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In the past two decades, augmented reality (AR) has received a growing amount of attention by researchers in the manufacturing technology community, because AR can be applied to address a wide range of problems throughout the assembly phase in the lifecycle of a product, e.g., planning, design, ergonomics assessment, operation guidance and training. However, to the best of authors’ knowledge, there has not been any comprehensive review of AR-based assembly systems. This paper aims to provide a concise overview of the technical features, characteristics and broad range of applications of AR-based assembly systems published between 1990 and 2015. Among these selected articles, two thirds of them were published between 2005 and 2015, and they are considered as recent pertinent works which will be discussed in detail. In addition, the current limitation factors and future trends in the development will also be discussed.

Abstract Increasing competition in the global marketplace demands products with better functionality, higher quality, lower cost, shorter delivery lead time, and increased environmental friendliness. Although advanced manufacturing technologies can partially address these challenges, advanced design technologies are considered critical, since most design and manufacturing properties of a product are influenced by the design decisions made in the early design stages. This paper provides a comprehensive review on a new design paradigm — adaptable design — that aims at developing adaptable products to satisfy the various requirements of customers. The topics discussed in this review include the fundamental concepts, objectives, methodologies, and applications. The paper also presents the differences between adaptable design and other design methods, such as modular design, platform design, and product customization. The focus is on mechanical product design; however, potential applications of adaptable design in other disciplines are also briefly mentioned.

It is a challenging task for operators to program a remote robot for welding manipulation depending only on the visual information from the remote site. This paper proposes an intuitive user interface for programming welding robots remotely using augmented reality (AR) with haptic feedback. The proposed system uses a depth camera to reconstruct the surfaces of workpieces. A haptic input device is used to allow users to define welding paths along these surfaces. An AR user interface is developed to allow users to visualize and adjust the orientation of the welding torch. Compared with the traditional robotic welding path programming methods which rely on prior CAD models or contact between the robot end-effector and the workpiece, this proposed approach allows for fast and intuitive remote robotic welding path programming without prior knowledge of CAD models of the workpieces. The experimental results show that the proposed approach is a user-friendly interface and can assist users in obtaining an accurate welding path.

Current industrial robotic welding systems cannot achieve automated solutions for multi-layer multi-pass welding of complex joints due to the presence of non-uniform and irregular welding groove geometries. This paper presents an adaptive pass planning approach for robotic welding of such complex joints. The welding groove is first segmented considering both the variation in groove dimension and the reachability of the robot welding torch. For each welding segment, the welding passes are planned to be in accordance with welding practices, viz., keeping the same number of welding passes in each layer while maintaining consistent welding parameters. An adaptive pass adjustment scheme is developed to address the discrepancies between the simulated results and the actual welding deposition after finishing a few layers of welding. Corresponding robot paths are generated and optimized to ensure minimum joint movement subject to three constraints, viz., reachability, collision-free and singularity avoidance. The proposed approach has been simulated with the arc welding of a Y-type joint found typically in offshore structures.

With the rapid advances in computing and Internet technologies, an integrated and collaborative environment, which is based on the complementary functions of concurrent engineering and Internet-based collaborative engineering, is imperative for companies to facilitate and expedite the product realization processes. Topics such as concurrent and collaborative engineering, feature-based design and manufacturing, evolutionary computational techniques such as Tabu Search, Simulated Annealing, Genetic Algorithms features, intelligent and computer-aided process planning are important strategies and enabling technologies for developing an integrative environment, facilitating modern product design and development. This book covers the state-of-the-art research and development status of these strategies and technologies. Implementation strategies and case studies are provided with an emphasis on technical details to help readers understand the underlying algorithms and infrastructures.

Since 1960s, with the development of societal and related technologies, many advanced manufacturing systems (AMSs) and modes have been put forward, and they have attracted the attention of a large number of researchers in manufacturing, information and management fields. However, existing studies are mainly focused on the specific theoretical research of each AMS, and the horizontal comparison of the difference and evolution of these AMSs are not significant. Furthermore, most of the existing studies try to realize concrete technical implementation, and discussions on the relationship among these AMSs and social factors are relatively rare. Therefore, this paper aims to address this issue, and a brief overview of the development process of AMSs is first presented. Next, a tri-view model is established to analyze the evolution and socialization characteristics of AMSs. It is found that the sharing of manufacturing resources and capabilities, the value creation carriers, the value measuring criteria, the composition of the value chain and enterprise collaboration, and the user participation in manufacturing are all moving towards socialization. It is essential that the evolution and development of AMSs should also adapt this trend towards socialization in order to achieve better sharing of limited resources and efficient adding of value.

The increasing digitalization and advancement in information communication technologies has greatly changed how humans interact with digital information. Nowadays, it is not sufficient to only display relevant data in production activities, as the enormous amount of data generated from smart devices can overwhelm operators without being fully utilized. Operators often require extensive knowledge of the machines in use to make informed decisions during processes such as maintenance and production. To enable novice operators to access such knowledge, it is important to reinvent the way of interacting with digitally enhanced smart devices. In this research, a mobile augmented reality remote monitoring system is proposed to help operators with low knowledge and experience level comprehend digital twin data of a device and interact with the device. It analyses both historic logs as well as real-time data through a cloud server and enriches 2D data with 3D models and animations in the 3D physical space. A cloud-based machine learning algorithm is applied to transform learned knowledge into live presentations on a mobile device for users to interact with. A scaled-down case study is conducted using a tower crane model to demonstrate the potential benefits as well as implications when the system is deployed in industrial environments. This user study verifies that the proposed solution yields consistent measurable improvements for novice users in human-device interaction that is statistically significant.

Efficient management of product information is vital for manufacturing enterprises in this information age. Considering the proliferation of product information, tight production schedules, and intense market competition, human intelligence alone cannot meet the requirements of efficient product development.

Augmented reality (AR) has recently become a worldwide research topic. AR technology renders intuitive computer-generated contents on users’ physical surroundings. To improve process efficiency and productivity, researchers and developers have paid increasing attention to AR applications in engineering analysis and simulation. The integration of AR with numerical simulation, such as the finite element method, provides a cognitive and scientific way for users to analyze practical problems. By incorporating scientific visualization technologies, an AR-based system superimposes engineering analysis and simulation results directly on real-world objects. Engineering analysis and simulation involving diverse types of data are normally processed using specific computer software. Correct and effective visualization of these data using an AR platform can reduce the misinterpretation in spatial and logical aspects. Moreover, tracking performance of the AR platforms in engineering analysis and simulation is crucial as it influences the overall user experience. The operating environment of the AR platforms requires robust tracking performance to deliver stable and accurate information to the users. In addition, over the past several decades, AR has undergone a transition from desktop to mobile computing. The portability and propagation of mobile platforms has provided engineers with convenient access to relevant information in situ. However, on-site working environment imposes constraints on the development of mobile AR-based systems. This paper aims to provide a systematic overview of AR in engineering analysis and simulation. The visualization, tracking techniques as well as the implementation on mobile platforms are discussed. Each technique is analyzed with respect to its pros and cons, as well its suitability to particular types of applications.