Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

An integrated approach to concept evaluation in a new product development

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

A new product development (NPD) process can be thought as a comprehensive process in which the design is progressively detailed through a series of phases. At the end of each phase a design review is held to approve the design and release or not it to the next level. As one of these phases, concept selection aiming to select the most appropriate concept for further development, is conducted earlier in the process. As the further development progresses on a selected concept, it becomes more difficult to make design changes in terms of cost and schedule dimensions, and therefore, selecting the best concept among a set of available alternatives has been an important issue for companies. On the other hand, in the presence of many alternatives and selection criteria, the selection problem becomes a multiple-criteria decision making concept selection problem. To solve this problem, in this work, an integrated approach bringing two popular methods together: the modified technique for order preference by similarity to ideal solution (TOPSIS) and the analytical network process (ANP). The ANP method is used to determine the relative weights of a set of quantitative and qualitative evaluation criteria, as the modified TOPSIS method utilized to rank competing concept alternatives. In addition, a real example is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Akao, Y. (1990). Quality function deployment: Integrating customer requirements into product design. Cambridge, MA: Productivity Press.

    Google Scholar 

  • Agarwal, A., & Shankar, R. (2003). On-line trust building in e-enabled supply chain. Supply Chain Management: An International Journal, 8(4), 324–334.

    Article  Google Scholar 

  • Ayag, Z. (2002). An analytic-hierarchy-process simulation model for implementation and analysis of computer-aided systems. International Journal of Production Research, 40(13), 3053–3073.

    Article  Google Scholar 

  • Ayag, Z. (2005a). An integrated approach to evaluating conceptual design alternatives in a new product development environment. International Journal of Production Research, 43(4), 687–713.

    Article  Google Scholar 

  • Ayag, Z. (2005b). A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment. IIE Transactions, 37, 827–842.

    Article  Google Scholar 

  • Ayag, Z., & Ozdemir, R. G. (2007). An ANP-based approach to concept evaluation in a new product development (NPD) environment. Journal of Engineering Design, 18(3), 209–226.

    Article  Google Scholar 

  • Ayag, Z., & Ozdemir, R. G. (2011). An intelligent approach to machine tool selection through fuzzy analytic network process. Journal of Intelligent Manufacturing, 22(2), 163–177.

    Article  Google Scholar 

  • Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200, 198–215.

    Article  Google Scholar 

  • Briand, L. C. (1998). COTS evaluation and selection. In Proceedings of the international conference on software maintenance, pp. 222–223.

  • Brown, S. L., & Eisenhardt, K. M. (1995). Product development: Past research, present findings and future directions. Academy of Management Review, 4, 343–378.

    Google Scholar 

  • Chesbrough, H. W., & Teece, D. J. (2002). Organizing for innovation: When is virtual virtuous? Harvard Business Review, 80, 127–135.

  • Dagdeviren, M. (2008). Decision making in equipment selection: An integrated approach with AHP and PROMETHEE. Journal of Intelligent Manufacturing, 19(4), 397–406.

    Article  Google Scholar 

  • Duffy, A. H. B., Andreasen, M. M., Maccallum, K. J., & Reijers, L. N. (1993). Design co-ordination for concurrent engineering. Journal of Engineering Design, 4, 251–261.

    Article  Google Scholar 

  • Ertugrul, I., & Karakasoglu, N. (2009). Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Systems with Applications, 36, 702–715.

    Article  Google Scholar 

  • Finger, S., & Dixon, J. R. (1989a). A review of research in mechanical engineering design, part I: Descriptive, prescriptive and computer-based models of design processes. Research Engineering Design, 1, 51–68.

    Article  Google Scholar 

  • Finger, S., & Dixon, J. R. (1989b). A review of research in mechanical engineering design, part II: Representations, analysis, and design for the life cycle. Research Engineering Design, 1, 121–137.

    Article  Google Scholar 

  • Fitzsimmons, J. A., Kouvelis, P., & Mallick, D. N. (1991). Design strategy and its interface with manufacturing and marketing strategy: A conceptual framework. Journal of Operations Management, 10, 398–415.

    Article  Google Scholar 

  • Gates, W. (1999). Business@the speed of sound. Grand Central Publishing.

  • Gorener, A. (2012). Comparing AHP and ANP: An application of strategic decisions making in a manufacturing company. International Journal of Business and Social Science, 3, 194–208.

    Google Scholar 

  • Griffin, A., & Hauser, J. R. (1996). Integrating R&D and marketing: A review and analysis of the literature. Journal of Product Innovation Management, 13, 191–215.

    Article  Google Scholar 

  • Hwang, C. L., & Yoon, K. (1981). Multiple-criteria decision making: Methods and applications, a state of art survey. New York: Springer.

    Google Scholar 

  • Işıklar, G., & Buyukozkan, G. (2007). Using a multi-criteria decision making approach to evaluate mobile phone alternatives. Computer Standards and Interfaces, 29, 265–274.

    Article  Google Scholar 

  • Kahraman, C., Buyukozkan, G., & Ates, N. Y. (2007). A two phase multi-attribute decision-making approach for new product introduction. Information Sciences, 177, 1567–1582.

    Article  Google Scholar 

  • Kang, H. Y., Lee, A. H. I., & Yang, C. Y. (2012). A fuzzy ANP model for supplier selection as applied to IC packaging. Journal of Intelligent Manufacturing, 23(5), 1477–1488.

    Article  Google Scholar 

  • King, A. M., & Sivaloganathan, S. (1999). Development of a methodology for concept selection in flexible design strategies. Journal of Engineering Design, 10, 329–349.

    Article  Google Scholar 

  • Krishnan, V., & Ulrich, K. T. (2001). Product development decisions: A review of the literature. Management Science, 47, 1–21.

    Article  Google Scholar 

  • Lee, J. W., & Kim, S. H. (2000). Using analytic network process and goal programming for interdependent information system project selection. Computers and Operations Research, 27, 367–382.

    Article  Google Scholar 

  • Lin, M. C., Wang, C. C., Chen, M. S., & Chang, C. A. (2008). Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry, 59, 17–31.

    Article  Google Scholar 

  • Marsh, S., Moran, J. V., Nakui, S., & Hoffherr, G. (1991). Facilitating and training in quality function deployment. Methuen, MA: GOAL/QPC.

    Google Scholar 

  • Meade, L., & Sarkis, J. (1999). Analyzing organizational project alternatives for agile manufacturing process: An analytical network approach. International Journal of Production Research, 37, 241–261.

    Article  Google Scholar 

  • Okudan, G. E., & Tauhid, S. (2008). Concept selection methods—a literature review from 1980 to 2008. International Journal of Design Engineering, 1, 243–277.

    Article  Google Scholar 

  • Okudan, G. E., & Shirwaiker, R. A. (2012). A multi-stage problem formulation for concept selection for improved product design. In PICMET 2006 proceedings, 9–13 July, Istanbul, Turkey.

  • Onut, S., & Soner, S. (2008). Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment. Waste Management, 28, 1552–1559.

    Article  Google Scholar 

  • Ozaki, T., Lo, M. C., Kinoshita, E., & Tzeng, G. H. (2012). Decision making for the best selection of suppliers by using minor ANP. Journal of Intelligent Manufacturing, 23(6), 2171–2178.

    Article  Google Scholar 

  • Pahl, G., & Beitz, W. (1984). Engineering Design (pp. 119–138). Springer Verlag.

  • Pugh, S. (1991). Total design (pp. 67–85). Reading: Addison-Wesley.

    Google Scholar 

  • Reddy, R., & Mistree, F. (1992). Modeling uncertainly in selection using exact interval arithmetic, DE-Vol. 24, DTM, ASME, Scottsdale, AZ, pp. 193–201.

  • Saaty, T. L. (1981). The analytical hierarchy process. New York: McGraw Hill.

    Google Scholar 

  • Saaty, T. L. (1989). Decision making, scaling, and number crunching. Decision Science, 20, 404–409.

    Article  Google Scholar 

  • Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. Pittsburgh, PA: RWS Publication.

    Google Scholar 

  • Saaty, T. L., & Takizawa, M. (1986). Dependence and independence—from linear hierarchies to nonlinear networks. European Journal of Operational Research, 26, 229–237.

    Article  Google Scholar 

  • Scott, M. (2002). Quantifying certainty in design decisions: Examining AHP. In Proceedings of the DETC2002 /DTM-34020, Montreal, Canada.

  • Sheu, J. B. (2007). A hybrid neuro-fuzzy analytical approach to mode choice of global logistics management. European Journal of Operational Research, 189, 971–986.

    Article  Google Scholar 

  • Sharma, S., & Balan, S. (2013). An integrative supplier selection model using Taguchi loss function, TOPSIS and multi criteria goal programming. Journal of Intelligent Manufacturing, 24(6), 1123–1130.

    Article  Google Scholar 

  • Shyur, H. J. (2006). COTS evaluation using modified TOPSIS and ANP. Applied Mathematics and Computation, 177, 251–259.

    Article  Google Scholar 

  • Shyur, H. J., & Shih, H. S. (2006). A hybrid MCDM model for strategic vendor selection. Mathematical and Computer Modeling, 44, 749–761.

    Article  Google Scholar 

  • Taha, Z., & Rostam, S. (2012). A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell. Journal of Intelligent Manufacturing, 23(6), 2137–2149.

    Article  Google Scholar 

  • Thurston, D., Carnahan, J., & Liu, T. (1991). Optimization of design utility, DTM-Vol. 31, ASME, Miami, pp. 173–180.

  • Thurston, D. L., & Carnahan, J. V. (1992). Fuzzy ratings and utility analysis in preliminary design evaluation of multiple attributes. Journal of Mechanical Design, 114, 648–658.

    Article  Google Scholar 

  • Triantaphyllou, E. (2000). Multiple-criteria decision making methods: A comparative study. Dordrecht: Kluwer.

  • Tsaur, S. H., Chang, T. Y., & Yen, C. H. (2002). The evaluation of airline service quality by fuzzy MCDM. Tourism Management, 23, 107–115.

    Article  Google Scholar 

  • Ulrich, K. T., & Eppinger, S. D. (2000). Product design and development (2nd ed.). Irwin: McGraw-Hill.

  • Welch, D., & Kerwin, K. (2003). Rick Wagoner’s game plan. Business Week, 52–60.

  • Whitney, D. T. (1988). Manufacturing by design. Harvard Business Review, 66, 83–91.

    Google Scholar 

  • Yurdakul, M. (2003). Measuring long-term performance of a manufacturing firm using analytic network process (ANP) approach. International Journal of Production Research, 41(11), 2501–2529.

    Article  Google Scholar 

  • Zahedi, F. (1986). The analytic hierarchy process: A survey of the method and its application. Interfaces, 16, 96–108.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Industrial Engineering Department, Faculty of Engineering and Natural Sciences, Kadir Has University, Cibali, Fatih, 34083 , Istanbul, Turkey

    Zeki Ayağ

Authors
  1. Zeki Ayağ
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zeki Ayağ.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ayağ, Z. An integrated approach to concept evaluation in a new product development. J Intell Manuf 27, 991–1005 (2016). https://doi.org/10.1007/s10845-014-0930-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-014-0930-7

Keywords

Search

Navigation