This paper deals with a methodology for the implementation of cloud manufacturing (CM) architecture. CM is a current paradigm in which dynamically scalable and virtualized resources are provided to users as services over the Internet. CM is based on the concept of coud computing, which is essential in the Industry 4.0 trend. A CM architecture is employed to map users and providers of manufacturing resources. It reduces costs and development time during a product lifecycle. Some providers use different descriptions of their services, so we propose taking advantage of semantic web technologies such as ontologies to tackle this issue. Indeed, robust tools are proposed for mapping providers’ descriptions and user requests to find the most appropriate service. The ontology defines the stages of the product lifecycle as services. It also takes into account the features of coud computing (storage, computing capacity, etc.). The CM ontology will contribute to intelligent and automated service discovery. The proposed methodology is inspired by the ASDI framework (analysis–specification–design–implementation), which has already been used in the supply chain, healthcare and manufacturing domains. The aim of the new methodology is to propose an easy method of designing a library of components for a CM architecture. An example of the application of this methodology with a simulation model, based on the CloudSim software, is presented. The result can be used to help the industrial decision-makers who want to design CM architectures.

The manufacturing industry has been reshaping its operations using digital technologies for a smart production towards a more customized demand. Nevertheless, the flexibility to attend the production plan changes in real time is still challenging. Although the Internet of Services (IoS) has been addressed as a key element for Industry 4.0, there is still a lack of clarity about the IoS contribution for advanced manufacturing. Through a case study, the paper aims to validate the adherence of a theoretical model named Service-Oriented Manufacturing Architecture (SOMA) in two manufacturing companies that have been already engaged in Industry 4.0. As main results, it was concluded that IoS could suit in one case of Industry 4.0 flexible production process but not in a mass production one. Considering the scarcity of research that exemplifies the IoS contribution, the present paper brings an important assessment on a real manufacturing scenario.