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.

The most recent metaverse development is investigated in light of cutting‐edge technologies and metaverse ecosystems.image

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.

(1) A general description of bipedal gait and the corresponding evaluation indicators are introduced. (2) The existing bipedal gait control methods are reviewed comprehensively, including the model‐based gait, stability criterion‐based gait, and learning strategy‐based gait. (3) The existing challenges and development trends of bipedal gait control are presented.image

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.

A framework based on deep learning and reinforcement learning for fault detection is developed. The authors can increase accuracy, overcome data imbalance, and better predict future defects by updating the reinforcement learning policy when new data is received.image

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.

This paper explores the impact of adopting 5G technologies on servitization and identifies the services that can benefit most from 5G networks. 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.image

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.

Misjudgement of urgent jobs may result in actual urgent jobs not being processed in time. This study focuses on shop floor dispatching stage and considers 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.image