## 2 Proposed Smart Factory Methods and Methodology
### Overall Architecture and Data Models  
To address some of the challenges faced by SMEs, the EU-funded Smart Human Oriented Platform for Connected Factories (SHOP4 CF) project was created. SHOP4 CF aims to create a unique infrastructure for the convenient deployment of human-centric industrial applications. In the project, a team of twenty partners developed a comprehensive software platform containing a wide range of components that cover a broad spectrum of industrial requirements, especially in the context of flexible and data-rich manufacturing. SHOP4 CF aims to find the right balance between the cost-effective automation of repetitive tasks and the involvement of human workers in areas such as adaptability, creativity, and agility, where they create the greatest added value. Furthermore, the project pursues a highly connected factory model to exploit the benefits of all data generated within a factory. The SHOP4 CF approach builds on existing work, including the HORSE ([[http://horse-project.eu/](http://horse-project.eu/)]([http://horse-project.eu/](http://horse-project.eu/)) (accessed on 4 March 2022)) project and the L4 MS ([[http://www.l4](http://www.l4) ms.eu/]([http://www.l4](http://www.l4) ms.eu/) (accessed on 4 March 2022)) project on smart logistics for manufacturing. Initially, the HORSE consortium designed, developed, deployed, and tested the HORSE framework--a reference architecture for cyber-physical systems that integrate smart technologies and provide manufacturing operations management in hybrid-actors settings [29]. The framework is a modular architecture with clear subsystems and interfaces at several levels of aggregation, resulting from a structured, hierarchical system design based on theoretical principles and guidelines [30]. From a functional high-level perspective, it distinguishes between manufacturing activities taking place in a work cell and activities in a production area or even site (across work cells). This distinction is depicted with two levels, global and local. There is also a clear distinction of phases, one regarding design of manufacturing activities (e.g., modeling and parameterization) and one regarding executions of manufacturing activities (e.g., actual product manufacturing)--i.e., the design and execution phases. Following, the L4 MS project was a four-year project with the goal to create a one-stop shop for manufacturing SMEs to help them digitalize intra-factory logistics. This was achieved by Open Platform for Innovations in Logistics (OPIL) [31], an open Internet of Things (IoT) platform with different enablers and the common aim of simplifying the development of customized logistics solutions. The OPIL reference architecture consists of three layers: the IoT nodes layer (L1), which is the layer where software components interact with the physical world using well-established technologies (e.g., robot operating system (ROS)); the cyber-physical middleware layer (L2), which allows interoperability among components of the platform and with external ones; and the software systems layer (L3), which consists of software components developed specifically for the logistics sector. A similar approach was adopted in SHOP4 CF. The platform aspect of the architecture represents the organization, from the functional perspective, of the software and hardware necessary for the software components to be operational. Its top-level logical view is illustrated in Figure 3.  
The software layer consists of SHOP4 CF components, the middleware, containers (i.e., OS-level virtualization), and third-party information systems (i.e., external to SHOP4 CF, such as MES, as discussed in Section 2.4) which may exist on a shop floor. The hardware layer consists of servers. In addition, cyber-physical systems and IoT devices of a shop floor may belong to both layers.