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This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations.

A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy.

The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems.

This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

This paper aims to solve the problem of the inability to apply learning methods for robot motion skills based on dynamic movement primitives (DMPs) in tasks with explicit environmental constraints, while ensuring the reliability of the robot system.

The authors propose a novel DMP that takes into account environmental constraints to enhance the generality of the robot motion skill learning method. First, based on the real-time state of the robot and environmental constraints, the task space is divided into different regions and different control strategies are used in each region. Second, to ensure the effectiveness of the generalized skills (trajectories), the control barrier function is extended to DMP to enforce constraint conditions. Finally, a skill modeling and learning algorithm flow is proposed that takes into account environmental constraints within DMPs.

By designing numerical simulation and prototype demonstration experiments to study skill learning and generalization under constrained environments. The experimental results demonstrate that the proposed method is capable of generating motion skills that satisfy environmental constraints. It ensures that robots remain in a safe position throughout the execution of generation skills, thereby avoiding any adverse impact on the surrounding environment.

This paper explores further applications of generalized motion skill learning methods on robots, enhancing the efficiency of robot operations in constrained environments, particularly in non-point-constrained environments. The improved methods are applicable to different types of robots.

Despite the proven evidence of ever-growing productivity gains in the manufacturing industry as a result of years of research and investment in advanced technologies, such as robotics, the adoption of robots in construction is still lagging. The existing literature lacks technical frameworks and guidelines that account for the one-of-a-kind nature of construction projects and the myriad of materials and dimensional components in construction activities. This study seeks to address existing technical uncertainty and productivity issues associated with the application of robotics in the assembly-type manufacturing of industrialized construction.

To facilitate the selection of suitable robotic arms for industrialized construction activities, primarily assembly-type manufacturing tasks of offsite production processes, an activity-based ranking system based on axiomatic design principles is proposed. The proposed ranking system utilizes five functional requirements derived from robot characteristics—speed, payload, reach, degrees of freedom and position repeatability—to evaluate robot performance in an industrialized construction task using simulations of a framing station.

Based on design parameters obtained from activity-based simulations, seventy six robotic arms suitable for the framing task were scored and ranked. According to the sensitivity analysis of proposed functional requirements, speed is the key functional requirement that has a notable effect on productivity of a framing station and is thus the determinant in robot performance assessment for framing tasks.

The proposed ranking system is expected to augment automation in construction and serve as a preliminary guideline to help construction professionals in making informed decisions regarding the adoption of robotic arms.

This paper aims to analyse the current state of research to identify the link between Lean Manufacturing and Industry 4.0 (I4.0) technologies to map out different research themes, to uncover research gaps and propose key recommendations for future research, including lessons to be learnt from the integration of lean and I4.0.

A systematic literature review (SLR) is conducted to thematically analyse and synthesise existing literature on Lean Manufacturing–I4.0 integration. The review analysed 60 papers in peer-reviewed journals.

In total, five main research themes were identified, and a thematic map was created to explore the following: the relationship between Lean Manufacturing and I4.0; Lean Manufacturing and I4.0 implication on performance; Lean Manufacturing and I4.0 framework; Lean Manufacturing and I4.0 integration with other methodologies; and application of I4.0 technologies in Lean Manufacturing. Furthermore, various gaps in the literature were identified, and key recommendations for future directions were proposed.

The integration of Lean Manufacturing and I4.0 will eventually bring many benefits and offers superior and long-term competitive advantages. This research reveals the need for more analysis to thoroughly examine how this can be achieved in real life and promote operational changes that ensure enterprises run more sustainably.

The development of Lean Manufacturing and I4.0 integration is still in its infancy, with most articles in this field published in the past two years. The five main research themes identified through thematic synthesis are provided in the original contribution. This provides scholars better insight into the existing literature related to Lean Manufacturing and I4.0, further contributing to defining clear topics for future research opportunities. It also has important implications for industrialists, who can develop more profound and richer knowledge than Lean and I4.0, which would, in turn, help them develop more effective deployment strategies and have a positive commercial impact.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This study aims to analyse the resilience strategy utilized by small and medium-sized enterprises (SMEs), enabling these businesses to effectively adapt their operations in response to varying conditions by providing them with essential resources. SMEs operate in marketplaces that are both dynamic and frequently tumultuous. These markets provide SMEs with a variety of obstacles, including economic ups and downs, advances in technology, evolving customer tastes and new regulatory requirements. SMEs need to create a strategic strategy to survive and grow in such situations. This strategy ought to help strengthen their resiliency and make it possible for them to make the most of emerging opportunities while simultaneously lowering the dangers.

The questionnaires adopted and adapted from previous research served as the basis for gathering the data. The manufacturing industry was polled through the use of questionnaires. To test the hypothesis, the data were analysed using Smart PLS. Through the use of closed-ended questions directed to the proprietors, managers or senior executives of SMEs, data were collected from each and every institution in the sample. Following the examination of the data by means of descriptive analysis and the presentation of several scenarios using information relating to SMEs, the findings were presented.

The ambidextrous strategies that are used by SMEs have a propensity to offer a constructive contribution to SMEs. In this study, it was discovered that ambidexterity, which is defined as the capacity to both seek and capitalise on possibilities, has a significant bearing on the organisational effectiveness of SMEs. The results showed that ambidextrous strategies have a propensity to work as mediators in interactions involving proactive resilience tactics and performance.

The research expands our understanding of how SMEs in the manufacturing sector may improve their performance by concentrating on growing their ambidextrous strategies.

This study provides a plausible explanation of two crucial management mechanisms for enhancing the sustainability of organisational effectiveness. The relationships between ambidextrous capabilities and firm effectiveness are malleable, and this study suggests that nurturing formal and informal relationships may be the key to SMEs' long-term sustainable performance. Improving the knowledge and performance of supply chain systems for SMEs in the manufacturing sector and boosting their competitiveness in domestic and international markets are the practical contributions of this study.

Our comprehension of monitoring, cooperation and innovation within social management was deepened as a result of these facts. In addition, the study conducted in the sector uncovered four essential connections that outline how managers should actively work towards lowering social risks, developing new possibilities and increasing business performance. These capacities and links, when taken as a whole, provide the foundation upon which an integrated framework and five research propositions are built.

This research offers a convincing explanation of fundamental management processes for enhancing the sustainability of organisational effectiveness. This research implies that developing formal and informal interactions may be the key to the sustainable performance of SMEs over the long run. The relationships between ambidextrous capabilities, methods and organisational effectiveness are flexible, and this study also suggests that these relationships may be shaped. The practical contributions made by this research include boosting the understanding and performance of supply chain systems for SMEs as well as the competitive power of these businesses in both local and international markets.