Lotfısadıgh, BahramSadigh, Bahram LotfiUnver, Hakki OzgurKılıç, Sadık EnginNikghadam, ShahrzadDogdu, ErdoganOzbayoglu, A. MuratKilic, S. EnginManufacturing Engineering2024-07-052024-07-05201780951-192X1362-305210.1080/0951192X.2016.11458112-s2.0-84958776288https://doi.org/10.1080/0951192X.2016.1145811https://hdl.handle.net/20.500.14411/593Sadigh, Bahram Lotfi/0000-0002-3027-3734; Ozbayoglu, Ahmet/0000-0001-7998-5735; UNVER, HAKKI OZGUR/0000-0002-4632-3505; Dogdu, Erdogan/0000-0001-5987-0164New advancements in computers and information technologies have yielded novel ideas to create more effective virtual collaboration platforms for multiple enterprises. Virtual enterprise (VE) is a collaboration model between multiple independent business partners in a value chain and is particularly suited to small and medium-sized enterprises (SMEs). The most challenging problem in implementing VE systems is ineffcient and inFLexible data storage and management techniques for VE systems. In this research, an ontology-based multi-agent virtual enterprise (OMAVE) system is proposed to help SMEs shift from the classical trend of manufacturing part pieces to producing high-value-added, high-tech, innovative products. OMAVE targets improvement in the FLexibility of VE business processes in order to enhance integration with available enterprise resource planning (ERP) systems. The architecture of OMAVE supports the requisite FLexibility and enhances the reusability of the data and knowledge created in a VE system. In this article, a detailed description of system features along with the rule-based reasoning and decision support capabilities of OMAVE system are presented. To test and verify the functionality and operation of this system, a sample product was manufactured using OMAVE applications and tools with the contribution of three SMEs.eninfo:eu-repo/semantics/closedAccessvirtual enterprisedomain ontologymulti-agent systemsOWLsemantic reasoningAn ontology-based multi-agent virtual enterprise system (OMAVE): part 1: domain model<bold>l</bold>ing and rule managementArticleQ2Q1302-3320343WOS:000390883300007