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Despite its potential, bidirectional data exchange remains underexplored. Most practical applications are limited to unidirectional data collection, known as a \u2019Digital Shadow\u2019 (DS) of the asset. Additionally, existing implementations typically focus on a single asset, which hinders interoperability, a critical requirement for smart manufacturing ecosystems. This study bridges these gaps by developing an AAS system that enables real-time monitoring and control across multiple assets through seamless communication, coordination, and orchestration. This research demonstrates and validates the capabilities of the AAS using three types of assets: a Mobile Industrial Robot (MiR-250), two KUKA KR4 R600 robots, and a KUKA KR1000 Titan robot. The implemented AAS framework retrieves data from these assets to monitor critical parameters while issuing control commands based on specific data conditions. The approach enables data exchange and coordinated interaction among the digital representations of assets (i.e., the AASs), effectively facilitating communication among the physical assets in interconnected, intelligent manufacturing systems. This research advances the role of AAS in achieving real-time communication and coordination within and between assets, addressing the persistent challenge of interoperability in multi-asset smart manufacturing environments. Our approach overcomes the limitations of unidirectional single-asset AAS implementations, paving the way for scalable, standardised, and autonomous Industry 4.0 ecosystems.<\/jats:p>","DOI":"10.1007\/s00170-025-17178-z","type":"journal-article","created":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T14:57:23Z","timestamp":1766329043000},"page":"1549-1566","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Facilitating interoperability in manufacturing systems using digital twins: a multi-asset AAS system"],"prefix":"10.1007","volume":"146","author":[{"given":"Basem","family":"Elshafei","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jack C.","family":"Chaplin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Sanderson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Svetan","family":"Ratchev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,21]]},"reference":[{"key":"17178_CR1","doi-asserted-by":"publisher","unstructured":"Otto B, Kleinert T (2022) A flow graph based approach for controlled generation of aas digital twin instances for the verification of compliance check tools. 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