The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs and growth. HCAI presents new objectives that were unreachable by either humans or machines alone, but this also comes with a new set of challenges. Our proposed method accomplishes this through the knowlEdge architecture, which enables human operators to implement AI solutions using a zero-touch framework. It relies on containerized AI model training and execution, supported by a robust data pipeline and rounded off with human feedback and evaluation interfaces. The result is a platform built from a number of components, spanning all major areas of the AI lifecycle. We outline both the architectural concepts and implementation guidelines and explain how they advance HCAI systems and Industry 5.0. In this article, we address the problems we encountered while implementing the ideas within the edge-to-cloud continuum. Further improvements to our approach may enhance the use of AI in Industry 5.0 and strengthen trust in AI systems.

Digital twin technology has become a driving force in the transformation of the manufacturing industry, playing a crucial role in optimizing processes, increasing productivity, and enhancing product quality. A digital twin (DT) is a digital representation of a physical entity or process, modeled to improve decision-making in a safe and cost-efficient environment. Digital twins (DTs) cover a range of problems in different domains at different phases in the lifecycle of a product or process. DTs have gained momentum due to their seamless integration with technologies such as IoT, machine learning algorithms, and analytics solutions. DTs can have different scopes in the manufacturing domain, including process level, system level, asset level, and component level. This work presents the knowlEdge Digital Twin Framework (DTF), a toolkit that comprises a set of tools to create specific instances of DTs in the manufacturing process. This chapter explains how the DTF relates to other standards, such as ISO 23247. This chapter also presents the implementation done for a dairy company.

This paper presents the Virtual Open Operating System (vf-OS) Input / Output (IO) Toolkit Generator, which is a design tool to develop vf-OS IO components that interact with all kinds of manufacturing assets, either physical devices like Program Logic Controllers (PLCs), software applications like Enterprise Resource Planning Systems (ERPs) or legacy file formats like STEP. The vf-OS IO Toolkit Generator is based on software scaffolding, a code generation technique that allows a developer to create a working component to interact with a manufacturing asset from the vf-OS Platform without writing a line of code. As described in this paper, software scaffolding not only simplifies the development of interoperability components, but it also fosters system security and platform integration automation. Another contribution of this paper is to propose possible integrations between the IO Toolkit Generator and the vf-OS Security Command Centre in charge of platform security. Additionally, this paper describes how the concept can be extended to address other digital manufacturing platforms like Fi-Ware.