2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )最新文献_第10页

Enabling Component Reuse in Model-based System Engineering of Cyber-Physical Production Systems 在基于模型的信息物理生产系统工程中实现组件复用

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613572

Stefano Spellini, Sebastiano Gaiardelli, M. Lora, F. Fummi

{"title":"Enabling Component Reuse in Model-based System Engineering of Cyber-Physical Production Systems","authors":"Stefano Spellini, Sebastiano Gaiardelli, M. Lora, F. Fummi","doi":"10.1109/ETFA45728.2021.9613572","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613572","url":null,"abstract":"Manufacturing lines are evolving into complex cyber-physical production systems. However, their growth in complexity is not matched by the development of structured modeling and design methodologies. In particular, approaches exploiting both models typical of the manufacturing domain and models used by computer engineers are still missing. In this work, we outline a design flow contemplating the reuse of already existing manufacturing lines' models, while designing novel advanced production systems. To enable such a flow, we propose a methodology extracting System Modeling Language (SysML) structural diagrams from AutomationML descriptions. Then, we propose to design the system functionalities on top of the produced diagrams. The paper shows the application of the methodology to a concrete manufacturing line, the structure of which was originally modeled using AutomationML. To exemplify the advantages of the methodology, we exploit the models being generated to automatically extract a digital twin for the production system transportation line. The resulting digital twin is compliant with a well-known plant simulation tool.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126588798","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}

引用次数: 3

Knowledge-Based Digital Twin for Predicting Interactions in Human-Robot Collaboration 基于知识的数字孪生预测人机协作中的交互

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613342

T. Tuli, Linus Kohl, S. Chala, M. Manns, Fazel Ansari

{"title":"Knowledge-Based Digital Twin for Predicting Interactions in Human-Robot Collaboration","authors":"T. Tuli, Linus Kohl, S. Chala, M. Manns, Fazel Ansari","doi":"10.1109/ETFA45728.2021.9613342","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613342","url":null,"abstract":"Semantic representation of motions in a human-robot collaborative environment is essential for agile design and development of digital twins (DT) towards ensuring efficient collaboration between humans and robots in hybrid work systems, e.g., in assembly operations. Dividing activities into actions helps to further conceptualize motion models for predicting what a human intends to do in a hybrid work system. However, it is not straightforward to identify human intentions in collaborative operations for robots to understand and collaborate. This paper presents a concept for semantic representation of human actions and intention prediction using a flexible task ontology interface in the semantic data hub stored in a domain knowledge base. This semantic data hub enables the construction of a DT with corresponding reasoning and simulation algorithms. Furthermore, a knowledge-based DT concept is used to analyze and verify the presented use-case of Human-Robot Collaboration in assembly operations. The preliminary evaluation showed a promising reduction of time for assembly tasks, which identifies the potential to i) improve efficiency reflected by reducing costs and errors and ultimately ii) assist human workers in improving decision making. Thus the contribution of the current work involves a marriage of machine learning, robotics, and ontology engineering into DT to improve human-robot interaction and productivity in a collaborative production environment.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131357433","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}

引用次数: 13

End System TSN Enablement Using OPC UA 通过OPC UA使能TSN

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613458

Alexander Gogolev, Roland Braun

引用次数: 2

Adaptive Decoupling of Multivariable Systems Using Extremum-Seeking Approach* 基于极值求法的多变量系统自适应解耦*

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613455

Amirreza Zaman, W. Birk, K. Atta, Martin Mörtsell

引用次数: 1

Automated Dependency Resolution for Dynamic Reconfiguration of IEC 61499 IEC 61499动态重配置的自动依赖解析

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613156

Laurin Prenzel, S. Steinhorst

引用次数: 8

Design of a framework for enabling TSN support in heterogeneous platforms with virtualization and preliminary experimental results 基于虚拟化的异构平台TSN支持框架设计及初步实验结果

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613442

Bartolomeo Caruso, Luca Leonardi, L. L. Bello, Gaetano Patti

引用次数: 1

Requirements for an energy data information model for a communication-independent device description 用于通信无关设备描述的能源数据信息模型的要求

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613401

M. Runge, Leif-Thore Reiche, Karl-Heinz Niemann, A. Fay, Andreas Würger

引用次数: 4

AI environment for predictive maintenance in a manufacturing scenario 在制造场景中用于预测性维护的AI环境

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613359

R. Rossini, Gianluca Prato, Davide Conzon, C. Pastrone, E. Pereira, João C. P. Reis, G. Gonçalves, D. Henriques, Ana Rita Santiago, A. Ferreira

{"title":"AI environment for predictive maintenance in a manufacturing scenario","authors":"R. Rossini, Gianluca Prato, Davide Conzon, C. Pastrone, E. Pereira, João C. P. Reis, G. Gonçalves, D. Henriques, Ana Rita Santiago, A. Ferreira","doi":"10.1109/ETFA45728.2021.9613359","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613359","url":null,"abstract":"Industries generate and collect a huge amount of data about their processes. Usually such data contain relevant information, which can be used to monitor and analyze the processes, but also improve them, applying optimization techniques that allow to enhance different aspects, such as machine maintenance scheduling, product quality, use of resources and so on and so forth. The Digital Twin (DT) concept has been recently applied in the context of Industry 4.0, to exploit this data, leveraging advanced physical modelling, data analysis, Artificial Intelligence (AI) algorithms for optimization and prediction, which are two key concepts in the Industry 4.0 paradigm. Currently, the major challenge in this field is to make these techniques available for the industries and ensure their ease of use for the final users. This paper presents an holistic solution that combining two open-source software - i.e., REclaim oPtimization and simuLatIon Cooperation in digitAl twin (REPLICA) and Optimization Platform for Refurbishment and Re-manufacturing (OPR2) - provides a flexible, open and easy-to-use AI environment that allows data scientists to create, test, connect and deploy their algorithms and to optimize them. This work presents a first prototype of this solution, then describes how it has been tested and validated with real industry data and finally provides the results obtained with these tests.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134452466","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}

引用次数: 3

Towards Adaptive Inspection for Fraud in I4.0 Supply Chains 面向工业4.0供应链中欺诈行为的适应性检测

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613693

T. Welsh, Faeq Alrimawi, Ali Farahani, Diane Hassett, A. Zisman, B. Nuseibeh

{"title":"Towards Adaptive Inspection for Fraud in I4.0 Supply Chains","authors":"T. Welsh, Faeq Alrimawi, Ali Farahani, Diane Hassett, A. Zisman, B. Nuseibeh","doi":"10.1109/ETFA45728.2021.9613693","DOIUrl":"https://doi.org/10.1109/ETFA45728.2021.9613693","url":null,"abstract":"The effective functioning of society is increasingly reliant on supply chains which are susceptible to fraud, such as the distribution of adulterated products. Inspection is a key tool for mitigating fraud, however it has traditionally been constrained by physical characteristics of supply chains such as their size and geographical distribution. The increasingly cyber-physical nature of supply chains, their autonomy, and their data richness, extends their attack surfaces and thus increases opportunities for fraud. However, it also presents new opportunities for increased and dynamic inspection, which in turn requires more targeted and flexible inspection regimes. In this paper we explore opportunities to engineer adaptive inspection of cyber-physical supply chains to support efforts to reduce fraud. Through using structural representations of supply chains (topological models) we propose defining optimal inspection zones. Such zones circumscribe assets of interest to optimise observation while reducing the intrusiveness of inspection. Using a motivating example of adulterated pharmaceuticals and a proof-of-concept tool we illustrate adaptive inspection, and surface challenges to its realisation, such as value metrics, forensic readiness integration and managing contrasting local and global perspectives.","PeriodicalId":312498,"journal":{"name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133357029","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}

引用次数: 1

Standalone low-cost versatile FPGA-based fault generator for PROFIBUS DP 用于PROFIBUS DP的独立低成本多功能fpga故障发生器

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ) Pub Date : 2021-09-07 DOI: 10.1109/ETFA45728.2021.9613509

Capron Jean-Marc, Mathieu Troch, D. D. Schuyter, A. Verhoeven, J. Knockaert, P. Saey

引用次数: 0