- Research Highlight
- Open Access
Future Digital Design and Manufacturing: Embracing Industry 4.0 and Beyond
© The Author(s) 2017
Published: 1 August 2017
This research highlight overviews the development roadmap of digital design and manufacturing and focuses on the future development directions under the Industries 4.0.
Digital design and manufacturing have been around for several decades from the numerical control of machine tools and automating engineering design in 1960s, through early Computer Aided Design (CAD)/Computer Aided Engineering analysis (CAE)/Computer Aided Manufacturing (CAM), to modern digital design and manufacturing , and cloud manufacturing  converging into product lifecycle management (PLM) [3, 4] and Internet-enabled personalized manufacturing .
Digital design and manufacturing technologies provide a great support for product realization from design conception and engineering to manufacturing, sales and services of a product. In the past, their developments and evolutions are driven greatly by other technological advances, such as those in materials, electronics, software, and ICT (information and computing) Technologies.
Now when we look at the horizon of the Industry 4.0 manufacturing scenarios and the emerging/evolving technologies, what are the challenges facing to our digital design and manufacturing research community and the industry? Examples of these technologies are novel manufacturing technology, such as additive manufacturing, ICTs, such as Cyber-Physics Systems (CPS), Big Data, the Internet of Things (IoTs), Artificial intelligence (AI), Digital Twin, and SMAC (Social, Mobile, Analytics, Cloud) and product and design technology, such as Smart Products, User Experience (UX) and Human Centered Design (HCD). In order to provide some insights into those questions, we organized an international workshop for scientists, engineers, scholars and research students to exchange ideas and update technical knowledge on related topics and published a special issue at this journal.
What are the driving forces  for Industry 4.0 or similar future manufacturing strategies such as “Made in China 2025”? On the one hand, we are facing some big social, economic and environmental challenges including ever-increasing global competitive pressure, personalized products/service, shrinking product lifecycles and fast changing technologies. These require horizontal integration of manufacturing value chains, such as  on integration of through-life product intelligence within smart products and smart manufacturing systems. On the other hand, with the increasing usage of information and communication technologies for the autonomy within the manufacturing environment or creating smart factory with Cyber-Physicals systems , there are requirements for vertical integration of manufacturing systems with CPS.
From a system point of view, future digital design and manufacturing research consists of four major research perspectives related to the manufacturing process, devices, software and engineering. The key technological enablers for implementing Industry 4.0 manufacturing environment are three interdependent ICT technologies: Internet of Thing, Cyber-Physical Systems and Smart Factory. Internet of Thing helps to create Cyber-Physical systems and the Cyber-Physical system helps to realize Smart Factories including Smart Products. Therefore, Smart Factory is regarded as a major vision of Industry 4.0 .
The selected 29 papers in the special issue provide some reference to the current research trends and challenges on digital design and manufacturing. Their research themes are closely related to the four research perspectives.
Under the manufacturing process perspective, two main research themes are (1) vertical integration with Internet of Thing, and Cyber-Physical Systems, and (2) horizontal integration with worldwide value chains. Vertical integration with Cyber-Physical Systems can support the concept of the smart factory, enabling (partly) autonomous and self-organized processes, which lead to increased efficiency and flexibility. The applications of Cyber-Physical Systems can also be extent to the self-aware health management of manufacturing systems and maintenance scheduling. Furthermore, the interaction study on the interplay of the machining process, the machine tools and the CPS systems needs more attentions.
Under the theme of horizontal integration with worldwide value chains, horizontal integration with supply chain can lead to better quality assurance systems by seamless integration of in-process production data and information internally and managing suppliers more effectively and efficiently. In addition, there is a need to the integration of customers, users and people in the early stage of product innovation to realize the human centered design and innovation from “design for people”, to “design by people” and “design with people”. It is also important to have the through lifecycle integration between smart product and smart manufacturing, which leads to entire smart manufacturing system.
In the view of devices perspective, the researches cover two themes: (1) physical devices and (2) device interfacing.
For physical device development, nanoparticles, nanomaterials and sensor technologies are being explored in the application. For device interfacing, wireless device connection problems, human-machine and human-system interfacing and interaction are taken into account. Examples are a smart and effective interfacing assistive system for the elder drivers by combining and interfacing various sensor devices, a smart power system solution for a household in the UK by connecting and interfacing several renewables properly and a smart cutting tool integrated with smart machining process. Some recent research focuses on platform technologies for integrating social sensors to support social manufacturing.
Under the software perspective, most of research attentions have been paid to (1)production control and regulation and (2) Product design and development processing control. Some researches investigate integrated manufacturing process quality analysis and control approaches based on Bayesian network and big data analysis. Others explore rapid online object identification and production control, such as a measured surface localization method for contour error evaluation, quality inspection and error compensation, and an energy-resource efficiency management method with in-process virtual management. In product design and collaborative processing control, researches focus on system simulation-driven multidisciplinary collaborative product design and development, such as spatiotemporal synchronization process control methods for collaborative simulation carried out on distributed computing devices.
Under the engineering perspective, the selected papers cover two themes: (1) product design and development, and (2) production and manufacturing engineering.
For product design and development, the role of digitalization in emotional product design has been highlighted and an demonstrative example is transferring 3D digital models into relief product models. Meanwhile, performance-driven design methods for complex engineering product development are well investigated by studying design product data models, design parameters’ impact on product performance, and complex relationships among the design parameters. Others focused on conceptual design methods of complex mechatronic products by investigating customers’ requirement modelling, design change propagation modelling, bio-mimicry design and concurrent multi-product development.
For production engineering, main researches are focused on design optimization, additive manufacturing and the optimization of production line for improving production efficiency.
Overall, future digital design and manufacturing will embrace the challenges and opportunities in the Industry 4.0 era in line with the SMAC phenomenon (Social Networking, Mobility, Analytics based on Big data and Cloud computing) which is increasingly playing a powerful role for future innovative design and manufacturing.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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