“Follow The Twin” Chal­lenge at SPS 2023

• Effi­cient Data Exchange: One of the primary purposes of ensuring inter­op­er­ability between the Digital Twin and AAS is to facil­i­tate a stan­dard­ized and effi­cient exchange of data across different stages of produc­tion. This stan­dard-confor­mant data exchange is partic­u­larly bene­fi­cial in engi­neering sectors, where various stake­holders like manu­fac­turers, suppliers, and customers are involved. Through the defined AAS stan­dard, digital twins can be exchanged effi­ciently among different part­ners, thereby enhancing the process of engi­neering.
• Industry 4.0 Align­ment: The inter­op­er­ability aligns well with the objec­tives of Industry 4.0, which advo­cates for enhanced connec­tivity, stan­dard­iza­tion, and data sharing among indus­trial assets. This inter­op­er­ability is described as a pillar of the mission state­ment for Industry 4.0. By estab­lishing a stan­dard­ized digital repre­sen­ta­tion (Digital Twin) via AAS, Industry 4.0’s goals of creating an inter­op­er­able, sustain­able, and sover­eign indus­trial ecosystem are advanced.
• Manu­fac­turer Inter­op­er­ability: The AAS is instru­mental in achieving manu­fac­turer inter­op­er­ability, meaning it enables the exchange of data between assets from different manu­fac­turers. This is a signif­i­cant advan­tage for manu­fac­turers, suppliers, customers, and facto­ries, as it simpli­fies coop­er­a­tion and promotes a stan­dard­ized repre­sen­ta­tion of data. The inter­op­er­ability thus facil­i­tates better coor­di­na­tion among different stake­holders involved in the produc­tion ecosystem .
• Support for Autonomous Systems and AI: The Asset Admin­is­tra­tion Shell not only supports the exchange of data but also lays a digital and inter­op­er­able foun­da­tion for autonomous systems and Arti­fi­cial Intel­li­gence (AI). It does this by struc­turing data in a way that can be stan­dard­ized, found, modeled, retrieved, and forwarded, covering the entire life­cycle of prod­ucts, devices, machines, and facil­i­ties. This struc­tured data handling is essen­tial for real­izing complex solu­tions and contin­uous value chains, which are core to the func­tioning of autonomous systems and AI in an indus­trial setup
• Imple­men­ta­tion Chal­lenges: The scope of imple­men­ta­tion possi­bil­i­ties, use cases, and complexity in the produc­tion envi­ron­ment can be chal­lenging, espe­cially for small and medium-sized enter­prises (SMEs), but also for larger compa­nies. The inter­op­er­ability between the Digital Twin and AAS helps in navi­gating these chal­lenges by providing a struc­tured approach towards imple­menting digital twins in a norm-compliant digital produc­tion 

Inter­op­er­ability between the Digital Twin and Asset Admin­is­tra­tion Shell is crucial for stan­dard­izing data exchange, aligning with Industry 4.0 objec­tives, facil­i­tating manu­fac­turer inter­op­er­ability, supporting autonomous systems and AI, and navi­gating imple­men­ta­tion chal­lenges in the produc­tion envi­ron­ment.

The plat­form allows compa­nies and consumers to partic­i­pate in a data ecosystem in an easy and versa­tile manner. All infor­ma­tion, such as needed for the digital product pass­port, can be provided along the the life­cycle of a product. Changes to product infor­ma­tion can instantly be made avail­able with events and push capa­bil­i­ties. Through this the digital twin can act as a single source of truth about product specifics in cross-company busi­ness scenarios.

Inter­faces for machine read and write access to the AAS, compliant with API spec­i­fi­ca­tion V3.0 of IDTA.

Multi-tenancy with secure isola­tion of client data.

Event mech­a­nism, for auto­matic reac­tion to changes in the data and push mech­a­nism to publish new digital twins.

Collec­tion and provi­sion of access and usage data.

Submodels: Digital Name­plate / Handover Docu­men­ta­tion / Tech­nical Data / Contact Infor­ma­tion / Hier­ar­chical Struc­ture for BoM / Product Carbon Foot­print