Robotics and Computer-integrated Manufacturing最新文献

{"title":"Superimposed Poisson Distribution Variable Neighborhood Search for Scheduling of Parallel Multi-track Shuttle Loop System","authors":"Wenbin Zhang ,&nbsp;Youshan Liu ,&nbsp;Chunjiang Zhang ,&nbsp;Weiming Shen","doi":"10.1016/j.rcim.2025.103016","DOIUrl":"10.1016/j.rcim.2025.103016","url":null,"abstract":"<div><div>This article presents a layout scenario of parallel multiple tracks shuttle loop system and its scheduling method within an automated storage and retrieval system. Leveraging the motion mathematical model articulated through angular coordinates and track coding, we established a multi-agent simulation environment. The simulation encompasses RGV agents, task assignment agents, track allocation agents, and charging decision-making agents. The actions of individual agents are directly or indirectly guided by a three-tier decision coding method. We also propose a heuristic algorithm, termed Superimposed Poisson Distribution-Variable Neighborhood Search, to optimize system efficiency through Simulation-Based Optimization. Numerical experiments validate the performance of the algorithm using example scenarios of varying scales. Furthermore, we confirm the superior efficiency of parallel multiple track layouts, assess the impact of the number of RGVs on system throughput, and identify the optimal number of RGVs for different track layout configurations. A sensitivity analysis is conducted to explore the effect of physical parameters on system efficiency.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103016"},"PeriodicalIF":9.1,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a continuum robot with inflatable stiffness-adjustable elements for in-situ repair of aeroengines","authors":"Jung-Che Chang,&nbsp;Hengtai Dai,&nbsp;Xi Wang,&nbsp;Dragos Axinte,&nbsp;Xin Dong","doi":"10.1016/j.rcim.2025.103018","DOIUrl":"10.1016/j.rcim.2025.103018","url":null,"abstract":"<div><div>Continuum robots, with their slender configuration and high redundancy, gain increasing interest in industrial applications such as intervention within confined spaces. However, when the robot end effector is required to travel a long distance, the existing products need a large actuation pack and complicated control strategy for a decent accuracy. This paper presents a continuum robot with a novel stiffness-adjustable mechanism designed to address conditions requiring high tip accuracy in long-reach confined spaces. Key innovations include (1) a section capable of inflating its diameter tenfold for the support of a 6-DoF continuum section, (2) a predictive model for a hybrid stiffening arm, and (3) a manual insertion approach that reduces actuation complexity. The proposed design was validated through a prototype that performed repairs on a thermal barrier coating within an aeroengine. During trials, a 12.6 mm diameter arm was inserted through an access port with a diameter of &lt; 15 mm, inflated to 120 mm to securely lock in place, and enabled precise six degrees of freedom (6-DoF) control. The predictive model achieved a Root Mean Square Error below 1.14 mm under payload, demonstrating enhanced positional accuracy compared to traditional continuum robots. These results mark a significant advancement towards robust, precise operations in restricted industrial environments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103018"},"PeriodicalIF":9.1,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel production execution logic model with directed service node pairs and encapsulated service cells for efficient scheduling and simulation in discrete manufacturing shops","authors":"Mingyuan Liu ,&nbsp;Jiaxiang Xie ,&nbsp;Jian Zhang ,&nbsp;Shengfeng Qin ,&nbsp;Guofu Ding ,&nbsp;Haojie Chen","doi":"10.1016/j.rcim.2025.103017","DOIUrl":"10.1016/j.rcim.2025.103017","url":null,"abstract":"<div><div>In discrete manufacturing shops, dynamic uncertainty disturbances necessitate frequent scheduling and simulation, posing significant challenges to the efficiency of traditional methods. Therefore, effective production execution logic models are required to manage these dynamics and enhance the efficiency of scheduling and simulation. However, existing production execution logic models lack comprehensive integration of flows of information, control, and material (FICM), making it difficult to effectively describe the dynamic production execution logic and limiting their ability to optimize scheduling and simulation processes. To address this challenge, by extending the seven-elements (SE) and material node-oriented seven-elements (MNOSE) models, this paper proposes a production execution logic model with directed service node pairs and encapsulated service cells (PELM-DaE). The model achieves the representation and integration of FICM, enabling an effective description of dynamic production execution logic. Based on PELM-DaE, a method for constructing connectivity maps is proposed, which allows the characterization of job execution relationships and constraints and the pre-computation of FICM. Additionally, by dynamically constructing and continuously applying connectivity maps, a connectivity map-based framework is proposed to support efficient scheduling and simulation. Based on the above research content, a software platform is developed to implement the encapsulation of the proposed model and method. The practicality and advantages of the model and method in describing the production execution logic and improving the efficiency of scheduling simulation are verified based on an actual manufacturing shop floor.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103017"},"PeriodicalIF":9.1,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on dynamics modelling and stiffness strengthening method for mobile industrial robot in-situ milling machining","authors":"Yunfei Miao ,&nbsp;Zhuoheng Yang ,&nbsp;Wei Liu ,&nbsp;Wei Tian ,&nbsp;Pinzhang Wang ,&nbsp;Bo Li","doi":"10.1016/j.rcim.2025.103014","DOIUrl":"10.1016/j.rcim.2025.103014","url":null,"abstract":"<div><div>Accurate analysis of the dynamic characteristics of a mobile industrial robot (MIR) is essential for evaluating and enhancing its machining performance. In the case of mobile heavy-load milling industrial robots, the significant weight of the end-effector and periodic external excitations highlight the flexibility of joints and links. This flexibility considerably affects the vibration characteristics and milling quality of the system. This work proposes a new multi-rigid-flexible coupling dynamics model for the MIR that employs the multibody systems transfer matrix method. The overall transfer equations and dynamics response equations for the system are derived. This method is distinguished by its high programmability, low system matrix order, and strong versatility. To validate the proposed method, modal experiments and excitation response tests have been designed in this work. Additionally, the influence of joint stiffness, joint angle, and link flexibility on the dynamic characteristics of the MIR is thoroughly analyzed. An evaluation index is developed to enhance the system's stiffness during milling that integrates both static and dynamic characteristics based on the analysis of these influencing factors. Finally, the feasibility and effectiveness of the stiffness enhancement model are verified after performing various milling experiments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103014"},"PeriodicalIF":9.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semi-active damping for industrial robots","authors":"Michael Neubauer,&nbsp;Christoph Hinze,&nbsp;Alexander Verl","doi":"10.1016/j.rcim.2025.103008","DOIUrl":"10.1016/j.rcim.2025.103008","url":null,"abstract":"<div><div>The dynamic accuracy of industrial robots is significantly influenced by the elastic drive trains of the axes. Their behavior is composed of the coupled dynamics of drive control and gear mechanics. As an undesirable consequence, increasing elasticity leads to growing tracking errors. One approach to reduce tracking errors is semi-active damping. The functional principle is based on damping the gear mechanics by selective braking of an additional actuator. From a drive control perspective, this results in a more favorable system behavior, which, in turn, allows the selection of more performant control parameter values. This leads to better tracking and disturbance behavior. The aim of this paper is to transfer the semi-active damping with a low-cost additional actuator to cascade-controlled industrial robots. For this purpose, a novel semi-active control law is proposed for actuator control. A damping actuator for the first robot axis is designed, design rules are derived, and an integration concept is proposed. Finally, a H<span><math><msub><mrow></mrow><mrow><mi>∞</mi></mrow></msub></math></span> synthesis methodology for simultaneous parameterization of the drive and actuator control is introduced. An experimental validation proves the effectiveness of the solution at axis level resulting in an average 17.3<!--> <!-->% reduction in tracking errors, and in a milling experiment, reducing the average Euclidean tracking error by 42.7<!--> <!-->%.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103008"},"PeriodicalIF":9.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demand-driven hierarchical integrated planning-scheduling control for a mobile robot-operated flexible smart manufacturing system","authors":"Chen Li,&nbsp;Kshitij Bhatta,&nbsp;Muhammad Waseem,&nbsp;Qing Chang","doi":"10.1016/j.rcim.2025.103015","DOIUrl":"10.1016/j.rcim.2025.103015","url":null,"abstract":"<div><div>The rapid advancement of Industry 4.0 has transformed manufacturing, giving rise to Flexible Smart Manufacturing Systems (FSMS) capable of adapting to fluctuating market demands and operational uncertainties—essential for achieving mass customization. However, conventional approaches that separate long-term planning from real-time scheduling struggle to meet the demands of modern manufacturing environments, particularly in adapting to frequent demand fluctuations, managing system complexity, and ensuring rapid responsiveness. To address this challenge, this paper presents a demand-driven hierarchical framework that integrates planning and scheduling for flexible smart manufacturing, enabled by a mobile, multi-skilled, robot-operated system. First, a novel system identification model is developed using behavioral cloning to extract essential system properties that inform decision-making. Next, a coupled dual-loop control structure is introduced: an outer planner loop optimizes robot configurations based on demand forecasts, while an inner scheduler loop dynamically adjusts robot assignments in response to unexpected disruptions. The control strategy leverages the System Property-Infused Multi-Agent Deep Deterministic Policy Gradient (P-MADDPG) algorithm, which integrates dynamic system properties to improve adaptability and decision-making in complex environments. Extensive experiments are carried out to demonstrate the framework's effectiveness in adapting to frequently shifting demands, minimizing resource waste, and achieving superior performance with higher throughput compared to existing approaches, thereby providing a robust solution for integrated planning and scheduling in personalized production.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103015"},"PeriodicalIF":9.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time defect detection and classification in robotic assembly lines: A machine learning framework","authors":"Fadi El Kalach ,&nbsp;Mojtaba Farahani ,&nbsp;Thorsten Wuest ,&nbsp;Ramy Harik","doi":"10.1016/j.rcim.2025.103011","DOIUrl":"10.1016/j.rcim.2025.103011","url":null,"abstract":"<div><div>Manufacturing systems have witnessed a significant transformation with the introduction of Industry 4.0, introducing new capabilities with the emergence of new technologies. One such instance is the proliferation of sensors enabling the generation and acquisition of vast amounts of data, leading to advancements in Artificial Intelligence (AI) for manufacturing. One field profiting from this is that of Time Series Analytics (TSC) which includes forecasting and classification. TSC can be crucial for fault detection and diagnosis in manufacturing systems. However, there are still challenges in utilizing manufacturing datasets to train and deploy classification algorithms for real time classification. As such this paper aims to tackle these challenges by presenting a closed-loop framework for the testing and deployment process of TSC algorithms. This paper also details the feature selection and extraction process outlining specific criteria to be considered throughout. This is done by presenting a new manufacturing dataset acquired from a robotic assembly line and detailing the full process undergone in this study to train and deploy TSC algorithms on that manufacturing system.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103011"},"PeriodicalIF":9.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A five-dimensional digital twin framework driven by large language models-enhanced RL for CNC systems","authors":"Xusheng Lin ,&nbsp;Weiqiang Chen ,&nbsp;Zheng Zhou ,&nbsp;Jinhua Li ,&nbsp;Yiman Zhao ,&nbsp;Xiyang Zhang","doi":"10.1016/j.rcim.2025.103009","DOIUrl":"10.1016/j.rcim.2025.103009","url":null,"abstract":"<div><div>In response to the growing demand for intelligence and digitalization in computer numerical control (CNC) systems, particularly in virtual debugging, performance evaluation, and machining quality optimization within the manufacturing sector, this study explores the mapping process from physical entities in the physical space to twin entities in the digital twin space. It further delves into the data transmission layer that represents the physical mechanisms of these entities. By constructing multi-layered models, digital twin technology facilitates the virtual simulation and personalized services of multi-layer coupled units in CNC systems. However, given the complexity and diversity of internal units in CNC systems, traditional CNC machining systems remain overly reliant on human expertise, while existing digital twin frameworks lack effective representation and efficient optimization methods tailored to the CNC field. This paper proposes a novel five-dimensional framework for digital twins in CNC systems to address these challenges, driven by large language models-assisted enhanced reinforcement learning. The framework leverages the advantages of digital twin technology in dynamic process management and reinforcement learning in intelligent analysis and decision-making. It comprises five key layers: the physical entity layer, the virtual entity layer, the intelligent decision-making layer, the data transmission layer, and the real-time computation layer. It also encompasses multi-domain modeling, including information models, mechanism models, and digital threads, and explores how large language models (LLM) can assist and enhance reinforcement learning in CNC applications. Finally, the study applies the framework to the tool-axis vector planning problem in CNC systems, positioning the LLM as an indirect decision-maker within reinforcement learning. Experimental results demonstrate that integrating LLM-enhanced reinforcement learning algorithms within the CNC system’s digital twin framework effectively reduces tool-axis vector variation rates, thereby decreasing collision interference incidents during machining. To some extent, the proposed digital twin framework’s effectiveness has been validated, providing a valuable approach for the advancement of the CNC system field.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103009"},"PeriodicalIF":9.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning and planning for optimal synergistic human–robot coordination in manufacturing contexts","authors":"Samuele Sandrini ,&nbsp;Marco Faroni ,&nbsp;Nicola Pedrocchi","doi":"10.1016/j.rcim.2025.103006","DOIUrl":"10.1016/j.rcim.2025.103006","url":null,"abstract":"<div><div>Collaborative robotics cells leverage heterogeneous agents to provide agile production solutions. Effective coordination is essential to prevent inefficiencies and risks for human operators working alongside robots. This paper proposes a human-aware task allocation and scheduling model based on Mixed Integer Nonlinear Programming to optimize efficiency and safety starting from the task planning stages. The approach exploits synergies that encode the coupling effects between pairs of tasks executed in parallel by the agents, arising from the safety constraints imposed on robot agents. These terms are learned from previous executions using a Bayesian estimation; the inference of the posterior probability distribution of the synergy coefficients is performed using the Markov Chain Monte Carlo method. The synergy enhances task planning by adapting the nominal duration of the plan according to the effect of the operator’s presence. Simulations and experimental results demonstrate that the proposed method produces improved human-aware task plans, reducing useless interference between agents, increasing human–robot distance, and achieving up to an 18% reduction in process execution time.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103006"},"PeriodicalIF":9.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-phase approach for benefit-driven and correlation-aware service composition allocation in cloud manufacturing","authors":"Chunhua Tang ,&nbsp;Qiang Zhang ,&nbsp;Jiaming Ding ,&nbsp;Shuangyao Zhao ,&nbsp;Mark Goh","doi":"10.1016/j.rcim.2025.103007","DOIUrl":"10.1016/j.rcim.2025.103007","url":null,"abstract":"<div><div>Manufacturing service composition (MSC) is a fundamental component of cloud manufacturing that involves multiple stakeholders and associated services. Stakeholders, viewed as autonomous entities, prioritize both temporary gains and long-term benefits, while service interactions significantly influence the feasibility and quality of MSCs. Effective MSC allocation demands a strategic approach that harmonizes stakeholders’ interests and accounts for service correlations to achieve optimal outcomes. Although previous studies have explored stakeholders’ long- and short-term benefits and service correlations independently, a comprehensive framework that integrates these aspects, aligns diverse interests, and thoroughly examines service correlation impacts remains a significant challenge. To bridge this gap, this study proposes a two-phase approach for benefit-driven and correlation-aware MSC allocation. This approach integrates the long- and short-term benefits of platform operators, service requesters, and resource suppliers, as well as the effects of two types of service correlations, composability-focused and quality-focused, on MSCs. The initial phase constructs a bi-objective optimization model with maximizing operational benefits to filter and recommend MSCs. Composability-focused service correlations are incorporated in the model to ensure MSC feasibility. The second phase refines the optimal MSC selection by matching supply and demand, leveraging quality-focused service correlations to modify MSC quality. A hybrid algorithm, combining an improved fast nondominated sorting genetic algorithm (PANSGA-II) with an enhanced technique for order preference by similarity to the ideal solution (TOPSIS-PR), is developed to solve the two-phase problem. The case study and numerical experiments are conducted to validate the applicability and effectiveness of the proposed approach and algorithm.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 103007"},"PeriodicalIF":9.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}