Knowledge recommendation has become a trend to improve the efficiency of acquiring knowledge during product development. As such, coping with the challenge of constantly discovering new knowledge is critical for knowledge reuse. This article proposes a knowledge recommendation framework based on design tasks, to facilitate the capturing and sharing of knowledge in manufacturing firms. An ontology-based knowledge representation model is designed and developed to organize the knowledge resources and a vector space model-based knowledge recommendation model is built to hasten the knowledge reuse process. A case study demonstrates the effectiveness of the proposed method.
Ammar-KhodjaSPerryNBernardA (2008) Processing knowledge to support knowledge-based engineering systems specification. Concurrent Engineering16(1): 89–101.
2.
ChangXTerpennyJ (2009) Ontology-based data integration and decision support for product e-Design. Robotics and Computer-Integrated Manufacturing25(6): 863–870.
3.
ChhimPChinnamRBSadawiN (2019) Product design and manufacturing process based ontology for manufacturing knowledge reuse. Journal of Intelligent Manufacturing30(2): 905–916.
4.
ChoiKYooDKimG, et al. (2012) A hybrid online-product recommendation system: combining implicit rating-based collaborative filtering and sequential pattern analysis. Electronic Commerce Research and Applications11(4): 309–317.
5.
CostaRLimaCSarraipaJ, et al. (2016) Facilitating knowledge sharing and reuse in building and construction domain: an ontology-based approach. Journal of Intelligent Manufacturing27(1): 263–282.
6.
FuYWangHTianG, et al. (2019) Two-agent stochastic flow shop deteriorating scheduling via a hybrid multi-objective evolutionary algorithm. Journal of Intelligent Manufacturing30(5): 2257–2272.
7.
GaoJNeeAY (2018) An overview of manufacturing knowledge sharing in the product development process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture232(13): 2253–2263.
8.
GaoLDaiKGaoL, et al. (2019) Expert knowledge recommendation systems based on conceptual similarity and space mapping. Expert Systems with Applications136: 242–251.
9.
HuangC-BGongS-J (2008) Employing rough set theory to alleviate the sparsity issue in recommender system. In Proceedings of the 2008 international conference on machine learning and cybernetics, Kunming, China, 12–15July2008. New York: IEEE.
10.
HuangZLuXDuanH, et al. (2012) Collaboration-based medical knowledge recommendation. Artificial Intelligence in Medicine55(1): 13–24.
11.
LeeCKH (2019) A knowledge-based product development system in the chemical industry. Journal of Intelligent Manufacturing30(3): 1371–1386.
12.
LiangT-P (2008) Recommendation systems for decision support: an editorial introduction. Decision Support Systems45(3): 385–386.
13.
LiuTWangHHeY (2016) Intelligent knowledge recommending approach for new product development based on workflow context matching. Concurrent Engineering24(4): 318–329.
14.
McSherryFNajorkM (2008) Computing information retrieval performance measures efficiently in the presence of tied scores. In: Proceedings of the European conference on information retrieval, Glasgow, 30 March–3 April 2008.
15.
MoonSKSimpsonTWKumaraSR (2009) An agent-based recommender system for developing customized families of products. Journal of Intelligent Manufacturing20(6): 649.
16.
OsadchiyTPoliakovIOlivierP, et al. (2019) Recommender system based on pairwise association rules. Expert Systems with Applications115: 535–542.
17.
ParkDHKimHKChoiIY, et al. (2012) A literature review and classification of recommender systems research. Expert Systems with Applications39(11): 10059–10072.
18.
PrasadB (2007) A knowledge-based product recommendation system for e-commerce. International Journal of Intelligent Information and Database Systems1(1): 18–36.
19.
PrasadB (2014) Knowledge-based enterprising (KBE) strategy for lean product development (LPD). In: Proceedings of the 27th international conference on CAD/CAM, robotics and factories of the future conference, London, 22–24July 2014.
20.
PrasadB (2016) Lean, integrated and connected framework for developing smart products. In: BatallaJMMastorakisGMavromoustakisCX, et al. (eds) Beyond the Internet of Things: Everything Interconnected (DRAFT). Cham: Springer, pp. 1–25.
21.
SongJZhanHYuJ, et al. (2017) Enterprise knowledge recommendation approach based on context-aware of time-sequence relationship. Procedia Computer Science107: 285–290.
22.
SuJHuangYLvG, et al. (2016) A framework research of power grid knowledge recommendation and situation reasoning based on cloud computing and CEP. In: Proceedings of the 2016 IEEE 3rd international conference on cyber security and cloud computing, Beijing, China, 25–27June2016. New York: IEEE.
23.
TarusJKNiuZMustafaG (2018) Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning. Artificial Intelligence Review50: 21–48.
24.
VermaCHartMBhatkarS, et al. (2016) Improving scalability of personalized recommendation systems for enterprise knowledge workers. IEEE Access4: 204–215.
25.
WanSLiDGaoJ, et al. (2017) Process and knowledge management in a collaborative maintenance planning system for high value machine tools. Computers in Industry84: 14–24.
26.
WangJWWangHFDingJL, et al. (2016) On domain modelling of the service system with its application to enterprise information systems. Enterprise Information Systems10(1): 1–16.
27.
WuZLiaoJSongW, et al. (2017) Product lifecycle-oriented knowledge services: status review, framework, and technology trends. Concurrent Engineering25(1): 81–92.
28.
WuZMingXHeL, et al. (2014) Knowledge integration and sharing for complex product development. International Journal of Production Research52(21): 6296–6313.
29.
YanYYangNHaoJ, et al. (2016) A context modeling method of knowledge recommendation for designers. In: Proceedings of the 2016 international conference on information system and artificial intelligence, Hong Kong, China, 24–26June2016. New York: IEEE.
30.
ZammitJGaoJEvansR, et al. (2018) A knowledge capturing and sharing framework for improving the testing processes in global product development using storytelling and video sharing. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture232(13): 2286–2296.
31.
ZhangCZhouGLuQ, et al. (2017) Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development. International Journal of Production Research55(23): 7187–7203.
32.
ZhangXHouXChenX, et al. (2013) Ontology-based semantic retrieval for engineering domain knowledge. Neurocomputing116: 382–391.
33.
ZhenLHuangGQJiangZ (2009) Recommender system based on workflow. Decision Support Systems48(1): 237–245.
34.
ZhenLJiangZSongH (2010) Distributed recommender for peer-to-peer knowledge sharing. Information Sciences180(18): 3546–3561.
35.
ZhengCBricogneMLe DuigouJ, et al. (2018) Knowledge-based engineering for multidisciplinary systems: integrated design based on interface model. Concurrent Engineering26(2): 157–170.
36.
ZhouK-QMoL-PJinJ, et al. (2019) An equivalent generating algorithm to model fuzzy Petri net for knowledge-based system. Journal of Intelligent Manufacturing30(4): 1831–1842.
37.
ZouariATollenaereMBen BachaH, et al. (2015) Domain knowledge versioning and aggregation mechanisms in product design processes. Concurrent Engineering23(4): 296–307.
