Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551477
Ilham Rabhi, A. Roussy, F. Pasqualini, C. Alegret
Semiconductor manufacturing is a continuously challenging and competitive industry. It is important to detect any anomalies in the production facilities, or fabs, as they occur to avoid defect accumulations and loss of performance. In this paper we present a literature review of classification methods and detailed the chosen method which is One Class-Support Vector Machine (OC-SVM). This method is used for out-of-control detection in semiconductor manufacturing. The method is tested via an application using industrial data of the studied fab.
{"title":"Out-Of-Control Detection In Semiconductor Manufacturing using One-Class Support Vector Machines","authors":"Ilham Rabhi, A. Roussy, F. Pasqualini, C. Alegret","doi":"10.1109/CASE49439.2021.9551477","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551477","url":null,"abstract":"Semiconductor manufacturing is a continuously challenging and competitive industry. It is important to detect any anomalies in the production facilities, or fabs, as they occur to avoid defect accumulations and loss of performance. In this paper we present a literature review of classification methods and detailed the chosen method which is One Class-Support Vector Machine (OC-SVM). This method is used for out-of-control detection in semiconductor manufacturing. The method is tested via an application using industrial data of the studied fab.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132404728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551427
Yu-Cheng Hsu, Ming C. Lin, C. G. Li
Dynamically self-balancing wheeled robots possess the characteristics of having a small footprint, low base-to-height ratios, high accelerations and speeds, and low costs. They are suitable for working in human-centric environments. As part of our ongoing effort in creating self-balancing wheeled robots, in this article, we reported the development of our latest model – $mathrm{J}4.beta$. In contrast to the previous model – $mathrm{J}4.alpha$, the new model has a greater dynamic mass-to-total ratio; thus, the acceleration and the ultimate speed are both increased. Here, the maximum speed of 4.4 m/s of the motion platform is achievable by $mathrm{J}4.beta$. We analyzed the system dynamics and had confirmations from measurements; a speed servo system was developed based on PID control. To simplify the dynamics of the mobile robot, a stepper motor instead of a DC motor was adopted for the actuation of the dynamic mass; the overall controlled plant could be approximated as a second-order system. To acquire the PID coefficients, a series of road tests were performed in a common office building. A set of suitable PID coefficients was obtained and verified by three speeds: 0.5 m/s, 1 m/s, and 2 m/s. The speed curves exhibited fast ramp-up, low overshoot, setpoint matching, and low oscillation. For regulation testing, a zero speed was set and external disturbance was applied. The robot was witnessed to slow down rapidly and remain stationary without intensive oscillation. While constructing the autonomous navigation and remote control systems for the mobile robot, the sampling rate of the control system was largely upgraded to 4k Hz to achieve a better tracking and regulation ability.
{"title":"Mobility Improvement on the Two-Wheeled Dynamically Balanced Robot – $mathrm{J}4.beta$","authors":"Yu-Cheng Hsu, Ming C. Lin, C. G. Li","doi":"10.1109/CASE49439.2021.9551427","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551427","url":null,"abstract":"Dynamically self-balancing wheeled robots possess the characteristics of having a small footprint, low base-to-height ratios, high accelerations and speeds, and low costs. They are suitable for working in human-centric environments. As part of our ongoing effort in creating self-balancing wheeled robots, in this article, we reported the development of our latest model – $mathrm{J}4.beta$. In contrast to the previous model – $mathrm{J}4.alpha$, the new model has a greater dynamic mass-to-total ratio; thus, the acceleration and the ultimate speed are both increased. Here, the maximum speed of 4.4 m/s of the motion platform is achievable by $mathrm{J}4.beta$. We analyzed the system dynamics and had confirmations from measurements; a speed servo system was developed based on PID control. To simplify the dynamics of the mobile robot, a stepper motor instead of a DC motor was adopted for the actuation of the dynamic mass; the overall controlled plant could be approximated as a second-order system. To acquire the PID coefficients, a series of road tests were performed in a common office building. A set of suitable PID coefficients was obtained and verified by three speeds: 0.5 m/s, 1 m/s, and 2 m/s. The speed curves exhibited fast ramp-up, low overshoot, setpoint matching, and low oscillation. For regulation testing, a zero speed was set and external disturbance was applied. The robot was witnessed to slow down rapidly and remain stationary without intensive oscillation. While constructing the autonomous navigation and remote control systems for the mobile robot, the sampling rate of the control system was largely upgraded to 4k Hz to achieve a better tracking and regulation ability.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131364703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551670
Ning Li, Z. Wang
Because different items of the perishable products have different deterioration extents in an inventory system, the deterioration process of these perishable products cannot be captured accurately by a single number like deterioration rate. Instead, it is more appropriate to capture their deterioration process on different freshness levels by employing the freshness transition function. Especially, time-temperature indicator (TTI) technology can detect the freshness deterioration process accurately. Therefore, the freshness transition function of perishable products can be constructed based on the data collected by the TTIs. The accuracy of a freshness transition function depends on the detection quality of the TTIs deployed in the perishable inventory system and affects the performance of the pricing decision, because this decision is made based on the observation accuracy of the products' freshness. In this research, we develop the method of optimal pricing decision to obtain the maximum total profit based on the freshness transition function. This method is implemented in three steps: constructing the freshness transition function, designing the pricing optimization policy based on Deep Q-network method, and analyzing the impact of the accuracy of the freshness transition function on the performance of the pricing decision. Finally, we conduct some numerical experiments to examine the performance of the proposed optimal pricing method based on the freshness transition function and found that (1) the retailers should increase the price to obtain more total profit within a sale cycle; (2) the accuracy of the freshness transition function has great influence on the proposed pricing optimization policy.
{"title":"Price Optimization for Perishable Products with Freshness Transition Function *","authors":"Ning Li, Z. Wang","doi":"10.1109/CASE49439.2021.9551670","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551670","url":null,"abstract":"Because different items of the perishable products have different deterioration extents in an inventory system, the deterioration process of these perishable products cannot be captured accurately by a single number like deterioration rate. Instead, it is more appropriate to capture their deterioration process on different freshness levels by employing the freshness transition function. Especially, time-temperature indicator (TTI) technology can detect the freshness deterioration process accurately. Therefore, the freshness transition function of perishable products can be constructed based on the data collected by the TTIs. The accuracy of a freshness transition function depends on the detection quality of the TTIs deployed in the perishable inventory system and affects the performance of the pricing decision, because this decision is made based on the observation accuracy of the products' freshness. In this research, we develop the method of optimal pricing decision to obtain the maximum total profit based on the freshness transition function. This method is implemented in three steps: constructing the freshness transition function, designing the pricing optimization policy based on Deep Q-network method, and analyzing the impact of the accuracy of the freshness transition function on the performance of the pricing decision. Finally, we conduct some numerical experiments to examine the performance of the proposed optimal pricing method based on the freshness transition function and found that (1) the retailers should increase the price to obtain more total profit within a sale cycle; (2) the accuracy of the freshness transition function has great influence on the proposed pricing optimization policy.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134546648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551642
Yue Li, Zilong Zhuang, W. Qin
With the continuous growth of express demand, the impact of its fluctuations is becoming more and more significant. The traditional H&S networks cannot respond intelligently to the demand changes. Therefore, a new network design method combining information and automation needs to be developed urgently. This paper considers a multi-hub version and proposes a hybrid network to dynamically design the hubs' locations and the straight connections between nodes. A mixed integer linear programming model is formulated, and a two-stage genetic algorithm is developed to solve the small and large-scale instances of the hybrid H&S network design problem. The MILP and heuristic algorithm are tested on instances provided by an express delivery giant from China. Experimental results verify the effectiveness and economy of the hybrid H&S network and the ability of the proposed heuristic algorithm to quickly find the approximate optimal solution.
{"title":"The Design of Hybrid Hub-and-spoke Networks for Large-scale Dynamic Express Logistics: A Case Study of Chinese Express*","authors":"Yue Li, Zilong Zhuang, W. Qin","doi":"10.1109/CASE49439.2021.9551642","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551642","url":null,"abstract":"With the continuous growth of express demand, the impact of its fluctuations is becoming more and more significant. The traditional H&S networks cannot respond intelligently to the demand changes. Therefore, a new network design method combining information and automation needs to be developed urgently. This paper considers a multi-hub version and proposes a hybrid network to dynamically design the hubs' locations and the straight connections between nodes. A mixed integer linear programming model is formulated, and a two-stage genetic algorithm is developed to solve the small and large-scale instances of the hybrid H&S network design problem. The MILP and heuristic algorithm are tested on instances provided by an express delivery giant from China. Experimental results verify the effectiveness and economy of the hybrid H&S network and the ability of the proposed heuristic algorithm to quickly find the approximate optimal solution.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131987231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551585
Tajima Shungo, H. Date
This study addresses the problem of automating the sewing process in the garment industry. While automatic feeding during sewing has been achieved, overlapping and feeding two a pair of cloths still require a human operator. The difficulty lies in manipulating a soft material. Instead of using a generic robot finger, we use a horizontal dual-arm manipulator with rollers as end effectors, which always hold down the cloth during manipulation. We validated our system through experiments with a prototype that can feed and sew a single piece of cloth in a single operation.
{"title":"Development of Fabric Feed Mechanism Using Horizontal Articulated Dual Manipulator for Automated Sewing","authors":"Tajima Shungo, H. Date","doi":"10.1109/CASE49439.2021.9551585","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551585","url":null,"abstract":"This study addresses the problem of automating the sewing process in the garment industry. While automatic feeding during sewing has been achieved, overlapping and feeding two a pair of cloths still require a human operator. The difficulty lies in manipulating a soft material. Instead of using a generic robot finger, we use a horizontal dual-arm manipulator with rollers as end effectors, which always hold down the cloth during manipulation. We validated our system through experiments with a prototype that can feed and sew a single piece of cloth in a single operation.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133588542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551567
Rebecca Clain, Valeria Borodin, Michel Juge, A. Roussy
Nowadays, virtual metrology models for semiconductor manufacturing aim to be scalable. A Virtual Metrology (VM) system is intended to cover a wide spectrum of production contexts. However, due to the large numbers of possible combinations of recipes, tools and chambers, it becomes intractable to model each context separately. This work presents a VM modeling approach based on the paradigm of transfer learning in a fragmented production context. The approach exploits a 2-Dimensional Convolutional Neural Network (2D-CNN) architecture, namely Spatial Pyramid Pooling Network (SPP-net), to perform the transfer learning from source to target domains with input of different sizes. We implemented several transfer learning strategies on a benchmark dataset provided by the Prognostics and Health Management competition in 2016. The main key points of the proposed approach are discussed based on the findings gathered from the numerical analysis.
{"title":"Virtual metrology for semiconductor manufacturing: Focus on transfer learning","authors":"Rebecca Clain, Valeria Borodin, Michel Juge, A. Roussy","doi":"10.1109/CASE49439.2021.9551567","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551567","url":null,"abstract":"Nowadays, virtual metrology models for semiconductor manufacturing aim to be scalable. A Virtual Metrology (VM) system is intended to cover a wide spectrum of production contexts. However, due to the large numbers of possible combinations of recipes, tools and chambers, it becomes intractable to model each context separately. This work presents a VM modeling approach based on the paradigm of transfer learning in a fragmented production context. The approach exploits a 2-Dimensional Convolutional Neural Network (2D-CNN) architecture, namely Spatial Pyramid Pooling Network (SPP-net), to perform the transfer learning from source to target domains with input of different sizes. We implemented several transfer learning strategies on a benchmark dataset provided by the Prognostics and Health Management competition in 2016. The main key points of the proposed approach are discussed based on the findings gathered from the numerical analysis.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115328898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551581
R. Corsini, Antonio Costa, S. Fichera
This paper deals with a comparison of production control policies in a two-product two-echelon supply chain dynamic problem with production capacity constraint. The factory related echelon consists of an unreliable manufacturing system that cannot produce both types of products simultaneously. Therefore, changeover operations are required to switch from one type of product to another. The decision on the product changeover depends on the production control policy. This research compares the well-known Hedging Corridor Policy, which has been previously adopted by the literature in a supply chain with production capacity constraints, and the Improved Modified Hedging Corridor Policy, which has been proved to minimize the total cost incurred in manufacturing companies characterized by unreliable production systems with constant demand rate. For comparison purposes, an experimental campaign was conducted through an analytical model based on discrete-time difference equations to investigate the Fill Rate of the multi-product supply chain as response variable. A proper ANDVA analysis and a set of interval plots revealed that the Hedging Corridor Policy outperforms the Improved Modified Hedging Corridor Policy in improving the Fill Rate Indicator.
{"title":"Comparing production control policies in two-product supply chain dynamics","authors":"R. Corsini, Antonio Costa, S. Fichera","doi":"10.1109/CASE49439.2021.9551581","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551581","url":null,"abstract":"This paper deals with a comparison of production control policies in a two-product two-echelon supply chain dynamic problem with production capacity constraint. The factory related echelon consists of an unreliable manufacturing system that cannot produce both types of products simultaneously. Therefore, changeover operations are required to switch from one type of product to another. The decision on the product changeover depends on the production control policy. This research compares the well-known Hedging Corridor Policy, which has been previously adopted by the literature in a supply chain with production capacity constraints, and the Improved Modified Hedging Corridor Policy, which has been proved to minimize the total cost incurred in manufacturing companies characterized by unreliable production systems with constant demand rate. For comparison purposes, an experimental campaign was conducted through an analytical model based on discrete-time difference equations to investigate the Fill Rate of the multi-product supply chain as response variable. A proper ANDVA analysis and a set of interval plots revealed that the Hedging Corridor Policy outperforms the Improved Modified Hedging Corridor Policy in improving the Fill Rate Indicator.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121205154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551468
Jing Huang, Q. Chang, J. Arinez
Product completion time is a random variable resulting from the random disturbances in production systems that delay the processing of products unexpectedly. Existing methods for product completion time prediction mostly predict its mean value. However, mean value only accounts for the first moment of a probability distribution, and is not sufficient for depicting the full spread of the product completion time. In this paper, we propose a novel method for predicting the probability distribution of production completion time by combining system model and deep learning. The original data collected from the plant floor are boosted through a model-based oversampling process. The location family of Tweedie distribution is discovered to fit the distribution of product competition time well. A hybrid framework is established to predict distribution parameters given system state as input, so as to predict the completion time distributions in a real-time fashion. The location parameter is analytically evaluated with system model. Other parameters are predicted or determined with data-driven methods, including a long-short term memory network and classic Tweedie prediction techniques.
{"title":"Predicting the Distribution of Product Completion Time in Multi-Product Manufacturing Systems","authors":"Jing Huang, Q. Chang, J. Arinez","doi":"10.1109/CASE49439.2021.9551468","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551468","url":null,"abstract":"Product completion time is a random variable resulting from the random disturbances in production systems that delay the processing of products unexpectedly. Existing methods for product completion time prediction mostly predict its mean value. However, mean value only accounts for the first moment of a probability distribution, and is not sufficient for depicting the full spread of the product completion time. In this paper, we propose a novel method for predicting the probability distribution of production completion time by combining system model and deep learning. The original data collected from the plant floor are boosted through a model-based oversampling process. The location family of Tweedie distribution is discovered to fit the distribution of product competition time well. A hybrid framework is established to predict distribution parameters given system state as input, so as to predict the completion time distributions in a real-time fashion. The location parameter is analytically evaluated with system model. Other parameters are predicted or determined with data-driven methods, including a long-short term memory network and classic Tweedie prediction techniques.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124935516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551465
O. Omisore, Wenjing Du, Wenke Duan, Thanh-Nhon Do, Rita Orji, Lei Wang
Recent insights from human-robot intelligence and deep learning raise hope towards task-specific autonomy in robotic intravascular coronary interventions. However, lack of learning-based methods for characterizing the interventionists' kinesthetic data hinders the drive for shared control and robotic autonomy during cyborg catheterization. In this study, a deep multimodal network model is proposed for classification and recognition of interventionists' hand movements during cyborg intravascular catheterization. The model has two modules for extracting salient features in electromyography signal datasets, and classification of hand motions made during intravascular catheterization procedures. Network training and evaluation observed for in-vitro and in-vivo datasets obtained from trained novice subjects and expert with about 5 years of experience in percutaneous coronary interventions. Performance evaluation shows the learning model could classify interventionists' hand movements accurately in manual and robot-assisted navigations, respectively. This study is suggested to further stimulate the development of appropriate skill level assessments towards cyborg catheterization for cardiac interventions.
{"title":"A Deep Multimodal Network for Classification and Identification of Interventionists' Hand Motions during Cyborg Intravascular Catheterization","authors":"O. Omisore, Wenjing Du, Wenke Duan, Thanh-Nhon Do, Rita Orji, Lei Wang","doi":"10.1109/CASE49439.2021.9551465","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551465","url":null,"abstract":"Recent insights from human-robot intelligence and deep learning raise hope towards task-specific autonomy in robotic intravascular coronary interventions. However, lack of learning-based methods for characterizing the interventionists' kinesthetic data hinders the drive for shared control and robotic autonomy during cyborg catheterization. In this study, a deep multimodal network model is proposed for classification and recognition of interventionists' hand movements during cyborg intravascular catheterization. The model has two modules for extracting salient features in electromyography signal datasets, and classification of hand motions made during intravascular catheterization procedures. Network training and evaluation observed for in-vitro and in-vivo datasets obtained from trained novice subjects and expert with about 5 years of experience in percutaneous coronary interventions. Performance evaluation shows the learning model could classify interventionists' hand movements accurately in manual and robot-assisted navigations, respectively. This study is suggested to further stimulate the development of appropriate skill level assessments towards cyborg catheterization for cardiac interventions.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129226706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551416
Feifan Wang, Yu-Li Huang, Feng Ju
Proton therapy is a highly targeted radiation treatment for tumors. In a typical proton therapy system, multiple gantries share a beam accelerator. A patient is often called back to a gantry immediately after the gantry becomes available, and each treatment requires multiple beams. This causes gantries to compete for the beam and results in long beam wait time, which negatively impacts treatment quality and patient satisfaction. In this study, we propose a rollout-based gantry call-back control method, considering both beam wait time and beam utilization. When a gantry becomes available, an optimal call-back delay time is applied to mitigate beam request conflicts. Simulation experiments suggest the proposed method can be used to find the trade-off between beam wait time and the bean utilization and improve proton therapy care delivery process.
{"title":"Rollout-based Gantry Call-back Control for Proton Therapy Systems","authors":"Feifan Wang, Yu-Li Huang, Feng Ju","doi":"10.1109/CASE49439.2021.9551416","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551416","url":null,"abstract":"Proton therapy is a highly targeted radiation treatment for tumors. In a typical proton therapy system, multiple gantries share a beam accelerator. A patient is often called back to a gantry immediately after the gantry becomes available, and each treatment requires multiple beams. This causes gantries to compete for the beam and results in long beam wait time, which negatively impacts treatment quality and patient satisfaction. In this study, we propose a rollout-based gantry call-back control method, considering both beam wait time and beam utilization. When a gantry becomes available, an optimal call-back delay time is applied to mitigate beam request conflicts. Simulation experiments suggest the proposed method can be used to find the trade-off between beam wait time and the bean utilization and improve proton therapy care delivery process.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130766676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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