Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets

A 3D immersive discrete event simulator for enabling prototyping of factory layouts

There is an increasing need to eliminate wasted time and money during factory layout design and subsequent construction. It is presently difficult for engineers to foresee if a certain layout is optimal for work and material flows. By exploiting modelling, simulation and visualisation techniques, this paper presents a tool concept called immersive WITNESS that combines the modelling strengths of Discrete Event Simulation (DES) with the 3D visualisation strengths of recent 3D low cost gaming technology to enable decision makers make informed design choices for future factories layouts. The tool enables engineers to receive immediate feedback on their design choices. Our results show that this tool has the potential to reduce rework as well as the associated costs of making physical prototypes

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences

Panel on future challenges in modeling methodology

This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing

Modeling IoT-aware Business Processes - A State of the Art Report

This research report presents an analysis of the state of the art of modeling Internet of Things (IoT)-aware business processes. IOT links the physical world to the digital world. Traditionally, we would find information about events and processes in the physical world in the digital world entered by humans and humans using this information to control the physical world. In the IoT paradigm, the physical world is equipped with sensors and actuators to create a direct link with the digital world. Business processes are used to coordinate a complex environment including multiple actors for a common goal, typically in the context of administrative work. In the past few years, we have seen research efforts on the possibilities to model IoT- aware business processes, extending process coordination to real world entities directly. This set of research efforts is relatively small when compared to the overall research effort into the IoT and much of the work is still in the early research stage. To create a basis for a bridge between IoT and BPM, the goal of this report is to collect and analyze the state of the art of existing frameworks for modeling IoT-aware business processes.Comment: 42 page

Towards Developing a Digital Twin Implementation Framework for Manufacturing Systems

This research studies the implementation of digital twins in manufacturing systems. Digital transformation is relevant due to changing manufacturing techniques and user demands. It brings new business opportunities, changes organizations, and allows factories to compete in the digital era. Nevertheless, digital transformation presents many uncertainties that could bring problems to a manufacturing system. Some potential problems are loss of data, cybersecurity threats, unpredictable behavior, and so on. For instance, there are doubts about how to integrate the physical and virtual spaces. Digital twin (DT) is a modern technology that can enable the digital transformation of manufacturing companies. DT works by collecting real-time data of machines, products, and processes. DT monitors and controls operations in real-time helping in the identification of problems. It performs simulations to improve manufacturing processes and end-products. DT presents several benefits for manufacturing systems. It gives feedback to the physical system, increases the system’s reliability and availability, reduces operational risks, helps to achieve organizational goals, reduces operations and maintenance costs, predicts machine failures, etc. DT presents all these benefits without affecting the system’s operation. xv This dissertation analyzes the implementation of digital twins in manufacturing systems. It uses systems thinking methods and tools to study the problem space and define the solution space. Some of these methods are the conceptagon, systemigram, and the theory of inventive problem solving (TRIZ in Russian acronym). It also uses systems thinking tools such as the CATWOE, the 9-windows tool, and the ideal final result (IFR). This analysis gives some insights into the digital twin implementation issues and potential solutions. One of these solutions is to build a digital twin implementation framework Next, this study proposes the development of a small-scale digital twin implementation framework. This framework could help users to create digital twins in manufacturing systems. The method to build this framework uses a Model-Based Systems Engineering approach and the systems engineering “Vee” model. This framework encompasses many concepts from the digital twin literature. The framework divides these concepts along three spaces: physical, virtual, and information. It also includes other concepts such as digital thread, data, ontology, and enabling technologies. Finally, this dissertation verifies the correctness of the proposed framework. The verification process shows that the proposed framework can develop digital twins for manufacturing systems. For that purpose, this study creates a process digital twin simulation using the proposed framework. This study presents a mapping and a workflow diagram to help users use the proposed framework. Then, it compares the digital twin simulation with the digital twin user and system requirements. The comparison finds that the proposed framework was built right

Simulation and the Fourth Industrial Revolution

Advancements in systems simulation over the past decade have propelled simulationinto a new position as a decision-making tool in Industry 4.0 applications. This paperaddresses the specific benefits of simulation which can be utilized to enable greaterflexibility in decision making in the Industry 4.0 environment. It is stressed thatboth discrete event simulation (DES) and agent-based simulation (ABS) can be usedto represent complex interactions in a fully integrated set of virtual and physicalsystems

Modeling 4.0: Conceptual Modeling in a Digital Era

Digitization provides entirely new affordances for our economies and societies. This leads to previously unseen design opportunities and complexities as systems and their boundaries are re-defined, creating a demand for appropriate methods to support design that caters to these new demands. Conceptual modeling is an established means for this, but it needs to be advanced to adequately depict the requirements of digitization. However, unlike the actual deployment of digital technologies in various industries, the domain of conceptual modeling itself has not yet undergone a comprehensive renewal in light of digitization. Therefore, inspired by the notion of Industry 4.0, an overarching concept for digital manufacturing, in this commentary paper, we propose Modeling 4.0 as the notion for conceptual modeling mechanisms in a digital environment. In total, 12 mechanisms of conceptual modeling are distinguished, providing ample guidance for academics and professionals interested in ensuring that modeling techniques and methods continue to fit contemporary and emerging requirements

A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.The present work was developed under the EUREKA–ITEA3 Project CyberFactory#1 (ITEA-17032), co-funded by Project CyberFactory#1PT (ANI|P2020 40124), from FEDER Funds through NORTE2020 program and from National Funds through FCT under the project UID/EEA/00760/2019 and by the Federal Ministry of Education and Research (BMBF, Germany, funding No. 01IS18061C).info:eu-repo/semantics/publishedVersio