IET Collaborative Intelligent Manufacturing最新文献

Autonomous AI Agents in Industrial Operations: A Systematic Review of Production Scheduling, Predictive Maintenance and Supply Chain Optimisation 工业运营中的自主人工智能代理：生产调度、预测性维护和供应链优化的系统回顾

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-10-10 DOI: 10.1049/cim2.70083

Md. Abdus Shabur

{"title":"Autonomous AI Agents in Industrial Operations: A Systematic Review of Production Scheduling, Predictive Maintenance and Supply Chain Optimisation","authors":"Md. Abdus Shabur","doi":"10.1049/cim2.70083","DOIUrl":"https://doi.org/10.1049/cim2.70083","url":null,"abstract":"The transition from Industry 4.0 to the value-driven human-centric Industry 5.0 paradigm increasingly relies on autonomous AI agents for complex decision-making. However, existing research remains fragmented within isolated operational silos. This systematic review aims to unify this landscape by analysing the deployment of agentic architectures encompassing classical multiagent systems, deep reinforcement learning and large language models (LLMs) across production scheduling, maintenance management and supply chain optimisation. Following PRISMA 2020 guidelines, we systematically analysed 118 peer-reviewed studies published between 2015 and 2026. The findings reveal a critical maturity asymmetry: although agentic methods are highly advanced in diagnostic monitoring and localised execution, a structural ‘deployment gap’ persists at the real-time prescriptive decision-making step across all three domains. This bottleneck is primarily driven by unresolved vulnerabilities in algorithmic explainability, safety verification and cybersecurity. As a central novelty, this review introduces a cross-domain taxonomy that categorises agent architectures and synthesises their shared cyber-physical dependencies, including digital twins, edge-distributed computing and semantic interoperability standards. By evaluating these traditionally isolated literature together, we expose performance discrepancies where identical architectures yield markedly different outcomes depending on the operational context. Finally, we propose a comprehensive research roadmap to bridge the deployment gap, emphasising the need for robust explainable AI (XAI), federated learning for cross-organisational data governance and sociotechnical frameworks that ensure genuine human–agent collaboration. Ultimately, closing this gap is essential for realising the fully self-organising resilient industrial networks envisioned by Industry 5.0.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MPTG-SNN: Membrane Potential Complementarity and Tactile Graph Convolution Integrated Spiking Neural Network for Tactile Recognition MPTG-SNN：膜电位互补与触觉图卷积集成的脉冲神经网络

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-10-06 DOI: 10.1049/cim2.70078

Lin Liu, Liya Yu, Qing Hou, Zukun Yu, Peng Zhang, Pan Yang, Qin Ran

{"title":"MPTG-SNN: Membrane Potential Complementarity and Tactile Graph Convolution Integrated Spiking Neural Network for Tactile Recognition","authors":"Lin Liu, Liya Yu, Qing Hou, Zukun Yu, Peng Zhang, Pan Yang, Qin Ran","doi":"10.1049/cim2.70078","DOIUrl":"https://doi.org/10.1049/cim2.70078","url":null,"abstract":"Event-driven tactile recognition is one of the core challenges in the field of robotic perception and interaction and its central goal is to efficiently perceive the spatio-temporal features of an object's surface through dynamic tactile signals. Spiking neural networks are ideal for tactile recognition modelling due to their advantages in temporal feature extraction from Event-driven data. However, traditional SNN based on LIF neurons suffer from the problem of temporal gradient vanishing during training, which makes it difficult for the model to effectively capture long time-dependent features. To this end, this research proposes a membrane potential complementary neuron model, which significantly alleviates the gradient vanishing problem by introducing complementary membrane potentials, dynamically compensating for membrane potential attenuation and increasing the temporal gradient propagation path. Further, we propose the MPTG-SNN to enhance the spatial correlation of tactile data by constructing a tactile topology convolution structure based on KD-tree. The ablation experiment further evaluated the impact of four gradient approximation functions on capturing the spatiotemporal gradient approximation of MPC neuron activation functions, as well as the effect of two tactile graph construction methods on spatial feature extraction. Experiments on the EvTouch-Containers and EvTouch-Objects datasets showed that the recognition accuracy of MPTG-SNN improvements of 7.5% and 2.23% over the classical TactileSGNet method.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Cross-Sector DigiCircular Digital Twin Architecture for Collaborative and Sustainable Manufacturing 面向协同和可持续制造的跨行业数字循环数字孪生体系结构

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-09-25 DOI: 10.1049/cim2.70082

Antonella Petrillo, Mizna Rehman, Fabio De Felice

{"title":"A Cross-Sector DigiCircular Digital Twin Architecture for Collaborative and Sustainable Manufacturing","authors":"Antonella Petrillo, Mizna Rehman, Fabio De Felice","doi":"10.1049/cim2.70082","DOIUrl":"https://doi.org/10.1049/cim2.70082","url":null,"abstract":"Collaborative intelligent manufacturing enables persistent data-synchronised interaction among distributed industrial systems, creating new opportunities for coordinated and sustainable manufacturing. However, sustainability and circular economy objectives are still largely managed. This paper proposes DT2 (DigiCircular Twin-Transition), a federated digital twin architecture for collaborative and sustainable manufacturing that integrates circular economy intelligence, life-cycle sustainability assessment, and cross-sector interoperability into an integrated decision-making framework. DT2 integrates heterogeneous digital twins from agri-food processing, textile manufacturing, logistics, and blockchain-based traceability into a shared decision layer, allowing environmental and circularity indicators to operate as real-time control variables. A unified sustainability efficiency index (SEI) supports cross-sector comparability and multi-objective optimisation of environmental performance, operational efficiency, and economic outcomes. Simulation-based validation, including Pareto-front analysis and Monte Carlo robustness testing (N = 10,000), demonstrated that, relative to the baseline nonfederated configuration, the evaluated DT2 simulation scenarios achieved reductions of up to 30% in environmental impacts, improvements of up to 25% in resource efficiency, extensions of product lifecycles of up to 20%, and improvements of up to 38% in long-term return on investment. Interoperability and trust are ensured through standards aligned federated architecture (ISO 23247, IEC 62890) and blockchain-backed performance verification. By transforming sustainability from reporting into predictive, collaborative control, DT2 advances the collaborative intelligent manufacturing metaverse towards scalable, auditable and policy-ready industrial sustainability governance.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An LLM-Enabled Human–Machine Collaborative Fault Diagnosis Framework via Industrial AI Agents 基于工业人工智能代理的llm人机协同故障诊断框架

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-09-10 DOI: 10.1049/cim2.70080

Yiming He, Chao Zhao, Yunkang Cao, Weiming Shen

{"title":"An LLM-Enabled Human–Machine Collaborative Fault Diagnosis Framework via Industrial AI Agents","authors":"Yiming He, Chao Zhao, Yunkang Cao, Weiming Shen","doi":"10.1049/cim2.70080","DOIUrl":"https://doi.org/10.1049/cim2.70080","url":null,"abstract":"Intelligent fault diagnosis (FD) of mechanical equipment is vital for ensuring the safety and stability of industrial systems. As modern industrial environments continue to expand in scale and complexity, systematic FD increasingly requires not only accurate signal pattern recognition but also flexible human–machine collaboration for task configuration, model selection and decision optimisation. Traditional static diagnostic systems based on small-scale specialised models (SSMs) are often inadequate for dynamic, multisource and heterogeneous diagnostic tasks. To address these challenges, this paper proposes a large language model (LLM)-enabled human–machine collaborative fault diagnosis framework that combines multimodal task interpretation, signal-source identification and dynamic selection of registered SSMs. The LLM operates at the task-cognition level, whereas structured task checking, model applicability validation and human review for uncertain cases prevent uncertain cognitive outputs from directly triggering deterministic diagnosis. Experiments on two public datasets and an industrial spindle-motor dataset show that the agent achieves 87.33% SSM selection accuracy and 75.00% end-to-end diagnosis accuracy without additional labelled samples for training a separate router, outperforming deterministic rule routing. These results indicate a feasible architecture for heterogeneous industrial diagnosis that combines flexible LLM-based task understanding, deterministic SSM diagnosis and explicit human review for uncertain tasks.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Intelligent Multi-Criteria Framework for Digital Twin Adoption Assessment in Smart Manufacturing via Circular q-Rung Orthopair Fuzzy CoCoFISO Dynamics 基于圆q-Rung Orthopair模糊CoCoFISO动力学的智能制造数字孪生采用评估多准则框架

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-08-27 DOI: 10.1049/cim2.70076

Asma Farhad, Kifayat Ullah, Zeeshan Ali, Yilun Shang

{"title":"An Intelligent Multi-Criteria Framework for Digital Twin Adoption Assessment in Smart Manufacturing via Circular q-Rung Orthopair Fuzzy CoCoFISO Dynamics","authors":"Asma Farhad, Kifayat Ullah, Zeeshan Ali, Yilun Shang","doi":"10.1049/cim2.70076","DOIUrl":"https://doi.org/10.1049/cim2.70076","url":null,"abstract":"Digital twin technologies are gaining importance in modern intelligent manufacturing to facilitate increased efficiency, smartness in manufacturing, and sustainability. Nevertheless, the choice of a suitable digital twin solution is a complicated long-term decision because of the high rate of technological development, integration issues, and financial limitations. To solve these problems, this research proposes a multi-criteria decision-making model based on the circular q-rung orthopair fuzzy compromise of ideal solution (CqROF-CoCoFISO). The proposed model uses circular q-rung orthopair fuzzy sets, which is an effective model for capturing the uncertainty, hesitation and ambiguity that exists in smart manufacturing environments. The most important assessment criteria will be the technological flexibility, compatibility with the system, the cost of implementation, functionality of the system, intellectual property protection, adherence to security and sustainability. The CoCoFISO mechanism will allow ranking competing digital twin alternatives reliably based on conflicting criteria, which will improve the strength and stability of decision-making results. The usefulness of the proposed framework can be proved through a comparative analysis. The findings offer useful information to manufacturing engineers, decision-makers and policymakers aiming at informed and credible digital twin adoption policies in changing industrial conditions.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing Cellular Manufacturing Systems in the Presence of Alternative Process Plans 在存在备选工艺方案的情况下设计元胞制造系统

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-08-24 DOI: 10.1049/cim2.70079

Md. Kutub Uddin, Md. Saiful Islam, Md Abrar Jahin, Md. Tanjid Hossen Irfan, Md. Saiful Islam Seam, M. F. Mridha

{"title":"Designing Cellular Manufacturing Systems in the Presence of Alternative Process Plans","authors":"Md. Kutub Uddin, Md. Saiful Islam, Md Abrar Jahin, Md. Tanjid Hossen Irfan, Md. Saiful Islam Seam, M. F. Mridha","doi":"10.1049/cim2.70079","DOIUrl":"https://doi.org/10.1049/cim2.70079","url":null,"abstract":"In the design of cellular manufacturing systems (CMS), numerous technological and managerial decisions must be made at both the design and operational stages. The first step in designing a CMS involves grouping parts and machines. In this paper, four integer programming formulations are presented for grouping parts and machines in a CMS at both the design and operational levels for a generalised grouping problem, where each part has more than one process plan and each operation of a process plan can be performed on more than one machine. These four integer programming formulations have the ability to simultaneously optimise cell formation and operational routing decisions within a unified framework, whereas prior models often treat these as sequential or independent stages. By integrating machine flexibility and alternative process plans directly into the mathematical objective, this approach ensures a more globally optimal configuration for generalised grouping problems. Minimising inter-cell and intra-cell movements is achieved by assigning as many consecutive operations of a part type as possible to the same cell and machine. This objective is evaluated against alternatives like reducing machine investment and operating costs. Numerical examples demonstrate how the proposed formulations work and highlight their effectiveness in practice.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70079","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TOPSO: A Hybrid Swarm Intelligence and Tabu Search Framework for Multi-Objective Flexible Flow-Shop Scheduling 一种多目标柔性流水车间调度的混合群智能和禁忌搜索框架

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-08-21 DOI: 10.1049/cim2.70073

Syed Abou Iltaf Hussain, Syeda Shamim Shabnam, C. Syamsundar, Jibitesh Kumar Panda, Rajesh K, Bharath Raju L B, S. P. Samal

{"title":"TOPSO: A Hybrid Swarm Intelligence and Tabu Search Framework for Multi-Objective Flexible Flow-Shop Scheduling","authors":"Syed Abou Iltaf Hussain, Syeda Shamim Shabnam, C. Syamsundar, Jibitesh Kumar Panda, Rajesh K, Bharath Raju L B, S. P. Samal","doi":"10.1049/cim2.70073","DOIUrl":"https://doi.org/10.1049/cim2.70073","url":null,"abstract":"Flexible flow-shop scheduling (FFSS) is an NP-hard problem requiring simultaneous optimisation of job sequencing and machine allocation under multiple conflicting objectives. This study proposes TOPSO, a hybrid multi-objective framework integrating Discrete Multi-Objective Particle Swarm Optimisation (DMOPSO), Tabu Search (TS) and the TOPSIS decision-making method. DMOPSO performs global exploration for machine assignment, while TS enhances local exploitation through adaptive neighbourhood search and tabu memory, avoiding premature convergence. TOPSIS selects the best compromise solution from the Pareto front. The proposed model optimises makespan, mean flow time (MFT) and total lateness concurrently. Benchmark evaluations show that TOPSO performs competitively with NSGA-II and MOPSO for small and medium instances, and outperforms them for large-scale problems, achieving reductions of 1.5%–3.2% in makespan and 2.1%–4.8% in total lateness, with lower computational time. A real-world case study with 72 jobs and 5 stages yields a makespan of 2019 min, MFT of 289.11 min and total lateness of 97 min, demonstrating scalability and industrial applicability. This work supports Sustainable Development Goal 9 by enabling efficient and intelligent manufacturing optimisation.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VR Digital Twin of Production With Network Jitter Compensation and Event-Driven WIP Synchronisation 带有网络抖动补偿和事件驱动的在制品同步的VR数字孪生生产

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-08-14 DOI: 10.1049/cim2.70069

Gulshat Amirkhanova, Yenlik Faruzkyzy, Murat Kunelbayev, Bauyrzhan Amirkhanov, Alina Raeva

{"title":"VR Digital Twin of Production With Network Jitter Compensation and Event-Driven WIP Synchronisation","authors":"Gulshat Amirkhanova, Yenlik Faruzkyzy, Murat Kunelbayev, Bauyrzhan Amirkhanov, Alina Raeva","doi":"10.1049/cim2.70069","DOIUrl":"https://doi.org/10.1049/cim2.70069","url":null,"abstract":"This article presents and experimentally validates DT-virtual-flow, a human-centric VR environment designed for production flow simulation and operator training based on a digital twin. The study addresses the key problem of temporal misalignment between physical processes and their DT during data transmission over unstable networks, increasing the risk of critical errors in VR control. To solve this and align with the human-centric principles of Industry 5.0, the authors propose a hybrid human-in-the-loop architecture combining event-driven WIP synchronisation, a VR interface with tactile feedback and a dead reckoning + LERP delay compensation module. This fundamentally distinguishes the solution from traditional snapshot approaches. The integration of heterogeneous equipment is ensured by an HAL abstraction layer based on OPC UA, normalising telemetry for the digital processing pipeline. In a randomised controlled experiment (n = 30), eliminating visual latency reduced critical errors by 76.4% and shortened skill acquisition time by 20.1%. Additionally, the results show a 9.4% increase in OEE, whereas ablation analysis confirmed that disabling network delay compensation leads to a 3.8-fold increase in accident rates. This emphasises the decisive role of algorithmic synchronisation for the safe ergonomic use of VR in next-generation industrial systems.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148754120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating Spatial Augmented Reality Performance and Human-Centricity for Operator 5.0 Assistance in Assembly: Insights From an Empirical Study 评估操作员5.0辅助装配的空间增强现实性能和以人为中心：来自实证研究的见解

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-08-08 DOI: 10.1049/cim2.70075

Chiara Cimini, Francesca Tria, Alexandra Lagorio, Sandra Mattsson, Tamas Ruppert

{"title":"Evaluating Spatial Augmented Reality Performance and Human-Centricity for Operator 5.0 Assistance in Assembly: Insights From an Empirical Study","authors":"Chiara Cimini, Francesca Tria, Alexandra Lagorio, Sandra Mattsson, Tamas Ruppert","doi":"10.1049/cim2.70075","DOIUrl":"https://doi.org/10.1049/cim2.70075","url":null,"abstract":"In the realm of Industry 5.0, the concept of Operator 5.0 emphasises the role of technologies enhancing human capabilities and adaptability. Augmented Reality, which shows potential to improve productivity, cognitive support, and workplace efficiency is one promising technology, being able to provide real-time access to instructions, facilitate assistance, and enhance operator performance. Nevertheless, its industrial adoption faces several challenges, including the need for specialised expertise in system design and concerns regarding the technology’s usability. To fulfil the gaps related to the development of human-centric AR solutions, this study explores the impact of AR-based guidance in assembly processes, through an experimental approach. A test conducted in laboratory involving 24 users demonstrates the AR's effectiveness in reducing errors and achieving high rates of usability, even if time increases in the tasks' completion were observed. The findings offer theoretical and practical insights to foster successful implementation of AR in manufacturing, understanding its benefits and challenges and highlighting its potential to optimise assembly operations and enhance workforce wellbeing and resilience.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Geometric Dimensions in 3D Printed Concrete: BP Neural Network Optimised by Enhanced Crayfish Algorithm 3D打印混凝土几何尺寸预测：增强小龙虾算法优化的BP神经网络

IF 3.3

IET Collaborative Intelligent Manufacturing Pub Date : 2026-08-04 DOI: 10.1049/cim2.70067

Jing He, Shuo Tang, Zongfang Ma, Chao Liu, Lin Song

{"title":"Prediction of Geometric Dimensions in 3D Printed Concrete: BP Neural Network Optimised by Enhanced Crayfish Algorithm","authors":"Jing He, Shuo Tang, Zongfang Ma, Chao Liu, Lin Song","doi":"10.1049/cim2.70067","DOIUrl":"https://doi.org/10.1049/cim2.70067","url":null,"abstract":"3D printed concrete technology has revolutionised construction methods by enabling the fabrication of complex structures. However, complex nonlinear coupling relationships exist among its process parameters, such as extrusion velocity, printing speed and printing height, which critically influence forming accuracy. Therefore, achieving precise prediction of geometric dimensions is essential for high-precision construction. This paper first establishes a nonlinear mapping model between process parameters and geometric dimensions through experiments, effectively addressing the challenge of multi-parameter coupling effects. To overcome the limitations of traditional optimisation algorithms—namely slow convergence in high-dimensional parameter spaces and susceptibility to local optima—this study proposes an (ECOA). This algorithm integrates two key innovations: the exploration phase of the Gorilla Troop Optimiser and the vertical crossover strategy. The ECOA-BPNN model for geometric dimension prediction is constructed using the BP neural network (BPNN) optimised by ECOA. Experimental results demonstrate that among 23 standard test functions and the CEC2019 test function, ECOA achieved global optimal solutions for 18 functions, whereas the fitness values for the remaining functions also outperformed other comparison algorithms, validating the optimisation capability of ECOA. The ECOA-BPNN model significantly outperformed traditional BPNN in prediction accuracy, reducing MAPE and RMSE by 1.2862% and 0.6828%, respectively, and demonstrating its effectiveness in predicting 3D printed concrete geometric dimensions. Based on this model, optimised process parameter combinations were further derived, enabling precise control and high-quality forming.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"8 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0