Digital twin-based cyber physical production system architectural framework for personalized production

A problem-solving ontology for human-centered cyber physical production systems

When cyber-physical systems (CPS) are connected to perform smart manufacturing, we have a cyber-physical production system (CPPS). In such systems, CPS collaborate in an intelligent way to obtain and maintain the optimum of the manufacturing process, handle disturbances and adapt to changing conditions. This work, based on a systematic literature review, shows current trends in cyber-physical production systems with a special focus on the role of connectivity and control systems in production. We are looking for the enablers of CPPS focusing on the current evolution of control systems in the smart factory of the future. As a result, a conceptual framework as well as a CPPS control system architecture for the introduction and organisation of enablers for CPPS is presented to support practitioners in the realisation of smart manufacturing control concepts.

Cyber-physical production systems are highly flexible systems that enable adaptive production processes. In these systems, all participants of the production process possess individual information about themselves and are equipped with sensors, actors, and communication interfaces. They can interact with each other and autonomously develop and execute process relevant decisions. For each component, a standard process sequence and alternative process sequences are defined. If a deviation in the standard process occurs during the production of an individual component, the process participants can interact with each other and autonomously define an appropriate response strategy and execute it by using actors of the participants and the intralogistics. Regardless of the deviation, the manufacturing and assembly process of individual components in cyber-physical production systems can still proceed. For this purpose, process deviations and the response behavior of cyber-physical production systems are analyzed, modeled, and simulated, to illustrate the benefits of cyber-physical production systems and to develop a process deviation management system for actual, physical production systems based on cyber-physical systems.

A method for supporting the transformation of an existing production system with its integrated Enterprise Information Systems (EISs) into a Cyber Physical Production System (CPPS)

The article offers the considerations and reasons for the application of the concept of intelligent engineering for the planning of cyber-physical production systems (CPPS). The engineering of an optimal chain of production processes is becoming an important competitive factor. Recently, an increase in individualization with simultaneously growing sales volumes has become the main trend in the market. In such conditions, industrial enterprises are facing the problem of the production of customized efficiency products. The solution to the problem of improving the economic efficiency can be ensured through the application of the intelligent engineering CPPS. The intelligent engineering is aimed at planning a CPPS that will ensure the production of a product in accordance with the individual requirements at the target cost. The intelligent engineering is based on the rapid planning of engineering enterprises, target cost analysis, and continuous digital planning of CPPS. The intelligent engineering of production includes several phases: analysis of requirements for a CPPS, calculation and analysis of the target cost, engineering of a cyber-physical production system according to the consumer requirements and target cost, creation of a production digital twin, application of a continuous digital planning approach, monitoring and evaluation of received data. Engineering of CPPS is based on the product framework the enterprise concept and target cost. The intelligent engineering involves designing a product using the concept of a product platform. This platform allows you to produce many options based on the layout of various product elements. As a part of the intelligent engineering concept, a cyber-physical production system planning is carried out in parallel with product design. Planning of the CPPS is done in accordance with the concept of an agile complex enterprise planning, at the same time for 23 modules simultaneously. A fundamental element of the intelligent engineering is the creation of a digital twin of the CPPS system that allows you to visualize the processes from product development to finished products as a single process in real time. Thus, the intelligent engineering allows you to quickly design the product and production process at the target cost. And the formation of an optimal chain of production processes is becoming an important factor in competition.

The Internet of Things (IoT) era facilitates new possibilities at the interface between the lifecycle of the product and the manufacturing disciplines allowing to add value and meet growing legal requirements. This work presents use cases from the automobile industry which are analyzed in order to derive requirements for data exchange. The analysis of the use cases shows clearly that we need to focus on the instance level for this purpose. This means that both, a specific unit of the product and the production system, must be considered. As a solution approach, a communication loop is proposed bringing the Digital Twin concept in a new field of usage. The key aspect of the proposed solution is the direct intercommunication between the Digital Twins of the product being produced as a Cyber-Physical System (CPS) and the production resources as Cyber-Physical Production Systems (CPPS). This solution enables the aggregation of production-related data within the products Digital Twin and therefore promotes maximal transparency throughout engineering disciplines, phases of the product lifecycle and the whole supply chain.

In the context of Industry 4.0, Cyber-Physical Production Systems (CPPS) and digital twins are key technologies for the management of huge amount of data generated by Industrial Internet of things (IIoT) devices. However, the interoperability and flexibility of different components is still an important challenge so as to integrate them in the process and fit all industrial specific needs. Thus, the main contribution of this paper is to propose a database architecture and a data model associated allowing multiple agents to work collaboratively and synchronously to perform high-level tasks. Therefore, it fulfils requirements and needs of Industry 4.0: interoperability, scalability, flexibility and resilience. The proposed architecture and model are implemented on a cyber-physical production system (CPPS) which is used in order to show and discuss several use cases examples.

Digital Twins are part of the vision of Industry 4.0 to represent, control, predict, and optimize the behavior of Cyber-Physical Production Systems (CPPSs). These CPPSs are long-living complex systems deployed to and configured for diverse environments. Due to specific deployment, configuration, wear and tear, or other environmental effects, their behavior might diverge from the intended behavior over time. Properly adapting the configuration of CPPSs then relies on the expertise of human operators. Digital Twins (DTs) that reify this expertise and learn from it to address unforeseen challenges can significantly facilitate self-adaptive manufacturing where experience is very specific and, hence, insufficient to employ deep learning techniques. We leverage the explicit modeling of domain expertise through case-based reasoning to improve the capabilities of Digital Twins for adapting to such situations. To this effect, we present a modeling framework for self-adaptive manufacturing that supports modeling domain-specific cases, describing rules for case similarity and case-based reasoning within a modular Digital Twin. Automatically configuring Digital Twins based on explicitly modeled domain expertise can improve manufacturing times, reduce wastage, and, ultimately, contribute to better sustainable manufacturing.

Industry 4.0 denotes a recent trend that aims at exploiting Cyber Physical Systems (CPS), based on IoT (Internet of Things) and cloud computing technologies, to obtain increased degrees of cooperation and communication in production systems, thus leading to what is referred to as Cyber Physical Production Systems (CPPS) or “Smart Factories”.

V-model based development of cyber-physical systems and cyber-physical production systems

Middleware-based Cyber-Physical Production System Modeling for Operators

The automation pyramid is shifting and will most likely not have a stock in rigid form. The shift is towards Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS). Some components in CPPS have to meet real-time requirements. One trend coming along with the change in automation architectures is the virtualization of applications. This enables platform independent development and deployment of secure and isolated applications. Yet, virtualization of applications comes with additional software components and therefore, additional processing effort. For web-services, virtualization is widespread, for embedded systems virtualization development and deployment is not common due time constraints of applications. The use of virtualized applications in embedded systems would have significant benefits like less effort in cross-platform development and cross compiling to state two examples. The method of virtualization in CPPS have to be evaluated concerning time-sensitive applications. In this approach, the time delays occurring through the additional virtualization layer with Docker containers are explored.

Using open-source microcontrollers to enable digital twin communication for smart manufacturing

One of the most significant directions in the development of computer science and information and communication technologies is represented by Cyber-Physical Systems (CPS) which are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the internet. Cyber-Physical Production Systems (CPPS), relying on the newest and foreseeable further developments of computer science, information and communication technologies on the one hand, and of manufacturing science and technology, on the other, may lead to the 4th Industrial Revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots generally – and particularly in the CIRP community – which point towards CPPS. Expectations and the related new R&D challenges are also outlined.

Industry 4.0 (the fourth industrial revolution) encapsulates future industry development trends to achieve more intelligent manufacturing processes, including reliance on Cyber-Physical Systems (CPS), construction of Cyber-Physical Production Systems (CPPS), and implementation and operation of smart factories. This paper introduces relevant aspects of Industry 4.0 in relation to strategic planning, key technologies, opportunities, and challenges. Strategic planning includes construction of a CPS network, discussion of two major themes which are based on the smart factory and intelligent production, achieving three integrations (horizontal integration, vertical integration and end-to-end integration) and achieving eight plans which consist of the formulation of system standardization, efficient management etc. Finally, it referred to the enlightenment for China's manufacturing industries, to build China's Industry 4.0.