A digital twin framework for the simulation and optimization of production systems

Industry 4.0 has raised the expectations on productivity, automation, and resource efficiency of manufacturing systems. This paper proposes a digital twin framework for the simulation and optimization of production lines and cells that can be used in the design and operation stages. The framework is supported by an architecture that connects manufacturing and machine tool data (digital shadow), the discrete event simulation model and the optimization engine, allowing for a variety of functionalities to plan and manage the production system. A use case is provided to demonstrate this framework, implemented in an automated line for the manufacturing of railway axles

Implementation of a holistic digital twin solution for design prototyping and virtual commissioning

Industry 4.0 has ushered in a new era of digital manufacturing and in this context, digital twins are considered as the next wave of simulation technologies. The development and commissioning of Cyber Physical Systems (CPS) is taking advantage of these technologies to improve product quality while reducing costs and time to market. However, existing practices of virtual design prototyping and commissioning require the cooperation of domain specific engineering fields. This involves considerable effort as development is mostly carried out in different departments using vendor specific simulation tools. There is still no integrated simulation environment commercially available, in which all engineering disciplines can work collaboratively. This presents a major challenge when interlinking virtual models with their physical counterparts. This paper therefore addresses these challenges by implementing a holistic and vendor agnostic digital twin solution for design prototyping and commissioning practices. The solution was tested in an industrial use case, in which the digital twin effectively prototyped cost-efficient solar assembly lines

Implementation of Digital Twin-based Virtual Commissioning in Machine Tool Manufacturing

Virtual commissioning is not a new concept; However, it is all the rage with the introduction of Industry 4.0, in the field of product lifecycle management, computer-aided design (CAD), computer-aided manufacturing (CAM), and within the industrial automation programming frameworks. Although, this is a very active area of research and innovation, these technologies have little implementation in the machine tool industry [11]. There is still no integrated simulation environment for virtual commissioning in the market. In this context, digitalisation is a key driver. The aim of this paper is to describe the practice of virtual commissioning in the machine tool manufacturing industry by identifying available solutions in the market and addressing the challenges faced within the machine tool sector. As a result, a digital twin based virtual commissioning solution has been developed at Danobatgroup, the leading machine tool builder in Spain, which is a step forward towards the digitalisation of machine tool manufacturing

La puesta en marcha virtual en la fabricación de máquinas herramienta: encuesta industrial

Virtual commissioning has acquired a major interest with the introduction of Industry 4.0. It is demonstrated that virtual commissioning can significantly reduce the commissioning time, error rate and costs. However, industry is still experiencing difficulties with the integration of these new technologies. This paper is one of the first empirical surveys conducted in the industry that aims at understanding the challenges and current practices with respect to virtual commissioning, with special focus on the machine tool manufacturing sector. The survey contextualizes the practice of virtual commissioning and the digital twin in industry, and benchmarks the results with academia, in which main gaps are identified.La puesta en marcha virtual ha adquirido un gran interés con la introducción de la Industria 4.0. Está demostrado que la puesta en marcha virtual puede reducir significativamente el tiempo de puesta en marcha, la tasa de errores y los costes. Sin embargo, la industria sigue teniendo dificultades con la integración de estas nuevas tecnologías. Este estudio es una de las primeras encuestas empíricas realizadas en la industria que tiene como objetivo comprender los desafíos y las prácticas actuales con respecto a la puesta en marcha virtual en el sector de la fabricación de máquinas herramienta. La encuesta contextualiza la práctica de la puesta en marcha virtual y el gemelo digital en la industria, y compara los resultados con el mundo académico, en el que se identifican discrepancias significativas

Implementation of a holistic digital twin solution for design prototyping and virtual commissioning

Abstract Industry 4.0 has ushered in a new era of digital manufacturing and in this context, digital twins are considered as the next wave of simulation technologies. The development and commissioning of Cyber Physical Systems (CPS) is taking advantage of these technologies to improve product quality while reducing costs and time to market. However, existing practices of virtual design prototyping and commissioning require the cooperation of domain specific engineering fields. This involves considerable effort as development is mostly carried out in different departments using vendor specific simulation tools. There is still no integrated simulation environment commercially available, in which all engineering disciplines can work collaboratively. This presents a major challenge when interlinking virtual models with their physical counterparts. This paper therefore addresses these challenges by implementing a holistic and vendor agnostic digital twin solution for design prototyping and commissioning practices. The solution was tested in an industrial use case, in which the digital twin effectively prototyped cost‐efficient solar assembly lines

PLC orchestration automation to enhance human–machine integration in adaptive manufacturing systems

Current approaches to manufacturing must evolve to respond to increasing demands for short product life cycles and customised products. Adaptive manufacturing systems integrate advanced technologies, automation, and data-driven methodologies to develop adaptable, efficient, and responsive production processes. Central to this concept is the emphasis on human involvement and fostering synergy between human operators and the manufacturing system. Significant changes to the system's controller are required to achieve adaptivity, with programmable logic controllers (PLCs) being a common controller type. After the necessary changes to the configuration of the manufacturing system, the PLC should be reconfigured to orchestrate the new required behaviour. Automated reconfiguration is vital to rapidly responding to change, but some changes cannot be entirely achieved without human input in collaboration with automated methods. Conventional practices in PLC programming include manual, repetitive coding practices subject to errors. As a result, to ensure operational safety, the changes must be tested before being deployed to operations, ensuring it is error-free. This paper presents a methodology to automatically reconfigure the simulation environment and controller in response to a new product request. We automate the PLC code generation and testing practices to support and free up the operators when performing repetitive manufacturing reconfiguration tasks. The methodology is based on human learning, software automation, customised program development, knowledge graphs, and Graph Neural Networks (GNNs). The presented solution is a generic, vendor-agnostic, and interoperable solution that facilitates information exchange among multiple heterogeneous environments. Lastly, we have validated the methodology as a proof of concept at an adaptive assembly cell at the University of Nottingham in the United Kingdom