The increasing dynamics and complexity of today’s manufacturing environments require greater flexibility and resilience to meet the demands of producing multi-variant products, including batch size one, with minimal additional effort. The Capability, Service and Skill Model provides an answer to this problem by decoupling processes and the resources used. However, especially small and medium-sized enterprises face the challenge of systematically modeling their machines and systems in terms of capabilities and skills, as the required knowledge is often not available in a structured form and is often tied to individual key personnel. To ensure a consistent and practical description of capabilities, a method based on historical data is proposed to help companies integrate their manufacturing resources into a networked system of manufacturing service providers. On this basis, historical manufacturing features are systematically examined to evaluate the potential to use them to determine capabilities.

Recent developments in Manufacturing-as-a-Service aim to create more flexible and resilient manufacturing networks by enabling the dynamic allocation of manufacturing tasks across company boundaries. This paper presents a pilot implementation of a shared manufacturing network based on the Capability, Skill and Service model and the Asset Administration Shell. The proposed approach supports semantically rich, platform-independent service descriptions and employs standardized negotiation logic based on the Industrie 4.0 language. A multi-partner prototype demonstrates how service requesters and providers – modeled as proactive AAS instances – can autonomously negotiate manufacturing services using capability and offer submodels. The implementation comprises cross-partner negotiation and feasibility checks, skill-based execution, and dynamic scheduling are handled individually at the partner level. Our findings highlight the benefits and challenges of integrating capabilities, skills and services with Asset Administration Shells standards in shared manufacturing scenarios and provide a foundation for future extensions toward more expressive interaction protocols and scalable, federated manufacturing ecosystems.

In the research area of capabilities and skills, the standardization of terms and models is progressing in working groups of Plattform Industrie 4.0 and Industrial Digital Twin Association. At the same time, there is an increasing amount of publications that use capability models for purposes such as automated selection of capabilities or planning of sequences. However, there is currently no concept and formal description of effects generated by resources when acting on products. Having such a formal effect definition is needed to express both required effects as well as effects achieved by capabilities in order to compare requirements with possible solutions to a desired production step in an automated manner. This article introduces a formalism that can be used to define effects in the context of capabilities. An effect is seen as the change between an initial and a target state, which can both be specified using properties. The formalism is used to express effects in three different manufacturing application examples. Furthermore, an implementation of the formalism using the Web Ontology Language is provided. This ontology is used to model effects in a machine-interpretable way and to automatically compare effects for compatibility.

Flexibility, agility and resilience of value chains are becoming increasingly important. One possible approach to achieving these goals could be the paradigm of cloud manufacturing, especially the shared production scenario, where a federation of trusted partners dynamically share manufacturing capabilities, capacity, and services over digital interfaces throughout the product lifecycle. This includes an automated bidding procedure in a cross-enterprise network. The Capability, Service, Skill (CSS) model provides a common terminology for Industry 4.0 applications. The paper focuses on enabling a shared production based on the CSS model through the implementation of the Asset Administration Shell (AAS), the use of the Industry 4.0 Language (I4.0L) and Gaia-X. It shows what a centralized approach to shared production using these technologies could look like. The scenario of a negotiation process to find suitable manufacturers for a customized product is described, and the different concepts are assigned to the elaborated steps of the I4.0L bidding procedure. In addition, the required AAS and its Submodels are designed for each step of the bidding procedure. Based on the results, the necessary standardization needs are outlined.