IET Collaborative Intelligent Manufacturing最新文献

As a better alternative to the energy-intensive process of recycling waste sheet steel (WSS) from the exterior components of end-of-life vehicles to produce new steel, the feasibility of remanufacturing WSS into angle mesh steel (AMS) for construction applications is evaluated. A remanufacturing unit with a capacity of 1278 m²/day of WSS (30,000 vehicle/year) was evaluated using a triple-bottom-line sustainability analysis of the technological, economic, and environmental feasibilities by hybrid defuzzification–curve-fitting, solid-waste recoverability management, and weighting methods. Based on the remanufacturing productivity, an economic feasibility index was calculated considering the sales potential and profit, while the energy and CO₂ emission savings were used to evaluate the environmental feasibility. The technical feasibility considered machine parameters and topological properties of the WSS. The Volkswagen Passat has the best remanufacturability of 200 analysed vehicle models. Remanufacturability indexes of 0.61 and 0.86 were calculated, giving remanufacturing efficiencies of 58%–82%. All feasibility indexes exceed literature thresholds, indicating that the proposed remanufacturing process is a sustainable business strategy and contributes to the United Nations Sustainability Goals of climate action; responsible consumption and production; no poverty; and industry, innovation, and infrastructure.

OpenAI's ChatGPT (GPT-4) ushers in a superior mode of computer interaction through natural language dialogues. Notably, it generates not only engaging dialogues but also codes aligned to queries and requirements. The potential of ChatGPT in hardware implementation via natural language is implemented and a strategy for “asking the right questions” is outlined. The versatility of ChatGPT is demonstrated through three mainstream hardware designs – systolic array, ResNet and MobileNet accelerators – comparing these with hand-coded designs. The evaluation metrics include design quality, design efforts, and limitations of code generated by ChatGPT/GPT-4/Cursor against prevalent High-Level Synthesis or hand-coded HDL designs. Consequently, a novel design workflow is proposed and the constraints of using GPT, particularly in AI accelerators, are highlighted.

A spectrum of control methods in human–robot interaction was investigated, ranging from direct control to telepresence with a virtual representation of the robot arm. A total of 24 participants used a setup that included a Franka Emika Panda robot arm, Varjo XR-3 head-mounted display, and Leap Motion Controller. Participants performed a box-and-block task using the bare hand (A), and under five gesture-controlled robotic operation methods: direct sight (B), sight via video-feedthrough (C), in a 3D telepresence environment with (D) and without (E) virtual representation of the robot arm, and using a 2D video feed (F). The number of grabbing attempts did not differ significantly between conditions, but local operation (B & C) yielded more transferred blocks than teleoperation (D–F). Teleoperation using a 3D presentation was advantageous compared to teleoperation using a 2D video feed, as demonstrated by lower peak forces and smaller range in gripper heights in conditions D and E compared to condition F, a finding supported by analyses of the head movement activity. Finally, the bare hand yielded the best performance and subjective ratings. In summary, teleoperation using a 3D presentation provided a smoother interaction than teleoperation with a 2D video feed. However, direct human interaction remains a benchmark yet to surpass.

The reliability of well-performing production processes not only depends on internal but also on external factors in the upstream supply chain. Therefore, companies require fast and reliable information exchange with cooperating organisations. Since existing researches usually put focus on reviewing intra-organisational solutions, the authors have conducted a survey to capture the current state and needs regarding the inter-organisational information exchange between German companies. The main outcomes of the authors’ survey are outlined. In a first step, the current status of digitalisation in the companies is analysed. The authors have found that the use and implementation of modern methods correlates positively with the company size. Taking a look on the current methods for inter-organisational information exchange in a second step, it is seen that only a few companies are completely satisfied with their current methods. Companies see the greatest potential for the improvement of information exchange in standardisation and the increase of required resources. This indicates that companies would be best supported by the development of solutions that can be implemented easily and help to form the heterogeneous landscape of data exchange strategies towards a structured, standardised way.

In the era of the fourth industrial revolution, many certain technologies such as Internet of Things (IoT) or Internet of Service (IoS) have been implemented for the improvement of current system. However, most of them did not ensure the real-time performance which is inevitable for modern motion systems. The implementation of Ethernet-based protocol, rapid data exchange and synchronised transmission are proper for the novelties of slave controller. An integration of the decentralised network into the motion control system is introduced firstly. To demonstrate the conceptual design, some descriptions of motivations and related definitions are explained. Then, the structure of hardware components and internal connections are mentioned. Later, the software architecture including the data exchange and flowchart of motion program, is described in detail. To verify the feasibility and effectiveness of the proposed approach, some technical analysis of timing synchronisation and tracking deviation between our method and the others are carried out. In addition, several practical validations are conducted in the same conditions. The contributions of the authors are (i) to firstly present the concept of controller design using the real-time technology, (ii) to illuminate both hardware design and software design of the proposed approach and (iii) to analyse the superior performance in delay time between our method and the others as well as validate the real-world results to prove the effectiveness and feasibility. From the authors’ achievement, it is observed that these results can be broadly purposeful to the sustainable development of Industry 4.0.

Meeting customer time requirements poses a major challenge in the context of high-variety make-to-order companies. Companies need to reduce the lead time and process urgent jobs in time, while realising high delivery reliability. The key decision stages within Workload Control (WLC) are order release and shop floor dispatching. To the best of our knowledge, recent research has mainly focused on order release stage and inadvertently ignored shop floor dispatching stage. Meanwhile, urgency of job is not only related to its due date, but also affected by the dynamics of shop floor. Specifically, urgency of jobs may decrease at downstream operations in the job's routing, since priority dispatching for urgent jobs accelerates production speed at the upstream operations. And occupying production resources increases the waiting time of non-urgent jobs at workstation. This phenomenon leads to the change of urgency of jobs. Misjudgement of urgent jobs therefore may result in actual urgent jobs not being processed in time. In response, the authors focus on shop floor dispatching stage and consider the transient status of urgent operations in the context of WLC. The urgency of jobs is rejudged at the input buffer of each workstation, which is firstly defined as urgent operations and non-urgent operations. Using simulation, the results show that considering the transient status of urgent operations contributes to speeding up production for actual urgent jobs and meeting delivery performance both in General Flow Shop and Pure Job Shop. In addition, percentage tardy performance is greatly affected by norm levels, especially at the severe urgent level. These have important implications on how urgent operations should be designed and how norm level should be set at shop floor dispatching stage.

Digital servitization is a business model transformation process enabled by the use of digital technologies to create or improve industrial services and product-service offerings by creating value and competitive advantage increasing customer satisfaction and loyalty as well as company revenue streams. 5G networks can enable digital servitization of manufacturing by providing faster, more secure, and more reliable communications between machines, devices, and humans. This paper explores the impact of adopting 5G technologies on servitization and identifies the services that can benefit most from 5G networks. The research consists of two parts: a literature review of the technologies currently used in the design and provision of industrial services that could benefit from 5G networks and an exploratory survey involving manufacturing companies that have started the digital servitization journey. The main results emerging from the research suggest that 5G can profoundly impact services supported by Augmented Reality, Cloud computing, and Cyber-physical systems, mainly concerning maintenance, workforce training, machine diagnosis and monitoring.

In modern industrial systems, diagnosing faults in time and using the best methods becomes increasingly crucial. It is possible to fail a system or to waste resources if faults are not detected or are detected late. Machine learning and deep learning (DL) have proposed various methods for data-based fault diagnosis, and the authors are looking for the most reliable and practical ones. A framework based on DL and reinforcement learning (RL) is developed for fault detection. The authors have utilised two algorithms in their work: Q-Learning and Soft Q-Learning. Reinforcement learning frameworks frequently include efficient algorithms for policy updates, including Q-learning. These algorithms optimise the policy based on the predictions and rewards, resulting in more efficient updates and quicker convergence. The authors can increase accuracy, overcome data imbalance, and better predict future defects by updating the RL policy when new data is received. By applying their method, an increase of 3%–4% in all evaluation metrics by updating policy, an improvement in prediction speed, and an increase of 3%–6% in all evaluation metrics compared to a typical backpropagation multi-layer neural network prediction with comparable parameters is observed. In addition, the Soft Q-learning algorithm yields better outcomes compared to Q-learning.

Bipedal gait control has always been a very challenging issue due to the multi-joint and non-linear structure of humanoid robots and frequent robot–environment interactions. To realise stable and robust bipedal walking, many aspects including robot modelling, gait stability and environmental adaptivity should be considered to design the gait control method. In this paper, a general description of bipedal gait and the corresponding evaluation indicators are introduced. Moreover, the existing bipedal gait control methods are classified into model-based gait, stability criterion-based gait and learning strategy-based gait and a comprehensive review is conducted. Finally, the existing challenges and development trends of bipedal gait control are presented.

Cyberspace has continued to change throughout the 1990s and 2000s, when the Internet became widely used. The concept of a massive, integrated, sustainable, and interconnected cyber world is the heart of the metaverse. The aim of the metaverse is to create a digital world that is analogous to the existing world. Thus, the most recent metaverse development is investigated in light of cutting-edge technologies and metaverse ecosystems. To this end, a pilot survey to provide a first overview of upcoming challenges and opportunities of the metaverse is presented. The results provide researchers with a direction for future study as well as potential applications in the metaverse.