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Cloud Computing is revolutionizing smart manufacturing by offering on-demand and scalable computer systems that facilitate plant data analysis and operational efficiency optimization. DevOps is a methodology, widely used for developing Cloud Computing systems, that streamlines software development by improving its integration, delivery, and deployment. Although cloud application designers within a DevOps team are assumed to have development and operational knowledge, this does not fall within the skills of experts that design analytics applications of plant data. The deployment environment is also relevant since, as such applications are often hosted in the Fog, the proliferation of application components may hinder their composition and validation. This work is aimed at embracing the Platform Engineering approach to provide a tailored toolkit that guides the design and development of OpenFog compliant applications for the experts in the Smart Manufacturing domain. The platform uses Model Driven Engineering techniques and a flow-based visual editor to allow application designers to graphically compose applications from components previously delivered by component developers, abstracting them from the underlying technologies. As a result, containerized applications, ready to be deployed and run by a container orchestrator, are obtained. The feasibility of the proposal is proved through an industrial case study.

The fourth industrial revolution paradigm places value on the management of information related to the manufacturing process. Reference Architectural Model for Industrie 4.0 (RAMI 4.0), proposed by Plattform Industrie 4.0 (I4.0), provides a starting point for the development of I4.0 systems, based on: (1) international standards organized in a cubic model; (2) a set of key concepts to define the system participants, called I4.0 components; and (3) a list of infrastructure services required to manage I4.0 components and support them in the execution of manufacturing applications. However, the terms in which RAMI 4.0 is stated are generic and neutral from a technological point of view, without actually providing support for the practical development of concrete management platforms (I4.0 Platforms). This work contributes an I4.0 platform for the manufacturing domain that offers the infrastructure services required to manage an I4.0 system. The objective is to bring Industry 4.0 closer to companies, bridging the existing gap by providing a platform aligned with RAMI 4.0 which also offers tools and resources to facilitate the development of I4.0 components. To that end, this I4.0 platform is based on industrial agents, which have an inherent ability to negotiate and cooperate with each other and address the integration of assets. The applicability of the proposed I4.0 platform is evaluated by means of a testing scenario.

Although the digital factory (DF) concept has raised high expectations since its inception, it is still missing industrial impact. One of the problems attributed to this issue is the lack of education curricula for enhancing the related digital competences of the future professionals. Higher education institutions, as major stakeholders in education, should introduce the new technologies for DF in practical courses. However, it is difficult to deal with the complexity of those technologies in a time-limited environment such us a bachelor or a master course. Instead of providing complete knowledge, this paper proposes to focus on the methodological aspects that allow students to acquire the skills needed to handle those technologies. Specifically, this paper illustrates this approach for teaching virtual commissioning (VC) within the automation learning process. The goal is to show the students how to use powerful industrial tools for performing VC through a set of methodological steps that help students manage the complexity of the VC process regardless of the specific tools used for it.

Although the digital factory (DF) concept has raised high expectations since its inception, it is still missing industrial impact. One of the problems attributed to this issue is the lack of education curricula for enhancing the related digital competences of the future professionals. Higher education institutions, as major stakeholders in education, should introduce the new technologies for DF in practical courses. However, it is difficult to deal with the complexity of those technologies in a time-limited environment such us a bachelor or a master course. Instead of providing complete knowledge, this paper proposes to focus on the methodological aspects that allow students to acquire the skills needed to handle those technologies. Specifically, this paper illustrates this approach for teaching virtual commissioning (VC) within the automation learning process. The goal is to show the students how to use powerful industrial tools for performing VC through a set of methodological steps that help students manage the complexity of the VC process regardless of the specific tools used for it.

Although the digital factory (DF) concept has raised high expectations since its inception, it is still missing industrial impact. One of the problems attributed to this issue is the lack of education curricula for enhancing the related digital competences of the future professionals. Higher education institutions, as major stakeholders in education, should introduce the new technologies for DF in practical courses. However, it is difficult to deal with the complexity of those technologies in a time-limited environment such us a bachelor or a master course. Instead of providing complete knowledge, this paper proposes to focus on the methodological aspects that allow students to acquire the skills needed to handle those technologies. Specifically, this paper illustrates this approach for teaching virtual commissioning (VC) within the automation learning process. The goal is to show the students how to use powerful industrial tools for performing VC through a set of methodological steps that help students manage the complexity of the VC process regardless of the specific tools used for it.