{"title":"Vibration reduction optimisation design of the high-speed elevator car system based on multi-factor horizontal coupling vibration model","authors":"Meihao Chen, Zhaoxi Hong, Junjie Song, Tang Li, Xiuju Song, Yixiong Feng","doi":"10.1049/cim2.70002","DOIUrl":"https://doi.org/10.1049/cim2.70002","url":null,"abstract":"<p>The increasing need for safe and comfortable high-speed elevators due to the rise of super-tall buildings has led to a focus on vibration reduction modelling and optimisation. This article selects factors that have a significant impact on the vibration of high-speed elevator car systems through sensitivity evaluation to form a six-dimensional parameter space and establishes a multi-objective optimisation model for the car system. The Gibbis method and Radial Basis Function neural network are combined to sample and construct surrogate models, respectively. Meanwhile, a BA–EO algorithm that combines Bat algorithm and Extremal optimisation to adapt to a multidimensional parameter space is proposed here. In practical applications, the peak-to-peak value of vibration acceleration, which significantly affects human perception, is chosen as the objective function for vibration reduction optimisation. After optimisation, the vibrations of the car and car frame are decreased by 19% and 9%, respectively, which extend the service life of the high-speed elevator and enhance safety and comfort for passengers.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429471","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}
Meng Yu, Xuetao Liu, Xiaojing Ji, Yucong Ren, Wenjing Guo
{"title":"Integrated berth allocation and quay crane assignment and scheduling problem under the influence of various factors","authors":"Meng Yu, Xuetao Liu, Xiaojing Ji, Yucong Ren, Wenjing Guo","doi":"10.1049/cim2.70001","DOIUrl":"https://doi.org/10.1049/cim2.70001","url":null,"abstract":"<p>As the important resources and equipment of container terminals, berths and quay cranes (QCs) face various challenges in actual operations and their operation efficiency in turn affects the performance of the whole terminal. The authors investigate an integrated berth allocation and QC assignment and scheduling problem under the influence of various factors, including the two main factors of vessel arrival time uncertainty and tide, and the two secondary factors of berth deviation and interference between cranes. To formulate the problem, the authors develop a multi-factor robust scheduling model. A Genetic Algorithm (GA) with Brain Storm Optimisation based on the Contract Net Protocol (CNP) is designed to optimise the berth and QC scheduling scheme. Specifically, the authors use the GA for individual coding and population initialisation, use the brainstorming algorithm for clustering, and introduce the CNP for individual updating. The experimental results show that the designed algorithm can adapt the scheduling plan to complex environments and can improve the service level of terminals.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429470","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}
{"title":"A conceptual framework proposal for the implementation of Prognostic and Health Management in production systems","authors":"Raffaele Abbate, Chiara Franciosi, Alexandre Voisin, Marcello Fera","doi":"10.1049/cim2.12122","DOIUrl":"https://doi.org/10.1049/cim2.12122","url":null,"abstract":"<p>Prognostic and Health Management (PHM) is an emerging maintenance concept that is highly regarded by the scientific community and practitioners, as its adoption can bring economic, technical and environmental benefits to a company. PHM fully reflects the smart maintenance paradigm encompassing data collection, data manipulation, state detection, health assessment, prognostic assessment and advisory generation. Despite the undeniable benefits, there is still a large gap between the scientific and the real world. Several authors have investigated on the barriers to PHM implementation for companies, highlighting among them the lack of systematic approaches to its design and implementation. As a first contribution to this topic, the authors conducted a systematic literature review (SLR) to investigate the use of Decision Support Systems (DSSs) to support the PHM implementation. The SLR highlighted that few DSS had been developed and were limited to critical unit identification, maintenance strategy selection and data acquisition phase of PHM. Therefore, a conceptual framework for PHM implementation was provided as a second contribution. This framework summarises the decisions that should be addressed by a practitioner wishing to implement PHM services; moreover, it could lay the foundations for the development/improvement of the missing/existing DSSs for PHM implementation.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12122","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142428882","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}
{"title":"Laminator trust in human–robot collaboration for manufacturing fibre-reinforced composites","authors":"Laura Rhian Pickard, Michael Elkington","doi":"10.1049/cim2.12123","DOIUrl":"https://doi.org/10.1049/cim2.12123","url":null,"abstract":"<p>Fibre-reinforced composites manufacturing is a large and growing industry, with much of the work carried out manually by skilled human laminators. The physical nature of the work can be significantly deleterious to these workers' health, while growing demand requires increased rates of manufacture. Human–robot collaborative manufacturing offers a potential solution but requires the human to feel confident working with the robot and trust that they will be safe. Successful human trials of two different approaches to collaborative lay-up of fibre-reinforced plastic composites are presented, with tasks representative of manufacturing challenges in industry. Volunteer responses are measured by questionnaires, with users reporting the processes to be safe, simple to use and allowing greater ease of manufacturing than manual-only lay-up.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12123","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324630","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}
Miaomiao Fan, Jianming Yang, Bowen Sun, Yanjun Shi
{"title":"A hierarchical design of complex interactive interface with multi-perception channels for a helmet-mounted display system of vehicle","authors":"Miaomiao Fan, Jianming Yang, Bowen Sun, Yanjun Shi","doi":"10.1049/cim2.70000","DOIUrl":"https://doi.org/10.1049/cim2.70000","url":null,"abstract":"<p>To expedite the modernisation of equipment construction and address practical challenges, such as low efficiency in armoured vehicle passenger information retrieval, diverse perception channels, and inadequate combat effectiveness in traditional vehicle-integrated electronic information systems, the authors aim to transition to a helmet-mounted display system (HMD). On the basis of the target mission stage of military vehicles, the authors have organised the required information items for the vehicle HMD, integrated the hierarchical relationships of interaction interface design elements, and formulated design strategies using the Garrett user experience element model. We have constructed a vehicle HMD interaction interface design model and conducted comparative experiments with typical vehicle electronic display system interfaces. The usability of the model has been verified through eye-tracking experiments and reaction time analysis. Experimental data indicates that the vehicle HMD interactive interface system, guided by the user experience element model, effectively enhances operational performance for passengers, demonstrating superior recognition, search ability, comprehensibility, and rationality. In conclusion, the vehicle HMD interaction interface design model, guided by the user experience element model, meets the requirements of vehicle HMD interaction interface design. It validates the effectiveness and feasibility of transitioning from a traditional vehicle-integrated electronic information system to a vehicle HMD, providing technical support for enhancing display efficiency in future prototype platforms on the prototype platform digital warfare.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324629","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}
{"title":"Dynamic scheduling of hybrid flow shop problem with uncertain process time and flexible maintenance using NeuroEvolution of Augmenting Topologies","authors":"Yarong Chen, Junjie Zhang, Mudassar Rauf, Jabir Mumtaz, Shenquan Huang","doi":"10.1049/cim2.12119","DOIUrl":"https://doi.org/10.1049/cim2.12119","url":null,"abstract":"<p>A hybrid flow shop is pivotal in modern manufacturing systems, where various emergencies and disturbances occur within the smart manufacturing context. Efficiently solving the dynamic hybrid flow shop scheduling problem (HFSP), characterised by dynamic release times, uncertain job processing times, and flexible machine maintenance has become a significant research focus. A NeuroEvolution of Augmenting Topologies (NEAT) algorithm is proposed to minimise the maximum completion time. To improve the NEAT algorithm's efficiency and effectiveness, several features were integrated: a multi-agent system with autonomous interaction and centralised training to develop the parallel machine scheduling policy, a maintenance-related scheduling action for optimal maintenance decision learning, and a proactive scheduling action to avoid waiting for jobs at decision moments, thereby exploring a broader solution space. The performance of the trained NEAT model was experimentally compared with the Deep Q-Network (DQN) and five classical priority dispatching rules (PDRs) across various problem scales. The results show that the NEAT algorithm achieves better solutions and responds more quickly to dynamic changes than DQN and PDRs. Furthermore, generalisation test results demonstrate NEAT's rapid problem-solving ability on test instances different from the training set.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142152345","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}
Lizhen Du, Xintao Wang, Jiaqi Tang, Chuqiao Xu, Guanxing Qin
{"title":"Improved hybrid estimation of distribution algorithm for distributed parallel assembly permutation flow shop scheduling problem","authors":"Lizhen Du, Xintao Wang, Jiaqi Tang, Chuqiao Xu, Guanxing Qin","doi":"10.1049/cim2.12116","DOIUrl":"https://doi.org/10.1049/cim2.12116","url":null,"abstract":"<p>Distributed assembly permutation flow shop scheduling problem is the hot spot of distributed pipeline scheduling research; however, parallel assembly machines are often in the assembly stage. Therefore, we propose and study distributed parallel assembly permutation flow shop scheduling problem (DPAPFSP). This aims to enhance the efficiency of multi-factory collaborative production in a networked environment. Initially, a corresponding mathematical model was established. Then, an improved hybrid distribution estimation algorithm was proposed to minimize the makespan. The algorithm adopts a single-layer permutation encoding and decoding strategy based on the rule of the Earliest Finished Time. A local neighbourhood search based on critical paths is performed for the optimal solution using five types of neighborhood design. A dual sampling strategy based on repetition rates was introduced to ensure the diversity of the population in the later periods of iteration. Simulated annealing searching was applied to accelerate the decline of optimal value. Finally, we conduct simulation experiments using 900 arithmetic cases and compare the simulation experimental data of this algorithm with the other four existing algorithms. The analysis results demonstrate this improved algorithm is very effective and competitive in solving the considered DPAPFSP.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968445","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}
Mohammad Hossein Modirrousta, Mahdi Aliyari Shoorehdeli, Mostafa Yari
{"title":"Imbalanced classification in faulty turbine data: New proximal policy optimisation","authors":"Mohammad Hossein Modirrousta, Mahdi Aliyari Shoorehdeli, Mostafa Yari","doi":"10.1049/cim2.12114","DOIUrl":"https://doi.org/10.1049/cim2.12114","url":null,"abstract":"<p>In industrial and real-world systems, recognising errors and adopting the best approaches are gaining relevance. The authors’ goal is to identify artificial intelligence apps that provide the most reliable and valuable data-based fault detection techniques. A system for fault identification is presented based on reinforcement learning and proximal policy optimisation (PPO). Due to the lack of fault data, one of the key issues with the standard policy is its inability to recognise fault classes; this issue was resolved by modifying the cost equation. Using improved PPO, the authors can improve performance, address data imbalances, and forecast possible failures more accurately. The approach utilises policy-based optimisation, which offers several advantages. Firstly, it directly optimises the advantage quantity, and secondly, it ensures the stability of function approximation. The authors have studied two different turbines in Iran and collected data from them separately when a fault occurred. To demonstrate the efficiency of our algorithm, the authors have included the third and fourth datasets as cyber attack benchmarks. When the authors’ proposed policy is adopted, all evaluation metrics will improve by 3%–4% as compared to the previous policy in the first benchmark, between 20% and 55% in the second benchmark, between 6% and 14% in the third benchmark, and between 4% and 5% in the fourth benchmark, with improved results and prediction times compared to existing studies.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968430","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}
Hongming Cai, Yanjun Dong, Min Zhu, Pan Hu, Haoyuan Hu, Lihong Jiang
{"title":"Intelligent method framework for 3D surface manufacturing in cloud-edge collaboration architecture","authors":"Hongming Cai, Yanjun Dong, Min Zhu, Pan Hu, Haoyuan Hu, Lihong Jiang","doi":"10.1049/cim2.12115","DOIUrl":"10.1049/cim2.12115","url":null,"abstract":"<p>Large and complex workpieces are core components in fields, such as aerospace, shipbuilding, and other industrial applications. However, the main challenge of curved plate processing comes from the difficulty in determining the nonlinear rebound features with structural design parameters. An intelligent method framework is proposed for 3D surface manufacturing in cloud-edge collaboration environment. With the construction of an intelligent generation method for machining parameters, a unified data model is effectively integrated with various discrete data, and an intelligent processing mechanism based on 3D point clouds is constructed. In particular, a prediction method for curved panel rebound is constructed to reduce the manual dependency of the manufacturing process. Finally, a related case study is conducted to verify the framework, and the result shows accuracy, interpretability and reusability advantages over other similar methods.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801945","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}
{"title":"Digital twin-based virtual commissioning for evaluation and validation of a reconfigurable process line","authors":"Suveg V. Iyer, Kuldip Singh Sangwan, Dhiraj","doi":"10.1049/cim2.12111","DOIUrl":"10.1049/cim2.12111","url":null,"abstract":"<p>The benefits of advancements in information and communication technologies have proliferated in manufacturing applications as more industries are migrating towards industry 4.0 compliance. The industry 4.0 process lines should be dynamic and reconfigurable. Digital twin (DT), supported by real-time data, is getting wide acceptance as a tool for monitoring and control of complex processes. Virtual commissioning (VC) has played a vital role in the software-based validation of the control systems. A DT-based VC methodology is proposed to evaluate and validate a reconfigured process line. The proposed new asset is commissioned virtually in the DT environment maintaining other stations and parameters synchronised. The proposed methodology is validated in a modular production system assembly line. A storage and retrieval station is virtually commissioned by the hardware in loop technique in the assembly line DT with a station time error of 1.3% between the VC model and the actual assembly line data. The case study demonstrates the feasibility of the proposed methodology in assessing the impacts due to reconfiguration of a process line. The findings offer significant support to decision makers in taking informed decisions and to reduce unforeseen interruptions resulting from the integration of a new asset with the existing process line.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12111","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813689","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}