A Hybrid Knowledge-Based Recommender for Product-Service Systems Mass Customization

Manufacturers today compete to offer not only products, but products accompanied by services, which are referred as product-service systems (PSSs). PSS mass customization is defined the production of and services meet needs individual customers with near-mass-production efficiency. In context environment, overwhelmed a plethora previously customized variants. As result, finding variant that precisely aligned customer’s cognitive task will be unable manage effectively. this paper, we propose hybrid knowledge-based recommender system assists in selecting variants from wide range available ones. The (RS) utilizes ontologies for capturing customer requirements, well production-related knowledge. RS follows recommendation approach, problem encoded constraint satisfaction (CSP), filter out do satisfy needs, then uses weighted utility function rank remaining Finally, offers list ranked can scrutinized customer. study, proposed approach was applied real-life large-scale case study domain laser machines. To ensure applicability RS, web-based prototype has been developed, realizing all modules RS.