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Digital twin and parameter correlation-enabled variant design of production lines

INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2025年第1期38卷 136-157页

作者： Yan, Douxi Yang, Jiafeng Zhu, Xiaofeng Leng, Jiewu Zhang, Ding Lu, Yuqian Liu, Qiang Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipment Guangzhou Peoples R China Guangdong Univ Technol Guangdong Prov Key Lab Comp Integrated Mfg Syst Guangzhou Peoples R China Univ Auckland Dept Mech Engn Auckland New Zealand Guangdong Univ Technol Guangzhou Peoples R China

The rapid transformation of production lines into a new design scheme is the key to improving the market competitiveness of enterprises. The production line is a complex manufacturing system with a complex structure. There are multidisciplinary correlation networks between different design dimensions, such as causality, mapping, and transfer. Clarifying these correlative relations is the key to the design of production line correlation. In this paper, a descriptive system is built for the production line configuration model, the motion model, the control model, and the optimization model, and the design content of production lines is clarified. A design framework of production line correlation based on the digital twin technology is proposed, and an optimization system of design schemes is built in the form of hierarchical iteration. Polychromatic sets are used to identify the relationship between different dimensions. The high-fidelity simulation ability of the digital twin technology is taken advantage of to verify the proposed four-in-one variant design method in the mobile phone welding assembly line.

关键词： Variant design production line digital twin parameter correlation

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Effect of Process Gradients and Process parameter correlation on Mismatch Modeling for Analog IC Design

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IEEE TRANSACTIONS ON ELECTRON DEVICES 2025年

作者： Mcandrew, Colin C. NXP Semicond Chandler AZ 85295 USA Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

The effect of across-wafer process gradients on pair mismatch is generally considered to add an additional, normally distributed, stochastic component. We analyze radial process parameter distributions, which, wafer maps show, are predominant and prove that they give rise to a semi-elliptical, not normal, distribution. Additionally, we discuss different approaches to modeling parameter correlations and the geometry dependence of mismatch and present data that show how the correlation in key mismatch parameters has changed over technology generations.

关键词： Semiconductor device modeling Gaussian distribution correlation Threshold voltage Probability density function Geometry Analytical models Transistors Stochastic processes Semiconductor device measurement Matching parameter correlation process gradients

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parameter correlation in wastewater dispersal area groundwater monitoring wells serving Corolla Light #1 Wastewater Treatment Facility in Currituck County, North Carolina

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ENVIRONMENTAL PRACTICE 2017年第4期19卷 182-195页

作者： Withrow, Lorna C. North Carolina Dept Hlth & Human Serv Div Publ Hlth Raleigh NC USA

More than half of North Carolina's population utilizes groundwater as a drinking water source. Efforts to protect water sources include groundwater monitoring around some of the larger wastewater systems. Samples collected from system monitoring wells are analyzed for selected contaminants, typically outlined in wastewater systems' operation permits. Detection of targeted parameters can result in early intervention of contamination identified through parameter correlation. This investigation focused on wells located around the Corolla Light #1 WWTF in the Corolla, NC. The WWTF has seven system monitoring wells for which sample analyses results were assessed for discernable correlations between parameters. The On-Site Water Protection (OSWP) system is monitored by wells MW-4, MW-5, and MW-6. The Division of Water Resources (DWR) system is monitored by wells MW-1, MW-2, MW-3, and MW-7. The OSWP system utilizes subsurface dispersal and the DWR system utilizes surface dispersal. Monitoring conducted around the areas is reported to OSWP and DWR. Results for samples collected November 2006-2016 were compiled and results for pH, TDS, Cl-, and NO3-examined. Evaluation by regression analyses appeared to indicate no correlation between concentrations of NO3-and the other three parameters. There did appear to be a significant relationship between TDS and Cl- in five of seven wells sampled. Only two wells (MW-1 and MW-7) appeared to have a relationship between pH and both TDS and Cl-.

关键词： Groundwater parameter correlation regression subsurface dispersal monitoring wastewater

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An evaluation of impacts of DEM resolution and parameter correlation on TOPMODEL modeling uncertainty

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JOURNAL OF HYDROLOGY 2010年第3-4期394卷 370-383页

作者： Lin, Kairong Zhang, Qiang Chen, Xiaohong Sun Yat Sen Univ Dept Water Resources & Environm Guangzhou 510275 Guangdong Peoples R China Sun Yat Sen Univ Guangdong High Educ Inst Key Lab Water Cycle & Water Secur So China Guangzhou 510275 Guangdong Peoples R China

Hydrological modeling uncertainties are the results of many factors such as input error calibration accuracy parameter uncertainty model structure and so on Wherein input errors and parameter uncertainties are the two of the major factors influencing the uncertainties of hydrological modeling TOPMODEL is a rainfall-runoff model that bases its distributed predictions on analysis of watershed topography which is widely used in hydrological modeling practices In this study the effects of DEM resolution and parameter correlation on TOPMODEL modeling uncertainties are evaluated by using GLUE technique The uncertainty evaluation is performed by modeling the rainfall-runoff processes of three tributaries in the Hanjiang River one of the major tributaries of the Yangtze River China The results show no evident effects of the DEM resolution on the uncertainty intervals of the TOPMODEL simulation This can be attributed to the fact that the modeling uncertainty is due solely to changes of DEM resolution by fixing the parameter values to avoid the artifacts resulted from interactions between In(a/tan(B)) and the parameters In addition the copula functions are used to produce more behavioral parameter sets for the same sample time intervals when the model parameters are in good correlation and which can benefit thorough evaluation of effects of parameter correlation on the hydrological modeling uncertainty With the same number of the behavioral parameter sets after putting the parameter correlation under consideration the simulated runoff series by the TOPMODEL with the behavioral parameter sets can fit reasonably better the observed runoff series Thus the uncertainty due to parameter correlation of the TOPMODEL modeling can be considerably removed This study is of great theoretical and practical merits in sound understanding of the modeling behaviors of the TOPMODEL under the influences of inputs and parameter correlation (C) 2010 Elsevier B V All rights reserved

关键词： Modeling uncertainty GLUE DEM resolution parameter correlation TOPMODEL

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Three-parameter correlation for the surface tension of saturated liquids

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MODERN PHYSICS LETTERS B 2020年第11期34卷

作者： Chen, Qiuju Tian, Jianxiang Jiang, Hua Qufu Normal Univ Sch Software Engn Dept Phys Qufu 273165 Shandong Peoples R China Linyi Univ Sch Phys & Elect Engn Linyi 276005 Shandong Peoples R China

In this paper, we study the multiple-parameter correlations for the surface tension of saturated liquids. The proposed three-parameter correlation requires only the critical temperature as inputs and is tested by using the NIST REFPROP data for 72 saturated liquids including refrigerants, alkanes and some other simple liquids such as argon, carbon dioxide, etc. It is found that this correlation well stands in the whole temperature range from the triple point to the critical point with high accuracy for 71 liquids with average absolute deviations (AADs) less than 5% and for 66 liquids with AADs less than 1%. These results are clearly better than the ones of other available correlations. This correlation can be directly used to estimate the value of the surface tension of the corresponding liquids at any temperature point from the triple point to the critical point. The accuracy of the predictions would clearly have economic benefits since it would allow improvement of process operating conditions, the development of new processes, the reduction of oversizing in the design of new equipment and even reduction of energy requirements.

关键词： Temperature parameter correlation surface tension saturated liquids refrigerants

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Monte Carlo Based Detection of parameter correlation in Simulation Models

Monte Carlo Based Detection of Parameter Correlation in Simu...

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International Mechatronics Conference

作者： Najman, Jan Brablc, Martin Rajchl, Matej Bastl, Michal Spacil, Tomas Appel, Martin Brno Univ Technol MECHLAB ISMMB FME Brno Czech Republic

ISBN: (纸本)9783030299934;9783030299927

Simulation models which are of high order or are automatically generated via modelling software are usually depended on high number of unknown parameters. In this paper we present a method for detecting correlation between these parameters and identifying the subspace shape for their uncorrelated complements. This can be further used to lower the order of the optimization problem. For our low-order examples the methods' operating principle is visualized and the subspace is shown.

关键词： parameter correlation Model-Based Design parameter estimation Monte Carlo Simulation MATLAB Simulink PCA

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Effect of parameter correlation on risk analysis of wellbore instability in deep igneous formations

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年第PartC期208卷 109521-109521页

作者： Ma, Tianshou Zhang, Yun Qiu, Yi Liu, Yang Li, Zhilin Southwest Petr Univ State Key Lab Oil & Gas Reservoir Geol & Exploita Chengdu 610500 Sichuan Peoples R China Southwest Petr Univ Key Lab Oil & Gas Equipment Minist Educ Chengdu 610500 Sichuan Peoples R China Chuanqing Drilling Engn Co Ltd Drilling & Prod Engn Technol Res Inst CNPC Guanghan 638100 Sichuan Peoples R China

A Permian igneous formation in the Sichuan Basin typically exhibits complex lithology, strong heterogeneity, and strong uncertainty;consequently, there is a very high risk of wellbore collapse during drilling and completion, which would seriously affect the safety, efficiency, and cost of drilling operations. Therefore, to prevent wellbore collapse in Permian igneous rock formations, a risk assessment method of wellbore instability based on reliability theory was proposed, and the effects of parameter correlation on the reliability of wellbore stability were considered. First, profiles of the rock mechanical parameters, formation pore pressure, and in-situ stresses were established by logging interpretation. Second, the optimal probability distribution of each parameter was determined for three typical igneous formations, and the correlation coefficient matrix was obtained using correlation analysis. Third, the effect of parameter correlation was involved to propose a risk analysis method of wellbore instability, where the Monte Carlo method was used for random sampling. Finally, the safe mud weight window of each igneous formation was determined, and the sensitivity of wellbore stability to the parameter mean values and correlation coefficients was analyzed. The results indicate that significant uncertainty and parameter correlation exist for the igneous formations, which clearly affect wellbore stability. The effect is greatest for the breccia formation, followed by the tuff and basalt formations. The correlations between cohesion and internal friction angle and between cohesion and maximum horizontal principal stress are the most important factors affecting collapse pressure, whereas the correlation between the two horizontal stresses is most important for fracture pressure. The results suggest that the effect of parameter correlation on the reliability of wellbore stability in strongly heterogeneous settings cannot be ignored.

关键词： Igneous rocks Wellbore stability parameter correlation Monte Carlo Sensitivity analysis

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EARLY PREDICTION OF REMAINING DISCHARGE TIME FOR LITHIUM-ION BATTERIES CONSIDERING parameter correlation BETWEEN DISCHARGE STAGES

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EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY 2019年第1期21卷 81-89页

作者： Yu, Jinsong Yang, Jie Tang, Diyin Dai, Jing Beihang Univ Sch Automat Sci & Elect Engn 37 Xueyuan Rd Beijing 100191 Peoples R China Collaborat Innovat Ctr Adv Aeroengine Beijing 100191 Peoples R China China Acad Launch Vehicle Technol R&D Ctr 1 Nan Da Hong Men Rd Beijing 100191 Peoples R China

In this paper, we propose a method for making early predictions of remaining discharge time (RDT) that considers information about future battery discharge process. Instead of analyzing the entire degradation process of a battery, as in the existing literature, we obtain the information about future battery condition by decomposing the discharge model into three stages, according to level of voltage loss. correlation between model parameters at the first and last stages of discharge process allows the values of model parameters in the future to be used to predict the value of parameters at early stages of discharge. The particle swarm optimization (PSO) and particle filter (PF) algorithms are employed to update parameters when new voltage data is available. A case study demonstrates that the proposed approach predicts RDT more accurately than the benchmark PF-based prediction method, regardless of the degradation period of the battery.

关键词： Lithium-ion battery parameter correlation particle swarm optimization particle filter remaining discharge time prognostics

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Remaining Useful Life Prediction for Complex Systems With Multiple Indicators Based on Particle Filter and parameter correlation

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IEEE ACCESS 2020年 8卷 215145-215156页

作者： Chen, Shaowei Wang, Meinan Huang, Dengshan Wen, Pengfei Wang, Shengyue Zhao, Shuai Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

In practical applications, the failure of large-scale complex equipment is often caused by the simultaneous degradation of multiple components. It is necessary to predict the remaining useful life (RUL) of the equipment with multiple degradation indicators. This article proposes a new joint-RUL-prediction method in the presence of multiple degradation indicators based on parameter correlation. The stochastic process model is established for each degradation indicator, and the model parameters are estimated by kernel smoothing particle filter (KS-PF) and maximum likelihood estimation (MLE). Meanwhile, to facilitate the dependencies between multiple degradation indicators, correlations of the degradation model parameter between multiple degradation indicators are established in KS-PF. In addition, optimal tuning (OT) is introduced to choose the best kernel parameter. A case study on the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dataset is applied to verify the proposed method, the experiment shows that the proposed joint-RUL-prediction method based on parameter correlation possesses a superior prediction performance compared with that by using a single degradation indicator.

关键词： Degradation Predictive models Stochastic processes correlation Trajectory Uncertainty Training RUL prediction particle filter multiple degradation indicators parameter correlation kernel smoothing

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Economic Evaluation Results Are Substantially Affected by parameter Input correlation

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Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research 2025年

作者： Erin Barker Harriet Fewster Karina Watts Emily Gregg Matthew Taylor York Health Economics Consortium University of York York North Yorkshire UK. Electronic address: erin.barker@york.ac.uk. York Health Economics Consortium University of York York North Yorkshire UK.

BACKGROUND:Probabilistic sensitivity analysis (PSA) is a method to account for uncertainty in cost-effectiveness analysis. The degree of correlation between input parameters is not well reported and is often overlooked in PSA. This means PSA results could be misestimating uncertainty. This study aimed to develop a simple model to explore the impact of input correlation on the incremental cost-effectiveness ratio (ICER) and the reported likelihood of cost effectiveness. METHODS:A Markov model was developed with three different approaches to correlation: no correlation, partial correlation, and perfect correlation. A hypothetical case study was used to explore the impact of each correlation option on the intervention's likelihood of cost effectiveness. Scenario analyses were also used to investigate whether the findings were consistent across different scenarios. RESULTS:The ICER was comparable across the correlation options. In all scenarios, the no correlation option had the most certain decision outcomes, and the perfect correlation option had the least certain likelihood. The proximity of the ICER to the willingness-to-pay threshold influenced the impact of correlation on the PSA results. CONCLUSION:This study shows that the approach towards modelling parameter correlation in PSA has a substantial impact on the level of certainty in model outputs. By ignoring this, the level of certainty of cost effectiveness could be over or understated. Therefore, researchers and decision makers should be careful to consider the potential impact of inter-parameter correlation.

关键词： Cost-effectiveness analysis Markov model parameter correlation Probabilistic sensitivity analysis

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