence and rsk degrees, project management to save costs and tme, and concurrent engneerng for parallel communcaton-based desgn rather than seral desgn. These processes should be systematcally connected. Ths paper studes concurrent engneerng and rsk management and presents how to take out the potental rsk factors n the development project and calculate the ntegrated rsk degree of the whole project. Fg. shows the overvew of ths paper. D. W. Cho. Master student, Department of Systems Management Engneerng, Sungkyunkwan Unversty, Suwon , Korea (e-mal: J. S. Km. Doctoral student, Department of Systems Management Engneerng, Sungkyunkwan Unversty, Suwon , Korea (e-mal: H. G Cho. Professor, Department of Systems Management Engneerng, Sungkyunkwan Unversty, Suwon , Korea (correspondng author) phone: ; e-mal: Fg. The structure to determne ntegrated rsk degrees

2 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA II. CLASSIFICATION OF ISK FACTOS In the plannng phase of product development project, companes are most lkely to overlook the consderaton of rsks that can happen durng the project. If a company fals to manage systematcally those rsks, t may face the dffcultes that the project s not successfully completed wthn a scheduled tme frame, and so requres hgher costs[3]. Frst of all, a company needs to nvestgate, collect, and classfy potental rsk factors arsng from the product development project. Table Ⅰ presents the general desgn phases. Also, the example of the rsk factors for each phase are presented n Table Ⅱ [4]-[]. Plannng Marketng Artculate market opportunty Defne market segments Desgn Consder product Platform and archtecture Assess new technologes Manufacturng Identfy producton constrants Set supply chan strategy Other Functon esearch: Demonstrate Avalable technologes Fnance: Provde plannng goals General Management: Allocate project resources Phase : Concept Development Collect customer needs Identfy lead users Identfy compettve products Table I. THE GENEIC PODUCT DEVELOPMENT POCESS [] Phase : Phase 3: System-Level Detal Desgn Desgn Investgate feasblty of product concepts Develop ndustral desgn concepts Buld and test expermental prototypes Estmate manufacturng cost Assess producton feasblty Fnance: Facltate economc analyss Legal: Investgate patent ssues Develop plan for product optons and extended product famly Set target sales Prce pont(s) Generate alternatve product archtectures Defne major subsystems and nterfaces efne ndustral desgn Identfy supplers for key components Perform make-buy analyss. Defne fnal assembly scheme Set target costs Fnance: Facltate make-buy analyss Servce: Identfy servce ssues Develop marketng plan Defne part geometry Choose materals. Assgn tolerances. Complete ndustral desgn control documentaton Defne pece-part producton processes Desgn toolng. Defne qualty assurance processes Begn procurement of long-lead toolng Testng and efnement Develop promoton and launch materals Facltate feld testng elablty testng. Lfe testng Performance testng Obtan regulatory approvals Implement desgn changes Facltate suppler amp-up efne fabrcaton and assembly Processes Tran work force efne qualty assurance processes Phase 5: Producton amp-up Place early producton wth Key customers Evaluate early producton output Begn operaton of entre producton system

3 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA Functons Marketng Desgn Manufacturng Fnancal and economc Other Functon Plannng Shfts n market Supply Avalablty of raw materals Competton Inadequate Specfcaton Scope of work Defnton Equpment Productvty System outage Unavalablty Economc dsaster Exchange rate Fluctuaton Inflaton Table II. ISK FACTOS CLSSIFIED BY PHASE* Phase : Concept Development Changes n the quantty used by other buyers Changes n consumer tastes Desgn change Conflct of document Equpment productvty System outage Unavalablty Economc dsaster Exchange rate Fluctuaton Inflaton Phase : System-Level Desgn Changes n the quantty used by other buyers End value n the market Desgn change Equpment productvty System outage Unavalablty Economc dsaster Exchange rate Fluctuaton Inflaton *More rsk factors have been collected and classfed by functons n our research Phase 3: Detal Desgn Shfts n market Supply Desgn change Equpment productvty System outage Unavalablty Economc dsaster Exchange rate Fluctuaton Inflaton Testng and efnement Shfts n market Supply Equpment productvty System outage Unavalablty Economc dsaster Exchange rate Fluctuaton Inflaton Bankruptcy Phase 5: Producton amp-up Shfts n market supply Equpment productvty System outage Unavalablty Economc dsaster Exchange rate Fluctuaton Inflaton Bankruptcy Ⅲ. DETEMINATION OF ISK DEGEES Calculate the rsk degrees of each phase and put those degrees together to calculate the ntegrated rsk degrees for the whole project. sk factors n each phase have dfferent degrees of mportance, so determne ther relatve mportance through the AHP (Analytc Herarchc Process) and convert the fgure nto an mpact values by usng the fuzzy algorthm. Fnally, calculate the probablty of the rsk occurrences of the rsk factor and multply the probablty by the mpact value to get the rsk degree of a rsk factor. sk degree s defned as Equaton () [3]. = P I () = rsk degree of rsk factor I = mpact value of rsk factor P = probablty of rsk occurrences of rsk factor A. The AHP (Analytc Herarchc Process) The AHP s a decson-makng process usng herarchcal analyss, whch was frst developed by T.L Satty[4] n the 970s. It s a mult-crtera decson method that captures the knowledge, experence, and ntuton of decson makers through a par-wse comparson between the elements of the decson-makng herarchy[5]. The features of AHP are that both quanttatve and qualtatve elements are consdered for decson-makng as the method nvolves logc from human thnkng and experence-based ntuton. Therefore, t s an approprate way to draw the relatve mportance of the rsk factors by development phases. Product development projects are dfferently exploted dependng on the product and corporate envronment. The potental rsks of the projects also have dfferent mportance. For that reason, ths paper suggests an AHP analyss to determne the mportance and mpact value of each rsk factor n a project. However, even though the AHP can quantfy the experence and knowledge of experts, these values have nherent ambguty. Thus, ths paper attempts to resolve the ambguty through the fuzzy theory. B. Fuzzy Theory sk factors can occur smultaneously n a product development project, so they should be dfferently handled dependng on ther mpact values and ramfcatons. To do so, the mportance of each rsk factor through AHP s frst determned and s removed ts ambguty by quantfyng the mpact values of the rsks usng the fuzzy theory. The fuzzy theory was suggested by Zadeh[6] that mathematcally demonstrates unclear quanttatve data as well as uncertanty and the ambguty of human thnkng and judgment [7]. To apply the fuzzy theory for a problem, an approprate membershp functon s requred. As development projects have dfferent mpact values dependng on ther degree of

4 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA dffculty. Dfferent membershp functons should also be used n accordance wth the level of dffculty. In ths paper, the dffculty of a project s determned after all the dvsons engagng n the product desgn phase make decsons on 9 dmensons shown n the Table Ⅲ, on the assumpton that concurrent engneerng s ntroduced [8]. That s, the weght level A of each dmenson the IDM s defned as, and B, C, and D, as, 3, and 4, respectvely to determne the dffculty of the project development project. As the IDM has 9 dmensons, the projects can have 9 levels of dffculty at the mnmum and 36 at the maxmum. Consequently, 8 membershp functons wll be defned and appled to determne the mpact value a rsk factor. Table III. IDM(INFLUENCING DIMENSIONS MATIX) Level Dmenson A B C D Product Complexty Product Technology Program Structure Program Futures Competton Busness elatonshp Team Scope esource Tghtness Schedule Tghtness (A: low, B: medum, C: hgh, D: very hgh) To apply the relatve mportance of a rsk factor obtaned through AHP nto the fuzzy algorthm, the value of ts relatve mportance should be normalzed through Equaton (). w I = () w max th w = elatve mportance of rsk factor w max = The maxmum value of relatve mportance th I = Normalzed mportance for rsk factor Fg. 3 sks over project lfe cycle[6] Even for experts, t s very hard to detect the sgns of rsks n the early phases. There are many reasons behnd ths. Frstly, dverse rsk factors can occur smultaneously. Among them, some are subject to tme whle others are ndependent of tme. In addton, one rsk factor can affect the occurrences of another rsk factor. That s also, the number of rsk occurrences follows varous statstcal dstrbutons. The most common way of predcton s to estmate the probablty of a rsk occurrence based on nformaton from smlar projects conducted n the past. The actual dstrbuton of rsk occurrence can vary dependng on dfferent corporate crcumstances, but ths paper analogzed dstrbuton types from Fg. 3. Fg. 3 shows that rsks occur more frequently n the early phase and rapdly decrease n the later part of the project. However, the paper assumed that the occurrence dstrbuton of a rsk factor s mportant, and that f effectve response actvtes, based on concurrent engneerng, are executed for a rsk factor occurrence, t wll sgnfcantly reduce the probablty of the same rsk occurrence n the later phase of project. Based on those assumptons, the frequency of rsks follows a gamma dstrbuton and s defned as n Fg. 4. Normalzed mportance and membershp functon determne mpact values. However, n order to convert a fuzzy fgure nto a scalar, defuzzfacaton should be followed. Ths paper uses the clpped center of gravty method, the most general way of defuzzfcaton, to determne the mpact value of a rsk factor. C. The Probablty of sk Occurrences As shown n Fg. 3, rsk factors occur more durng the early phase of project development. sks n the early stages cost less to tackle than those n the later phases. Fg. 4 Probablty of rsk occurrences for a rsk factor

5 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA A gamma dstrbuton shows the tme to wat for every n tmes of Posson occurrences. The Posson dstrbuton ndcates the number of a certan events such as arrvals and servces wthn a gven tme. The densty probablty functon of gamma dstrbuton gven n Equaton (3). n n λx P(X > u) = Γ λ x e (3) (n) u λ= the amount of an event that occurs wthn a gven tme n= the amount of exponental varables for whch the tme of event s ndependent x= the tme to be taken untl the occurrence of an event Γ( n) = ( n ) Γ( n ), Γ() = x > 0, n > 0, λ > 0 x, n= real vales If the probablty of a rsk occurrence follows a gamma dstrbuton, the probablty for multple number of rsks occurred wll be also defned as a gamma dstrbuton. However, n the actual development project, the probablty of occurrences of a rsk factor does not necessarly ft a gamma dstrbuton. Ⅳ. DETEMINATION OF INTEGATED ISK DEGEE In a product development project, a harmonc mean s appled to calculate the average rsk degree of each phase. If rsk factors are regarded as electrc resstance aganst a successful completon of the project, a harmonc mean s approprate because t s more common for rsk factors to occur smultaneously, rather than consecutvely. Equaton (4) s used to compute a harmonc mean. p = + r r n r 3 r (4) consecutvely. Equaton (5) shows the ntegrated rsk degree n a product development project T = (5) 6 Ⅴ. AN EXAMPLE The ntegrated rsk degree of the project s determned n accordance wth the phases of Fg.. The degree s also affected by the determnaton of mpact values accordng to the mportance of rsks, the probablty of rsk occurrence, and the rsk degrees. In ths example, Inflaton affects the project fnance s used as a rsk factor. Frst of all, Table Ⅴ shows the assumed relatve mpact values through an AHP analyss of the rsk factors from phases 0 to 5. The dffculty of the project s assumed to be 30, based on the IDM (Table TABLE Ⅴ WEIGHTS OBTAINED FONM AHP ANALYSIS Phase Functons sks Weght Desgn Inadequate specfcaton 0.50 Conflct of document Phase 0 Lack Fnance Inflaton Exchange rate fluctuaton Phase Ⅵ), and the correspondng membershp functons s shown n Fg. 5. Table VI. IDM(INFLUENCING DIMENSIONS MATIX) ASSUMED FO A POJECT Level Dmenson A() B() C(3) D(4) Product Complexty = the average rsk degree per phase p th r = the rsk degree of factor n= the number of rsk factors Table Ⅳ shows the results of the harmonc mean for each desgn phase. Plannng Table IV. ISK DEGEES CLASSIFIED BY PHASES Phase : Concept Developmen t Phase : System-Level Desgn Phase 3: Detal Desgn Testng and efnement Phase 5: Producton amp-up Product Technology Program Structure Program Futures Competton Busness elatonshp Team Scope esource Tghtness Schedule Tghtness Project dffculty 30 (A: low, B: medum, C: hgh, D: very hgh) Unlke rsk degrees by phases, an arthmetc mean s appled to determne the ntegrated rsk degree of the project. That s because product development phases are carred out

6 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA Fg. 5 Choce of membershp functon The mpact values of the rsk factors can be calculated by phases and functons. But, ths example calculated only the mpact value of the Inflaton rsk among the fnancal rsks of Phase 0. Based on the AHP, the mportance of Inflaton s 0.78 n Table V. Then, select a membershp functon from Fg. 5, apply 0.78 to the fuzzy algorthm, and go through defuzzfcaton. After ths calculaton, the fnal mpact value s calculated at (efer to Fgs. 6-8) Fg 8. Defuzzfacaton usng clpped of gravty method To determne the probablty of rsk occurrences, the hstorcal data regardng the Inflaton factor should be collected and analyzed. If the rsk data shows that Inflaton factor occurs three tmes exponentally wth arrval rate, 0. n phase 0. the probablty of that rsk factor to be happened more than once wll be as follows. P(X 4) = P(X > 4) : tme perod for the phase 0=4 hour λ=/0, n=3 P[X > 4] = = ( 0 3 ) x e ( ) x 0 Fg 6. Membershp functon by AHP s evaluaton That s, the probablty of Inflaton occurrence s 0.43 and the fnal rsk degree s 0.967(0.69ⅹ0.43). Lkewse, all rsk factors n the phases can be calculated through the same process. A harmonc mean s appled to measure the average rsk degree by phases. In ths example, Table Ⅶ presents the harmonc means of rsk degrees that consder all rsk factors ncludng the factor of the Inflaton effect on the project fnance. The ntegrated rsk degree of the whole project s 0.4. Table VII. ISK DEGEE CLASSIFIED BY PHASES Phase : Phase : Phase Testng Phase 5: Concept System- 3: Plannn and Producton Developme Level Detal g efneme amp-up nt Desgn Desgn nt Integrated rsk degree = 6 Fg 7. Dstrbuton of mpact value of the rsk factor by fuzzy nferencng =0.4

7 Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0-, 009, San Francsco, USA Ⅵ. CONCLUSION Ths paper surveyed and collected the possble rsk factors n a product development project, and classfed the rsks by phases. Those rsks n each phase were also categorzed by functons. The surveyed, collected and classfed rsk factors can be selectvely appled dependng upon the corporate envronments or the developng products. The paper suggests a method to calculate the rsk degree of the whole project based on these factors. In other words, the paper ncludes: how to leverage the AHP and fuzzy theory to calculate mpact values; how to calculate the probablty of rsk occurrences through general probablty dstrbuton; and how to ntegrate the rsk degrees of each factor. If a company puts ths study nto practce and calculates the ntegrated rsk degree of a project n the plannng phase, the company wll be able to determne whether to conduct the project n the plannng phase, as well as whether or not to stop the ongong project. The bggest beneft s that the company can recognze the rsk degrees of a product development project and devse counter respondng actvtes. Moreover, the study enables the company to determne whether to manage the project ntensvely or not, thereby ncreasng the chances of the successful completon of the project. Consequently, ths wll help to reduce the tme and costs for product development and create new profts. Lastly, the study s expected to promote the development of the engneerng rsk management area. [0] T. J. Kloppenborg, Project Management: A Contemporary Approach. South-Western Cengage Learnng, 009, ch. 0. [] T.. Adlder, J. G. Leonard,. K. Nordgren, Improvng rsk management: movng from rsk elmnaton to rsk avodance, Informaton and Software Technology, 999, pp [] K. T. Ulrch, S. D, Epppnger, Product Desgn and Development. McGraw-Hll, 004, ch.. [3] C. A. Bana e Costa, J. C. Vansnck, A crtcal analyss of the egenvalue method used to derve prortes n AHP, European Journal of Operatonal esearch, vol. 87, 008, pp [4]. W. Saaty The analytc herarchy process-what t s and how t s used, Mathematcal Modelng, 987, pp [5] T. L. Saaty, Decson Makng for Leaders, ws Pubns, 995. [6] L. A. Zadeh, Fuzzy set, nformaton and Control, vol. 8, 965. [7] E. W. T. Nga, F. K. T. Wat., Fuzzy decson support system for rsk analyss n e-commerce development, Decson Support Systems, vol. 40, 005, pp [8] N. Sngh, System Approach to Computer-Integrated Desgn and Manufacturng. John Wley & Sons, 996, ch. 4. ACKNOWLEDGMENTS Ths study was supported by the Bran Korea Program of the Korea esearch Foundaton, 007. Ths work was also supported by the Korea Scence and Engneerng Foundaton (KOSEF) grant funded by the Korean government (MOST) ( ). EFEENCES [] C. John, Manage rsk n product and process development and avod unpleasant surprses, Engneerng Management Journal, 995, pp [] H. Kerzner, Project Management: A Systems Approach to Plannng, Schedulng, and Controllng. John Wley & Sons, 006. [3] J. O. Ahn, H. S. Jeung, J. S. Km, H. G. Cho, A framework for managng rsks on concurrent engneerng bass, Internatonal Conference on Management of Innovaton and Technology, 008, pp [4] D. V. Well-Stam, F. Lndenaar, S. V. Knderen, B. V. D. Bunt, Project rsk management : an essental tool for managng and controllng projects. Kogan Page, 007, pp [5] K. D. Mller, A Framework for Integrated sk Management n Internatonal Busness, Journal of Internatonal Busness Studes, vol. 3, 99, pp [6] L. P. Cooper, A research agenda to reduce rsk n new product development through knowledge management: a practtoner perspectve, Journal of Engneerng and Technology Management, vol. 0, 003, pp [7] P. K. Dey, Process re-engneerng for effectve mplementaton of projects, Internatonal Journal of Project Management, vol. 7, pp [8]. M. Wdeman, Project and program rsk management: a gude to managng project rsks and opportuntes, Project Management Insttute, 99, pp. A-~A-4. [9] S. Ghosh, J. Jntanapakanont, Identfyng and assessng the crtcal rsk factors n an underground ral project n Thaland: a factor analyss approach, Internatonal Journal of Project Management, 004, pp

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