Keywords
Industry 4.0, design engineering, digitalization, integration, service-oriented products, smart X, data-driven, dynamic risk management, sustainable design, flexible manufacturing
Introduction
Industry 4.0, also known as the fourth industrial revolution, is having a profound impact on design engineering (DE4.0). This chapter discusses how the new principles, methods, and roles of design engineering adapt in the Industry 4.0 era and leverage big data, machine learning, and other digital technologies to improve product design, lifecycle management, and supply chain efficiency. With the advent of Industry 4.0, the design field is facing unprecedented challenges, including new forms of human-data interaction, increased system complexity and uncertainty, and cybersecurity issues. To address these challenges, the article emphasizes the importance of incorporating design thinking into product development and manufacturing, and proposes several key solutions.
First, Design Thinking becomes the core of strategic planning, systematically leveraging employee creativity for decision-making to achieve dynamic integrated manufacturing innovation. The design process not only focuses on the completion of traditional products, but also extends to marketing and customer service, such as the application of digital twins, which helps improve production efficiency and adapt to changes.
Second, the application of intelligent technologies provides data-driven decision support. For example, the use of eye tracking systems can collect data about the location or status of products and share them in real time through digital twins, thereby optimizing safety and productivity in the production process.
In addition, the article also discusses how to deal with uncertainty and complexity in design, such as introducing flexibility in the selection and determination of design parameters, and using data science methods to manage and assess risks. These technologies can help designers foresee and respond to possible problems and ensure the reliability and adaptability of the system.
Finally, the article proposes that organizations need to transform from profit-oriented enterprises to learning organizations, guided by social interests, and safely integrate robots into production lines. This transformation not only requires the manufacturing industry to update its production model, but also requires employees to have interdisciplinary capabilities and innovation skills.
In summary, the challenges of the Industrial 4.0 era call for the comprehensive application of design thinking. Through data-driven, system flexibility and sustainable design, enterprises can cope with complex environments and achieve efficient manufacturing. In addition, organizational transformation is the key to ensuring this goal, which will help drive the manufacturing industry in a smarter and more flexible direction.
Key topics include: Innovation Ecosystem: With the development of Industry 4.0, the roles of consumers and design engineers become more important. They jointly shape the future system and ensure its sustainability. This requires design engineering to focus on cultivating an innovation ecosystem to support the evolution of products and services through real-time data decision-making.
Cyber-Physical-Systems (CPS) and Internet of People: With the integration of the Internet and personal items, designers need to deal with the blurring of the boundaries between the "digital self" and the physical world, which involves how to deal with human interaction and cooperation while technology advances.
Academic Keyword 1: Industry 4.0 - Product Ecosystem Design
Explanation: This keyword refers to the concept of product ecosystem design in the Industry 4.0 era, which involves dynamic product units and user interactions, and designers need to deal with growing technical challenges.
Academic Keyword 2: Cloud-based Digital Platform - Open Innovation
Explanation: It refers to the use of cloud platforms to support open design and manufacturing, promote the realization process of service-oriented products, and coordinate physical flows.
Relationship: It is related to digital production and service-oriented in Industry 4.0, reflecting the impact of technological progress on product development.
Academic Keyword 3: Sharing Economy - Resource Sharing
Explanation: The sharing economy is an economic and social system based on resource sharing. It drives innovation through crowdsourcing and digital platforms, and promotes the distribution and market feasibility of products.
Key point: In design thinking, this model emphasizes cooperation and the flow of resources.
Academic keyword 4: Human-Cyber-Physical Systems (HCPS)
Explanation: It integrates human interaction, cooperation and physical systems. It is a concept in Industrialization 4.0 and involves the design of complex social and technical systems.
Key point: In industrial design and engineering, it is crucial to understand and adapt to the dynamic changes of such systems.
Academic keyword 5: Data-driven Design
Explanation: Data-driven design refers to guiding product development based on a large amount of process data, emphasizing the role of data in design decisions.
Relationship: It reflects the data analysis and application in modern design, emphasizing the innovation of design methods and technologies.
Problem: How to use digital technology and human-computer interaction to solve the problems faced in DE4.0?
Solution: Through cloud design and manufacturing, use digital platforms for collaboration, reduce technology dependence and improve decision-making efficiency. At the same time, design new products such as service systems, use CSCW technology to understand and deal with complexity, and optimize products and services through data analysis.
Results
This approach enables products to adapt to consumer ecosystems, provide real-time value, and potentially capture value through subscription fees. In addition, it emphasizes sustainability and circular economy thinking in design, such as managing resources through system dynamics simulation and simulation, and using data science methods for knowledge synthesis and integration tasks.
Summary
DE4.0 achieves intelligent production by combining technology with humanized design and leveraging real-time event data, and has a profound impact on service-oriented product design, risk management, and sustainable design. This has prompted manufacturers to transform from a purely profit-oriented approach to a learning organization to adapt to the rapidly changing market environment and technological development.
With the advent of Industry 4.0, the field of design engineering faces problems such as resource-sharing production networks, intelligent manufacturing, and cross-organizational coordination. These issues are mainly reflected in how to achieve efficient decision-making in the digital age, the construction of digital communication frameworks, and the application of intelligent systems.
First, the article discusses the "Digital Thread" in digital communication, which is a key concept that promotes the automation of production processes and information flow by integrating design information and models. However, how to establish and maintain this framework is a challenge because it involves data security and privacy protection.
Secondly, the application of intelligent manufacturing in manufacturing has also brought a series of problems, such as production efficiency, quality and innovation decision-making needs. The concept of Smart X was proposed to improve competitiveness by shortening the supply chain cycle, but its implementation requires solving the integration of software and hardware, and how to use the data brought by these technologies to achieve faster response.
In addition, the article also mentions specific issues such as business to consumer (B2C), Internet services, digital sharing of products and services, and emotion prediction in the design and manufacturing process. This involves data-driven design optimization, the application of emotion recognition technology, and the value of information.
In terms of solutions, the authors emphasize the importance of cybersecurity management, by using digital twin technology to protect design data, while using intelligent decision support systems for continuous decision making and evaluation. In addition, technology and innovation strategies are also proposed, such as human-computer interaction design (Industry 4.0) through a model-driven framework, and the application of biometric devices for user experience analysis.
Finally, the article summarizes the application effects of these solutions, including improving production efficiency through digital technology, promoting product and service innovation through service-oriented thinking, and adapting to changes in the digital workplace through the requirements of non-technical capabilities. However, specific data on actual effects are not provided in the article, and further reference to specific studies or reports is required.
The article "Engineering Design in the Era of Industry 4.0: Integration and Innovation" explores the new challenges and opportunities of design engineering in the era of Industry 4.0. First, the article points out that with the advancement of technology and the popularization of the Internet, such as the application of the Internet of Things, big data and artificial intelligence, the design process is no longer limited to the completion of product functions, but has expanded to multiple fields such as marketing and customer service, forming a "digital thread", which emphasizes the importance of digital communication and coherence in design.
Design engineering is shifting from traditional physical manufacturing to more complex human-machine interactive systems, such as Human-Cyber-Physical Systems (HCPMS). The author mentions how to understand and manage uncertainty in the early stages of design, and how to deal with cybersecurity threats, such as how to prevent and protect systems from potential threats. In addition, the article mentions that the design process needs more iterative decision-making and evaluation, and emphasizes the importance of design thinking and service orientation.
At the same time, the article points out that the way of education may also need to adapt to changes, such as the length of courses may be shortened to ensure that knowledge is not outdated, and explores the possibility of online education (MOOCs) as a new education model. This reflects the need for innovation, rapid learning and lifelong learning in Industry 4.0.
In addition, the article discusses how to transform from a profit-oriented enterprise to a "learning organization" and integrate social interests, such as through the challenges of the circular economy, and how to use technology such as big data analysis to improve decision-making efficiency and quality assurance. The author points out the importance of non-technical capabilities (such as innovative thinking, adaptability, etc.) in the digital workplace, and emphasizes that education should cultivate future work force.
The view of this article is that Industry 4.0 has brought multi-dimensional challenges and opportunities to design engineering. Designers need to have interdisciplinary understanding and the ability to adapt quickly. At the same time, enterprises also need to change their business models and embrace learning and sustainable development. This tells us that in the face of technological progress, design should not only focus on product functions, but also consider overall efficiency and user experience; education should focus on cultivating innovation capabilities and lifelong learning; enterprises should assume social responsibilities and promote the development of the circular economy while pursuing profits.
Through this article, we can understand that design engineering in the era of Industry 4.0 requires comprehensive capabilities and adjustments and optimizations in combination with trends such as digitalization and service-orientedness.