Nowadays, along with the application of new-generation information technologies in industry and manufacturing, the big data-driven manufacturing era is coming. However, although various big data in the entire product lifecycle, including product design, manufacturing, and service, can be obtained, it can be found that the current research on product lifecycle data mainly focuses on physical products rather than virtual models. Besides, due to the lack of convergence between product physical and virtual space, the data in product lifecycle is isolated, fragmented, and stagnant, which is useless for manufacturing enterprises. These problems lead to low level of efficiency, intelligence, sustainability in product design, manufacturing, and service phases. However, physical product data, virtual product data, and connected data that tie physical and virtual product are needed to support product design, manufacturing, and service. Therefore, how to generate and use converged cyber-physical data to better serve product lifecycle, so as to drive product design, manufacturing, and service to be more efficient, smart, and sustainable, is emphasized and investigated based on our previous study on big data in product lifecycle management. In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed. The detailed application methods and frameworks of digital twin-driven product design, manufacturing, and service are investigated. Furthermore, three cases are given to illustrate the future applications of digital twin in the three phases of a product respectively.

Digital twin-driven product design, manufacturing and service with big data

Digital twin (DT) is one of the most promising enabling technologies for realizing smart manufacturing and Industry 4.0. DTs are characterized by the seamless integration between the cyber and physical spaces. The importance of DTs is increasingly recognized by both academia and industry. It has been almost 15 years since the concept of the DT was initially proposed. To date, many DT applications have been successfully implemented in different industries, including product design, production, prognostics and health management, and some other fields. However, at present, no paper has focused on the review of DT applications in industry. In an effort to understand the development and application of DTs in industry, this paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development of DTs, and the major DT applications in industry. This paper also outlines the current challenges and some possible directions for future work.

Digital Twin in Industry: State-of-the-Art

Digital Twin in manufacturing: A categorical literature review and classification

https://re.public.polimi.it/bitstream/11311/1049863/2/Negri%20et%20al%202017%20FAIM.pdf

A Review of the Roles of Digital Twin in CPS-based Production Systems

With the advances in new-generation information technologies, especially big data and digital twin, smart manufacturing is becoming the focus of global manufacturing transformation and upgrading. Intelligence comes from data. Integrated analysis for the manufacturing big data is beneficial to all aspects of manufacturing. Besides, the digital twin paves a way for the cyber-physical integration of manufacturing, which is an important bottleneck to achieve smart manufacturing. In this paper, the big data and digital twin in manufacturing are reviewed, including their concept as well as their applications in product design, production planning, manufacturing, and predictive maintenance. On this basis, the similarities and differences between big data and digital twin are compared from the general and data perspectives. Since the big data and digital twin can be complementary, how they can be integrated to promote smart manufacturing are discussed.

Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison

About The Importance of Autonomy and Digital Twins for the Future of Manufacturing

The vision of the Digital Twin itself refers to a comprehensive physical and functional description of a component, product or system, which includes more or less all information which could be useful in all—the current and subsequent—lifecycle phases. In this chapter we focus on the simulation aspects of the Digital Twin. Today, modelling and simulation is a standard process in system development, e.g. to support design tasks or to validate system properties. During operation and for service first simulation-based solutions are realized for optimized operations and failure prediction. In this sense, simulation merges the physical and virtual world in all life cycle phases. Current practice already enables the users (designer, SW/HW developers, test engineers, operators, maintenance personnel, etc) to master the complexity of mechatronic systems.

Digital Twin—The Simulation Aspect

Der seit einigen Jahren vielfaltig verwendete Begriff Digital Twin beinhaltet nach wie vor visionare Aspekte. Deren Berucksichtigung wird zur Entwicklung einer nachsten Generation digitaler Zwillinge fuhren. In der in diesem Beitrag beschriebenen Vision werden die Lebenszyklus-ubergreifenden Perspektiven vorgestellt und anhand von zwei Beispielen diskutiert. Neben seinem Einsatz in der Entwicklung wird der digitale Zwilling als Abbild des realen Systems im Betrieb und Service zunehmend neue simulationsbasierte Losungen ermoglichen. Die Lebenszyklus-ubergreifende Perspektive gepaart mit der Veranderung der Wertschopfungsketten wird zu einem Digital-Twin-Okosystem fuhren.

Next Generation Digital Twin: Öko-System für simulationsbasierte Lösungen im Betrieb

Next Generation Digital Twin: an Ecosystem for Mechatronic Systems?

For the automation of industrial plants in particular the plant technology can be described by processing technology on the one hand and control and instrumentation technology on the other. According to the invention, industrial process objects are formed from models of the process and control and instrumentation technology and processed in a computer-controlled planning system from which interlinked models are generated by control and/or regulation and/or simulation, including breakdown analysis. With the associated planning system, a computer (10) is used in a similar manner to access a component library (11) comprising industrial process elements and to access a description (12) of the elements of the actual plant from the viewpoint of a processing engineer.

Roland Rosen

Papers

About The Importance of Autonomy and Digital Twins for the Future of Manufacturing

Digital Twin—The Simulation Aspect

Next Generation Digital Twin: Öko-System für simulationsbasierte Lösungen im Betrieb

Next Generation Digital Twin: an Ecosystem for Mechatronic Systems?

Drafting method for industrial and building systems and computer-controlled planning system for use in said method