**4. Conclusions**

In basic applications QFD uses human knowledge. The presented approach is focused on developing a QFD-KB knowledge base, which is able to support human decisions related to product configuration. The presented algorithm joins methods of knowledge representation and supports decisions related to identifying and assessing product configuration items, such as components, modules and parts. In the presented QFD-KB, attributes analyzed by customer and producer are related to one another with the QFD matrix.

**References**

2005

2003. pp. 809-821

[1] Jiao J, Ma Q, Tseng MM. Towards High Value-Added Products and Services: Mass Customisation and Beyond. Vol. 23. Amsterdam: Elsevier, Technovation, The International Journal of Technological Innovation, Entrepreneurship and Technology Management;

Configuration of a Customized Product http://dx.doi.org/10.5772/intechopen.79523 69

[2] Rong YK. Setup planning and tolerance analysis. In: Wang L, Shen W, editors. Process Planning and Scheduling for Distributed Manufacturing. Springer Series in Advanced

[3] Saaksvuori A, Immonen A. Product Lifecycle Management. Berlin Heidelberg: Springer;

[4] Ameri F, Dutta D. Product Lifecycle Management Needs, Concepts and Components.

[5] Liu W, Zeng Y. Conceptual Modeling of design chain management towards product lifecycle management. In: Chou SY, Trappey A, Pokojski J, Smith S, editors. Global Perspective for Competitive Enterprise, Economy and Ecology. Advanced Concurrent

[6] Jinsong Z, Qifu W, Li W, Yifang Z. Configuration-oriented product modelling and knowledge management or made-to-order manufacturing enterprises. The International

[7] Hu SJ, Ko J, Weyand L, ElMaraghy HA, Lien TK, Koren Y, Chryssolouris G, Nasr N, Shpitalni M. Assembly system design and operations for product variety. CIRP Annals

[8] Sanchez R. Building real modularity competence in automotive design, development, production, and after-service. International Journal of Automotive Technology and

[9] Stone R, Wood K, Crawford R. A heuristic method for identifying modules for product

[10] Kubota F, Hsuan J, Cauchick-Miguel P. Theoretical analysis of the relationships between modularity in design and modularity in production. International Journal of Advanced

[11] Koren Y, Hu S, Gu P, Shpitalni M. Open-architecture products. CIRP Annals-Manu-

[12] Ma H, Peng Q, Zhang J, Gu P. Assembly sequence planning for open-architecture products. International Journal of Advanced Manufacturing Technology. 2018;**94**:1551-1564

[13] Su Y. Product family Modeling and optimization driven by customer requirements. In: Hinduja S, Li L, editors. Proceedings of the 36th International MATADOR Conference.

Manufacturing. London: Springer; 2007. pp. 137-166

Ann Arbor: University of Michigan; 2004

Engineering. London: Springer; 2009. pp. 137-148

Manufacturing Technology. 2011;**60**:715-733

architectures. Design Studies. 2000;**21**:5-31

Manufacturing Technology. 2017;**89**:1943-1958

facturing Technology. 2013;**62**(2):719-729

London: Springer; 2010

Management. 2013;**13**:204-236

Journal of Advanced Manufacturing Technology. 2005;**25**:41-52

Methods of knowledge representation, such as procedures, rules, ANN and CBR are useful in the presented QFD-KB. The presented approach uses advantages and avoids disadvantages of different methods of knowledge representation. Selection of the proper knowledge representation method determines the effectiveness of QFD-KB.

Integration of the knowledge related to customer requirements, product structure and the manufacturing process helps to assess product characteristics in make-to-order product offer preparation.

The proposed algorithm of product configuration uses the QFD method and performs comparison and evaluation of configuration item variants, as well as missing data estimation related to the production process of product redesign.

Product configuration requires knowledge related to, among others, product structure, manufacturing process and potential failure problems.

Product configuration efforts are focused on the following categories:


The decision process regarding product configuration, which is focused on compatibility between customer requirements and functional and physical product features, can be supported with the use of QFD-KB for product configuration.
