Advertisement

Journal of Intelligent Manufacturing

, Volume 30, Issue 3, pp 1069–1083 | Cite as

A method for product platform planning based on pruning analysis and attribute matching

  • Qiuhua Zhang
  • Weiping Peng
  • Jin LeiEmail author
  • Junhao Dou
  • Xiangyang Hu
  • Rui Jiang
Article
  • 361 Downloads

Abstract

Product platform planning can greatly support product variant design, which is of great help to the implementation of mass customization (MC). In most of product platform planning methods, product modules and product families have been usually preplanned before products are designed, which would not make full use of the existing product resources. In this paper, we propose a method for product platform planning using the existing product data in product lifecycle management (PLM) database. The proposed method introduces two key technologies, i.e., pruning analysis and attribute matching. The pruning analysis is used to find out the sharing parts of different product families, which constitutes the basic framework of product platform; the attribute matching is used to classify product modules into different categories according to their sharing degrees, which reveals the relationships of different product modules and forms the association rules of product platform. The effectiveness of the proposed method is verified by the product data in the PLM database of a valve company. The proposed method greatly improves the reuse rate of existing product resources, providing an effective and fast way for enterprises to implement the MC strategy.

Keywords

Product platform Mass customization PLM database Pruning analysis Attribute matching 

Abbreviations

PLM

Product lifecycle management

MC

Mass customization

BOM

Bill of material

PST

Product structure tree

PFSTs

Product family structure trees

BM

Basic module

MuM

Must-selected module

MaM

May-selected module

PrM

Private product module

FSM

Families sharing product module

SSM

Series sharing product module

GSM

Global sharing product module

LCISF

Longest consecutive identical structure segment from the first node

List of symbols

\(P^{m}\)

Product series \(m, m\in N^{+}\)

\(PF_{Ni}^{i}\)

Product family \(N_{i}\) of product series \(P^{i}, N_i \in N^{+}\)

N

The total number of product family in an enterprise

\(Tr_{Nk}^{k}\)

Product family structure tree \(N_{k}\), of product series \(P^{k}\)

\(Ta_{Nk}^{k}\)

Product structure chain table \(N_{k}\), of product series \(P^{k}\)

\(Tr_{\mathrm{min}}\)

Minimum structure tree

\(L_{n}\)

Structure chain \(n, n\in N^{+}\)

\(f_{n}\)

The code of function \(n, n\in N^{+}\)

\(M_{n}^{i}\)

Product module n of product series \(P^{i}\)

\(PrM^{i}\)

The PrMs of product series \(P^{i}\)

\(FSM^{i}\)

The FSMs of product series \(P^{i}\)

\(SSM^{i}\)

The SSMs of product series \(P^{i}\)

\(F_{i}\)

The function code of product module \(M_{i}\)

S / F / P

The structure/function/process parameter of a product module

Notes

Acknowledgements

Funding was provided by National Natural Science Foundation of China (Grant no. 51275362), National Science and Technology Major Projetcs (Grant no. 2014ZX04015021).

References

  1. André, S., Stolt, R., & Elgh, F. (2015). Introducing design descriptions on different levels of concretisation in a platform definition. In IFIPInternational conference on product lifecycle management (pp. 800–810). Springer International Publishing.Google Scholar
  2. Anzanello, M. J., & Fogliatto, F. S. (2011). Selecting the best clustering variables for grouping mass-customized products involving workers’ learning. International Journal of Production Economics, 130(2), 268–276.CrossRefGoogle Scholar
  3. Aoki, M., & Ando, H. (2003). The times of module the essence of the new industrial structure. Shanghai: Shanghai Far East Press.Google Scholar
  4. Bruun, H. P. L., Mortensen, N. H., & Harlou, U. (2013). PLM support for development of modular product families. In DS 75-4: Proceedings of the 19th international conference on engineering design (ICED13), design for harmonies, vol. 4: product, service and systems design, Seoul, Korea, 19–22 08 2013.Google Scholar
  5. Bruun, H. P. L., Mortensen, N. H., Harlou, U., et al. (2015). PLM system support for modular product development. Computers in Industry, 67, 97–111.CrossRefGoogle Scholar
  6. Choi, T. M. (2013). Optimal return service charging policy for a fashion mass customization program. Service Science, 5(1), 56–68.CrossRefGoogle Scholar
  7. Chowdhury, S., Maldonado, V., Tong, W., et al. (2016). New modular product-platform-planning approach to design macroscale reconfigurable unmanned aerial vehicles. Journal of Aircraft, 53(2), 309–322.CrossRefGoogle Scholar
  8. Duray, R., Ward, P. T., Milligan, G. W., et al. (2000). Approaches to mass customization: Configurations and empirical validation. Journal of Operations Management, 18(6), 605–625.CrossRefGoogle Scholar
  9. Ebert, C. (2013). Improving engineering efficiency with PLM/ALM. Software and Systems Modeling, 12(3), 443–449.CrossRefGoogle Scholar
  10. Fan, B. B., Qi, G., Hu, X., et al. (2015). A network methodology for structure-oriented modular product platform planning. Journal of Intelligent Manufacturing, 26(3), 553–570.CrossRefGoogle Scholar
  11. Ferre, M., Puig, A., & Tost, D. (2004). A fast hierarchical traversal strategy for multimodal visualization. In Electronic Imaging 2004 (pp. 1–13). International Society for Optics and Photonics.Google Scholar
  12. Gao, F., Xiao, G., & Simpson, T. W. (2009). Module-scale-based product platform planning. Research in Engineering Design, 20(2), 129–141.CrossRefGoogle Scholar
  13. Jensen, K. N., Nielsen, K., & Brunoe, T. D. (2015). Application of mass customization in the construction industry. In IFIP international conference on advances in production management systems (pp. 161–168). Springer International Publishing.Google Scholar
  14. Jiao, J. R., Zhang, L. L., Pokharel, S., & He, Z. (2007). Identifying generic routings for product families based on text mining and tree matching. Decision Support Systems, 43(3), 866–883.CrossRefGoogle Scholar
  15. Jiao, J., & Tseng, M. M. (1999). A methodology of developing product family architecture for mass customization. Journal of Intelligent Manufacturing, 10(1), 3–20.CrossRefGoogle Scholar
  16. Kintner, H. J. (2007). Representation and analysis challenges in design for part-reuse: An automotive case study. In ASME 2007 international design engineering technical conferences and computers and information in engineering conference (pp. 611–619). American Society of Mechanical Engineers.Google Scholar
  17. Lee, H. H., & Moon, H. (2015). Perceived risk of online apparel mass customization scale development and validation. Clothing and Textiles Research Journal, 33(2), 115–128.CrossRefGoogle Scholar
  18. Levandowski, C. E., Corin-Stig, D., Bergsjö, D., Forslund, A., Högman, U., Söderberg, R., et al. (2013a). An integrated approach to technology platform and product platform development. Concurrent Engineering, 21(1), 65–83.CrossRefGoogle Scholar
  19. Levandowski, C., Forslund, A., Söderberg, R., & Johannesson, H. (2013b). Using PLM and trade-off curves to support set-based convergence of product platforms. In 19th international conference on engineering design–ICED 2013.Google Scholar
  20. Li, Z., Pehlken, A., Qian, H., & Hong, Z. (2016). A systematic adaptable platform architecture design methodology for early product development. Journal of Engineering Design, 27(1–3), 93–117.CrossRefGoogle Scholar
  21. Liu, W., Liu, Z. Y., & Tan, J. R. (2010). Construction of product modules based on process similarity. Journal of Computer-Aided Design and Computer Graphics, 22(10), 1647–1654. (in Chinese).Google Scholar
  22. Liu, X. Y., Huang, M. F., Liu, F. Y., & Deng, X. L. (2009). Research and realization of the product family structure tree based on complex network. Microelectronics and Computer, 26(11), 177–180.Google Scholar
  23. McIntosh, R. I., Matthews, J., Mullineux, G., & Medland, A. J. (2010). Late customisation: Issues of mass customisation in the food industry. International Journal of Production Research, 48(6), 1557–1574.CrossRefGoogle Scholar
  24. Meyer, M. H., & Lehnerd, A. P. (1997). The power of product platforms: Building value and cost leadership. Research Technology Management, 40(6), 526–529.Google Scholar
  25. Ming, X. G., Yan, J. Q., Lu, W. F., Ma, D. Z., & Song, B. (2007). Mass production of tooling product families via modular feature-based design to manufacturing collaboration in PLM. Journal of Intelligent Manufacturing, 18(1), 185–195.CrossRefGoogle Scholar
  26. Navarrete, I. A., & Guzmán, A. A. L. (2013). Reduction of product platform complexity by vectorial Euclidean algorithm. Journal of Mechanical Science and Technology, 27(11), 3371–3379.CrossRefGoogle Scholar
  27. Nelson, S. A., Parkinson, M. B., & Papalambros, P. Y. (2001). Multicriteria optimization in product platform design. Journal of Mechanical Design, 123(2), 199–2.CrossRefGoogle Scholar
  28. Ojamaa, A., Kotkas, V., Spichakova, M., & Penjam, J. (2013). Developing a lean mass customization based manufacturing. In 2013 IEEE 16th international conference on computational science and engineering (CSE) (PP. 28–33). IEEE.Google Scholar
  29. Ostrosi, E., Stjepandić, J., Fukuda, S., & Kurth, M. (2014, September). Modularity: New trends for product platform strategy support in concurrent engineering. In Proceedings of the 21st ISPE international conference on concurrent engineering (pp. 414–423).Google Scholar
  30. Pearl, J. (1986). Fusion, propagation, and structuring in belief networks. Artificial intelligence, 29(3), 241–288.CrossRefGoogle Scholar
  31. Pedersen, K., Messer, M., Allen, J. K., & Mistree, F. (2013). Hierarchical product platform design: A domain-independent approach. Ships and Offshore Structures, 8(3–4), 367–382.CrossRefGoogle Scholar
  32. Qu, T., Bin, S., Huang, G. Q., & Yang, H. D. (2011). Two-stage product platform development for mass customisation. International Journal of Production Research, 49(8), 2197–2219.CrossRefGoogle Scholar
  33. Sharafat, A. R., & Ma, O. R. (2006). Recursive contraction algorithm: A novel and efficient graph traversal method for scanning all minimal cut sets. Iranian Journal of Science and Technology, 30(B6), 749–761.Google Scholar
  34. Wang, H., & Chen, B. (2013). Intrusion detection system based on multi-strategy pruning algorithm of the decision tree. In Proceedings of 2013 IEEE international conference on grey systems and intelligent services (GSIS) (pp. 445–447). IEEE.Google Scholar
  35. Xu, Y., Chen, G., & Zheng, J. (2016). An integrated solution-KAGFM for mass customization in customer-oriented product design under cloud manufacturing environment. International Journal of Advanced Manufacturing Technology, 84(1–4), 85–101.Google Scholar
  36. Xu, Y., Chen, Y., Xu, Q., & Hou, L. (2004). Generalized modular design method for durable product customization. In Proceeding of the 11th world congress in mechanism and machine science.Google Scholar
  37. Zhang, L. L. (2015). A literature review on multitype platforming and framework for future research. International Journal of Production Economics, 168, 1–12.CrossRefGoogle Scholar
  38. Zhang, M., Li, G. X., Cao, J., Gong, J., & Wu, B. (2016). A bottom-up method for module-based product platform development through mapping, clustering and matching analysis. Journal of Central South University, 23(3), 623–635.CrossRefGoogle Scholar
  39. Zhang, W. L., Fan, Y. S., & Yin, C. W. (2006). Approach of product configuration based on product family genealogy. Computer Integrated Manufacturing Systems, 12(11), 1741–1746.Google Scholar
  40. Zhao, L. X., Jiang, P., Wang, X. Y., Ding, J. G., & Tan, R. H. (2007). A method of optimum product platform parameters planning. In 2007 IEEE international conference on industrial engineering and engineering management (pp. 382–386). IEEE.Google Scholar
  41. Zhou, F., Ji, Y., & Jiao, R. J. (2013). Affective and cognitive design for mass personalization: Status and prospect. Journal of Intelligent Manufacturing, 24(5), 1047–1069.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Qiuhua Zhang
    • 1
  • Weiping Peng
    • 1
  • Jin Lei
    • 1
    Email author
  • Junhao Dou
    • 1
  • Xiangyang Hu
    • 1
  • Rui Jiang
    • 1
  1. 1.School of Power and Mechanical EngineeringWuhan UniversityWuhanChina

Personalised recommendations