skip to main content


Title: Design Engineering in the Age of Industry 4.0
Abstract Industry 4.0 is based on the digitization of manufacturing industries and has raised the prospect for substantial improvements in productivity, quality, and customer satisfaction. This digital transformation not only affects the way products are manufactured but also creates new opportunities for the design of products, processes, services, and systems. Unlike traditional design practices based on system-centric concepts, design for these new opportunities requires a holistic view of the human (stakeholder), artefact (product), and process (realization) dimensions of the design problem. In this paper we envision a “human-cyber-physical view of the systems realization ecosystem,” termed “Design Engineering 4.0 (DE4.0),” to reconceptualize how cyber and physical technologies can be seamlessly integrated to identify and fulfil customer needs and garner the benefits of Industry 4.0. In this paper, we review the evolution of Engineering Design in response to advances in several strategic areas including smart and connected products, end-to-end digital integration, customization and personalization, data-driven design, digital twins and intelligent design automation, extended supply chains and agile collaboration networks, open innovation, co-creation and crowdsourcing, product servitization and anything-as-a-service, and platformization for the sharing economy. We postulate that DE 4.0 will account for drivers such as Internet of Things, Internet of People, Internet of Services, and Internet of Commerce to deliver on the promise of Industry 4.0 effectively and efficiently. Further, we identify key issues to be addressed in DE 4.0 and engage the design research community on the challenges that the future holds.  more » « less
Award ID(s):
1928313
NSF-PAR ID:
10312975
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
Journal of Mechanical Design
Volume:
143
Issue:
7
ISSN:
1050-0472
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract This paper (Wu 2016), which was published in AI EDAM online on August 22, 2016, has been retracted by Cambridge University Press as it is very similar in content to a published ASME Conference Proceedings paper. The article in question and the ASME Conference Proceedings paper were submitted for review with AI EDAM and the ASME at similar times, but copyright was assigned to ASME before the paper was accepted in AI EDAM and therefore the article in AI EDAM is being retracted. (In recent years, industrial nations around the globe have invested heavily in new technologies, software, and services to advance digital design and manufacturing using cyber-physical systems, data analytics, and high-performance computing. Many of these initiatives, such as cloud-based design and manufacturing, fall under the umbrella of what has become known as Industry 4.0 or Industrial Internet and are often hailed as pillars of a new industrial revolution. While an increasing number of companies are developing or already offer commercial cloud-based software packages and services for digital design and manufacturing, little work has been reported on providing a review of the state of the art of these commercial software and services as well as identifying research gaps in this field. The objective of this paper is to present a state-of-the-art review of digital design and manufacturing software and services that are currently available on the cloud. The focus of this paper is on assessing to what extent engineering design, engineering analysis, manufacturing, and production across all phases of the product development lifecycles can already be performed based on the software and services accessed through the cloud. In addition, the key capabilities and benefits of these software packages and services are discussed. Based on the assessment of the core features of commercial software and services, it can be concluded that almost all phases of product realization can be conducted through digital design and manufacturing software and services on the cloud. Finally, existing research gaps and related challenges to overcome are identified. The state-of-the-art review serves to provide a technology guide for decision makers in their efforts to select suitable cloud-based software and services as alternatives to existing in-house resources as well as to recommend new research areas.) 
    more » « less
  2. Digital twin is a vital enabling technology for smart manufacturing in the era of Industry 4.0. Digital twin effectively replicates its physical asset enabling easy visualization, smart decision-making and cognitive capability in the system. In this paper, a framework of dynamic data driven digital twin for complex engineering products was proposed. To illustrate the proposed framework, an example of health management on aircraft engines was studied. This framework models the digital twin by extracting information from the various sensors and Industry Internet of Things (IIoT) monitoring the remaining useful life (RUL) of an engine in both cyber and physical domains. Then, with sensor measurements selected from linear degradation models, a long short-term memory (LSTM) neural network is proposed to dynamically update the digital twin, which can estimate the most up-to-date RUL of the physical aircraft engine. Through comparison with other machine learning algorithms, including similarity based linear regression and feed forward neural network, on RUL modelling, this LSTM based dynamical data driven digital twin provides a promising tool to accurately replicate the health status of aircraft engines. This digital twin based RUL technique can also be extended for health management and remote operation of manufacturing systems. 
    more » « less
  3. This paper proposes a conceptual architecture of digital twin with human-in-the-loop-based smart manufacturing (DH-SM). Our proposed architecture integrates cyber-physical systems with human spaces, where artificial intelligence and human cognition are employed jointly to make informed decisions. This will enable real-time, collaborative decision-making between humans, software, and machines. For example, when evaluating a new product design, information about the product’s physical features, manufacturing requirements, and customer demands must be processed concurrently. Moreover, the DH-SM architecture enables the creation of an immersive environment that allows customers to be effectively involved in the manufacturing process. The DH-SM architecture is well fitted to those relatively new manufacturing processes, such as metal additive manufacturing, since they can benefit from using digital twins, data analytics, and artificial intelligence for monitoring and controlling those processes to support non-contact manufacturing. The proposed DH-SM will enable manufacturers to leverage the existing cyber-physical system and extended reality technologies to generate immersive experiences for end users, operators, managers, and stakeholders. A use case of wire + arc additive manufacturing is discussed to demonstrate the applicability of the proposed architecture. Relevant development and implementation challenges are also discussed. 
    more » « less
  4. Digital Twin (DT) is one of the key enabling technologies for realizing the promise of Smart Manufacturing (SM) and Industry 4.0 to improve production systems operation. Driven by the generation and analysis of high volume data coming from interconnected cyber and physical spaces, DTs are real-time digital images of physical systems, processes or products that help evaluate and improve business performance. This paper proposes a novel DT architecture for the real- time monitoring and evaluation of large-scale SM systems. An application to a manufacturing flow-shop is presented to illustrate the usefulness of the proposed methodology. 
    more » « less
  5. The Internet of Things (IoT) technologies can enable products to become smarter through sensing their environment, analyzing lots of data (big data), and connecting to the Internet to allow for the exchange of data. As smart products become ubiquitous, they provide enormous opportunities for scientists and engineers to invent new products and build interconnected systems of vast scale. As a result, the STEM workforce demands are shifting rapidly. Mechanical engineers will play a significant role in innovating and designing smart products and manufacturing systems of the Industry 4.0 revolution. However, the current mechanical engineering curriculum has not kept pace. In this paper, we present an overview of a new curriculum along with the design of an inexpensive smart flowerpot device that was used as an instructional tool throughout the curriculum. We provide details about how two curriculum modules were implemented in the first offering of the course. Preliminary assessment results from the first offering of the course are discussed. 
    more » « less