2017 13th IEEE Conference on Automation Science and Engineering (CASE), 2017
In concert with advances in information and communication technology and their application to man... more In concert with advances in information and communication technology and their application to manufacturing environments, physical entities in factories are acquiring more intelligence via integration with cyber systems. This integration brings about Cyber-Physical Production Systems and leads to smart manufacturing, the next generation manufacturing paradigm. In the new paradigm, high levels of agility, flexibility, and real-time control make it possible to keep the system running efficiently and self-organized. At the same time, however, it becomes difficult in a self-organized and decentralized system to capture the system's status, evaluate the system's performance, and predict the system's future events. In this article, we suggest improvements to smart manufacturing systems where the intelligence from smart entities could be fully utilized without losing system control. To achieve this goal, a solution for integrating schedule-driven production (push systems) and e...
Remaining Useful Life (RUL) estimation is critical in many engineering systems where proper predi... more Remaining Useful Life (RUL) estimation is critical in many engineering systems where proper predictive maintenance is needed to increase a unit's effectiveness and reduce time and cost of repairing. Typically for such systems, multiple sensors are normally used to monitor performance, which create difficulties for system state identification. In this paper, we develop a semi-supervised left-to-right constrained Hidden Markov Model (HMM) model, which is effective in estimating the RUL, while capturing the jumps among states in condition dynamics. In addition, based on the HMM model learned from multiple sensors, we build a Partial Observable Markov Decision Process (POMDP) to demonstrate how such RUL estimation can be effectively used for optimal preventative maintenance decision making. We apply this technique to the NASA Engine degradation data and demonstrate the effectiveness of the proposed method.
IEEE Transactions on Automation Science and Engineering, 2016
ABSTRACT Battery management system has attracted mounting research attention recently, within whi... more ABSTRACT Battery management system has attracted mounting research attention recently, within which cell equalization plays a key role. Although many research and practices have been devoted to developing various structures of cell equalizers, there are still substantial opportunities for performance improvement yet to investigate. In particular, mathematical modeling and systematic analysis of equalizer systems are limited. In this paper, the performance analysis of the modularized global equalizer system for Lithium-ion battery cell equalization is conducted analytically. Specifically, a mathematical model is developed to emulate the equalization dynamics by considering both charging/discharging and energy loss. Analytical formulas are derived to evaluate the performance of the global equalizer. The introduced model is also compared with the state-of-the-art structures in terms of equalization speed and energy loss. Numerical studies show that the modularized global equalization outperforms others by its substantial reduction on energy loss with similar equalization performance and much less equalizers. In addition, a module segmentation guide is provided to facilitate the equalization system design.
ABSTRACT A battery manufacturing system typically includes a serial production line with multiple... more ABSTRACT A battery manufacturing system typically includes a serial production line with multiple inspection stations and repair processes. In such systems, productivity and quality are tightly coupled. Variations in battery quality may stack up along the line so that the upstream quality may impact downstream. The repairing process after each inspection could also affect downstream quality behaviors and may further impose an effect on the throughput of conforming batteries. In this paper, an analytical model of such integrated productivity and quality systems in battery manufacturing is introduced. Analytical methods based on overlapping decomposition approach have been developed to estimate line production rate of conforming batteries. The convergence of the method has been proved analytically and the accuracy of the estimation is justified numerically. In addition, bottleneck identification methods based on the probabilities of blockage, starvation and quality statistics are investigated. Indicators are proposed to identify the downtime and quality bottlenecks without calculation of throughput and quality performance and their sensitivities. These methods have provided a quantitative tool for modeling, analysis, and improvement of productivity and quality in battery manufacturing systems, and can be applied in other manufacturing systems with integrated productivity and quality models.
IEEE Transactions on Automation Science and Engineering, 2014
ABSTRACT Improving quality in large volume battery manufacturing systems for hybrid and electric ... more ABSTRACT Improving quality in large volume battery manufacturing systems for hybrid and electric vehicles is of significant importance. In this paper, we present a flow model to analyze and improve product quality in electrical vehicle battery assembly lines with 100% inspections and repairs for defective parts. Specifically, a battery assembly line consisting of multiple inspection stations is considered. After each inspection, defective parts will be repaired and sent back to the line. A quality flow model is introduced to analyze quality propagations along the battery production line. Analytical expressions of final product quality are derived and structural properties, such as monotonicity and sensitivities, are investigated. A bottleneck identification and mitigation method is introduced to improve quality performance. Finally, a case study is presented to illustrate the applicability of the method.
2010 IEEE International Conference on Automation Science and Engineering, 2010
Page 1. Hybrid/Electric Vehicle Battery Manufacturing: The State-of-the-Art Claudia P. Arenas Gue... more Page 1. Hybrid/Electric Vehicle Battery Manufacturing: The State-of-the-Art Claudia P. Arenas Guerrero, Jingshan Li, Stephan Biller and Guoxian Xiao Abstract Automotive battery manufacturing has become more and more ...
IEEE Transactions on Automation Science and Engineering, 2000
ABSTRACT To achieve this goal, a battery simulation model is needed. Such a model should provide ... more ABSTRACT To achieve this goal, a battery simulation model is needed. Such a model should provide capabilities for performance evaluation and failure prediction, through simulation of cell variations, joint quality, and thermal distributions. It should also enable us to investigate the impacts of both external and internal changes, such as work status (charge, discharge, idle, etc.), temperature, driving profiles, connecting and sealing qualities, etc. In addition, using such a battery model, the quality performance of a manufactured battery can be fed back to design and manufacturing engineers to identify the potential impact of design and improvement of manufactur ing process on battery performance. Currently, models with these capabilities are still not available. Therefore, in this paper, we present a simulation frame work, which is capable of carrying out such functions by incorporating various models to emulate the dynamic changes in battery parameters and inputs. Such a framework is referred to as virtual battery. The model is based on the analysis of coupled kinetics,
2017 13th IEEE Conference on Automation Science and Engineering (CASE), 2017
In concert with advances in information and communication technology and their application to man... more In concert with advances in information and communication technology and their application to manufacturing environments, physical entities in factories are acquiring more intelligence via integration with cyber systems. This integration brings about Cyber-Physical Production Systems and leads to smart manufacturing, the next generation manufacturing paradigm. In the new paradigm, high levels of agility, flexibility, and real-time control make it possible to keep the system running efficiently and self-organized. At the same time, however, it becomes difficult in a self-organized and decentralized system to capture the system's status, evaluate the system's performance, and predict the system's future events. In this article, we suggest improvements to smart manufacturing systems where the intelligence from smart entities could be fully utilized without losing system control. To achieve this goal, a solution for integrating schedule-driven production (push systems) and e...
Remaining Useful Life (RUL) estimation is critical in many engineering systems where proper predi... more Remaining Useful Life (RUL) estimation is critical in many engineering systems where proper predictive maintenance is needed to increase a unit's effectiveness and reduce time and cost of repairing. Typically for such systems, multiple sensors are normally used to monitor performance, which create difficulties for system state identification. In this paper, we develop a semi-supervised left-to-right constrained Hidden Markov Model (HMM) model, which is effective in estimating the RUL, while capturing the jumps among states in condition dynamics. In addition, based on the HMM model learned from multiple sensors, we build a Partial Observable Markov Decision Process (POMDP) to demonstrate how such RUL estimation can be effectively used for optimal preventative maintenance decision making. We apply this technique to the NASA Engine degradation data and demonstrate the effectiveness of the proposed method.
IEEE Transactions on Automation Science and Engineering, 2016
ABSTRACT Battery management system has attracted mounting research attention recently, within whi... more ABSTRACT Battery management system has attracted mounting research attention recently, within which cell equalization plays a key role. Although many research and practices have been devoted to developing various structures of cell equalizers, there are still substantial opportunities for performance improvement yet to investigate. In particular, mathematical modeling and systematic analysis of equalizer systems are limited. In this paper, the performance analysis of the modularized global equalizer system for Lithium-ion battery cell equalization is conducted analytically. Specifically, a mathematical model is developed to emulate the equalization dynamics by considering both charging/discharging and energy loss. Analytical formulas are derived to evaluate the performance of the global equalizer. The introduced model is also compared with the state-of-the-art structures in terms of equalization speed and energy loss. Numerical studies show that the modularized global equalization outperforms others by its substantial reduction on energy loss with similar equalization performance and much less equalizers. In addition, a module segmentation guide is provided to facilitate the equalization system design.
ABSTRACT A battery manufacturing system typically includes a serial production line with multiple... more ABSTRACT A battery manufacturing system typically includes a serial production line with multiple inspection stations and repair processes. In such systems, productivity and quality are tightly coupled. Variations in battery quality may stack up along the line so that the upstream quality may impact downstream. The repairing process after each inspection could also affect downstream quality behaviors and may further impose an effect on the throughput of conforming batteries. In this paper, an analytical model of such integrated productivity and quality systems in battery manufacturing is introduced. Analytical methods based on overlapping decomposition approach have been developed to estimate line production rate of conforming batteries. The convergence of the method has been proved analytically and the accuracy of the estimation is justified numerically. In addition, bottleneck identification methods based on the probabilities of blockage, starvation and quality statistics are investigated. Indicators are proposed to identify the downtime and quality bottlenecks without calculation of throughput and quality performance and their sensitivities. These methods have provided a quantitative tool for modeling, analysis, and improvement of productivity and quality in battery manufacturing systems, and can be applied in other manufacturing systems with integrated productivity and quality models.
IEEE Transactions on Automation Science and Engineering, 2014
ABSTRACT Improving quality in large volume battery manufacturing systems for hybrid and electric ... more ABSTRACT Improving quality in large volume battery manufacturing systems for hybrid and electric vehicles is of significant importance. In this paper, we present a flow model to analyze and improve product quality in electrical vehicle battery assembly lines with 100% inspections and repairs for defective parts. Specifically, a battery assembly line consisting of multiple inspection stations is considered. After each inspection, defective parts will be repaired and sent back to the line. A quality flow model is introduced to analyze quality propagations along the battery production line. Analytical expressions of final product quality are derived and structural properties, such as monotonicity and sensitivities, are investigated. A bottleneck identification and mitigation method is introduced to improve quality performance. Finally, a case study is presented to illustrate the applicability of the method.
2010 IEEE International Conference on Automation Science and Engineering, 2010
Page 1. Hybrid/Electric Vehicle Battery Manufacturing: The State-of-the-Art Claudia P. Arenas Gue... more Page 1. Hybrid/Electric Vehicle Battery Manufacturing: The State-of-the-Art Claudia P. Arenas Guerrero, Jingshan Li, Stephan Biller and Guoxian Xiao Abstract Automotive battery manufacturing has become more and more ...
IEEE Transactions on Automation Science and Engineering, 2000
ABSTRACT To achieve this goal, a battery simulation model is needed. Such a model should provide ... more ABSTRACT To achieve this goal, a battery simulation model is needed. Such a model should provide capabilities for performance evaluation and failure prediction, through simulation of cell variations, joint quality, and thermal distributions. It should also enable us to investigate the impacts of both external and internal changes, such as work status (charge, discharge, idle, etc.), temperature, driving profiles, connecting and sealing qualities, etc. In addition, using such a battery model, the quality performance of a manufactured battery can be fed back to design and manufacturing engineers to identify the potential impact of design and improvement of manufactur ing process on battery performance. Currently, models with these capabilities are still not available. Therefore, in this paper, we present a simulation frame work, which is capable of carrying out such functions by incorporating various models to emulate the dynamic changes in battery parameters and inputs. Such a framework is referred to as virtual battery. The model is based on the analysis of coupled kinetics,
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