Abstract
New product development is often promoted and managed by enterprises in the form of projects. A new product development project involves a knowledge-intensive process and a series of complex team-working procedures. Therefore, enterprises can establish new product development process or model through practical experience of projects, which can not only serve as the basis for continuous learning and progress of R&D organizations, but also serve as the benchmark for the management of new product development activities. In this study, Construction Ontology-based NPD Process Recommendation Smart System (ONPS) consistent knowledge base architecture. ONPS assist the company, department quickly build and easy to maintain the body of knowledge; at the same time build a graphical user interface for presenting Find knowledge in knowledge, enhance the efficiency of reuse of knowledge. And with three desktop computers as a case study; the original will-depth interviews and expert designers to take advantage of this study ONPS to build ontologies validation framework; and requested the original expert designers use SUS ease of use in the assessment of verification graphical user interface. The results showed that ONPS is feasible, the corporate sector can help quickly build a structure consistent body of knowledge, reasoning ability and possess the knowledge, easy to maintain, but also have a high degree of scalability.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bangor, A., Kortum, P., Miller, J.: Determining what individual SUS scores mean: adding an adjective rating scale. J. Usability Stud. 4(3), 114–123 (2009)
Bell, S.T.: Deep-level composition variables as predictors of team performance: a meta-analysis. J. Appl. Psychol. 92(3), 595 (2007)
Cheng, C.C., Chen, J.-S.: Breakthrough innovation: the roles of dynamic innovation capabilities and open innovation activities. J. Bus. Ind. Market. 28(5), 444–454 (2013)
Clarke, P., O’Connor, R.V.: The situational factors that affect the software development process: towards a comprehensive reference framework. Inf. Softw. Technol. 54(5), 433–447 (2012)
Compton, M., et al.: The SSN ontology of the W3C semantic sensor network incubator group. Web Semant.: Sci. Serv. Agents World Wide Web 17, 25–32 (2012)
Demirors, O., Demirors, E., Tarhan, A., Yildiz, A.: Tailoring ISO/IEC 12207 for instructional software development. Paper presented at the Proceedings of the 26th Euromicro Conference. EUROMICRO 2000. Informatics: Inventing the Future (2000)
Díaz, M., Martín, C., Rubio, B.: State-of-the-art, challenges, and open issues in the integration of Internet of Things and cloud computing. J. Netw. Comput. Appl. 67, 99–117 (2016)
Ginsberg, M., Quinn, L.: Process Tailoring and the Software Capability Maturity Model: Technical Report CMU/SEI-94-TR-024. Software Engineering Institute. Carnegie Mellon University, Pittsburgh, Pennsylvania (1995)
Glimm, B., Horrocks, I., Motik, B., Stoilos, G., Wang, Z.: HermiT: an OWL 2 reasoner. J. Autom. Reason. 53(3), 245–269 (2014)
Hollauer, C., Lindemann, U.: Design process tailoring: a review and perspective on the literature. Paper Presented at the International Conference on Research into Design (2017)
Hsiao, C., Ruffino, M., Malak, R., Tumer, I.Y., Doolen, T.: Discovering taxonomic structure in design archives with application to risk-mitigating actions in a large engineering organisation. J. Eng. Des. 27(1–3), 146–169 (2016)
Kaur, R., Sengupta, J.: Software process models and analysis on failure of software development projects. arXiv preprint arXiv:1306.1068 (2013)
Lai, C.-Y., Liou, W.-C.: A service-oriented architecture for constructing ontology-based learning objects repository. Paper Presented at the Multimedia Workshops, 2007. ISMW 2007. Ninth IEEE International Symposium on (2007)
Lorenz, R.D.: The flushing of ligeia: composition variations across Titan’s seas in a simple hydrological model. Geophys. Res. Lett. 41(16), 5764–5770 (2014)
Lukyanenko, R., Parsons, J., Wiersma, Y., Wachinger, G., Huber, B., Meldt, R.: Representing crowd knowledge: guidelines for conceptual modeling of user-generated content. J. Assoc. Inf. Syst. 18(4), 2 (2017)
Martínez-Ruiz, T., Münch, J., García, F., Piattini, M.: Requirements and constructors for tailoring software processes: a systematic literature review. Softw. Qual. J. 20(1), 229–260 (2012)
Mathieu, J.E., Hollenbeck, J.R., van Knippenberg, D., Ilgen, D.R.: A century of work teams in the journal of applied psychology. J. Appl. Psychol. 102(3), 452 (2017)
McGuinness, D.L., Van Harmelen, F.: OWL web ontology language overview. W3C Recommendation 10(10), 2004 (2004)
Noy, N.F., Sintek, M., Decker, S., Crubézy, M., Fergerson, R.W., Musen, M.A.: Creating semantic web contents with protege-2000. IEEE Intell. Syst. 16(2), 60–71 (2001)
Park, S.-H., Bae, D.-H.: Tailoring a large-sized software process using process slicing and case-based reasoning technique. IET Softw. 7(1), 47–55 (2013)
Park, S., Na, H., Park, S., Sugumaran, V.: A semi-automated filtering technique for software process tailoring using neural network. Exp. Syst. Appl. 30(2), 179–189 (2006)
Samuel, B. M., Watkins, L., Ehle, A., Khatri, V.: Customizing the representation capabilities of process models: understanding the effects of perceived modeling impediments. IEEE Trans. Softw. Eng. 41(1), 19–39 (2015)
Simperl, E., Bürger, T., Hangl, S., Wörgl, S., Popov, I.: ONTOCOM: a reliable cost estimation method for ontology development projects. Web Semant.: Sci. Serv. Agents World Wide Web 16, 1–16 (2012)
Ulrich, K., Eppinger, S.: Product Design and Development. McGraw-Hill Education, New York (2015)
Williams, L., Cockburn, A.: Agile software development: it’s about feedback and change. IEEE Comput. 36(6), 39–43 (2003)
Xu, P., Ramesh, B.: Using process tailoring to manage software development challenges. IT Prof. 10(4), 39–45 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Hsu, Y., Chaing, YH. (2021). The Strategic Advantages of Artificial Intelligence System for Product Design Teams with Diverse Cross-Domain Knowledge. In: Rau, PL.P. (eds) Cross-Cultural Design. Experience and Product Design Across Cultures. HCII 2021. Lecture Notes in Computer Science(), vol 12771. Springer, Cham. https://doi.org/10.1007/978-3-030-77074-7_31
Download citation
DOI: https://doi.org/10.1007/978-3-030-77074-7_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77073-0
Online ISBN: 978-3-030-77074-7
eBook Packages: Computer ScienceComputer Science (R0)