2019 IEEE 17th International Conference on Industrial Informatics (INDIN)最新文献

Embedded systems for time–critical applications over Wi-Fi: design and experimental assessment 嵌入式系统的时间关键应用在Wi-Fi:设计和实验评估

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972168

Francesco Branz, R. Antonello, F. Tramarin, Tommaso Fedullo, S. Vitturi, L. Schenato

{"title":"Embedded systems for time–critical applications over Wi-Fi: design and experimental assessment","authors":"Francesco Branz, R. Antonello, F. Tramarin, Tommaso Fedullo, S. Vitturi, L. Schenato","doi":"10.1109/INDIN41052.2019.8972168","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972168","url":null,"abstract":"Networked embedded systems for industrial control based on wireless support provide several advantages over wired counterparts, but often reveal unsuitable for the most demanding industrial control applications, such as advanced manufacturing and cooperative robotics. Data exchange over IEEE 802.11 networks may theoretically represent an appropriate solution for time–critical applications, provided that unreliability and non– determinism issues are properly handled. In this respect, this paper hence proposes an original solution, based on a cross– layer approach, to allow the realization of high–speed industrial control–over–Wi-Fi networked embedded systems. The proposal implements a novel robust frame–delay state estimator, a time efficient communication policy, and a specific tuning of critical protocol parameters. Suitable hardware–in–the–loop experiments have been carried out implemented exploiting two different embedded systems. Preliminary results show that the proposed architecture enables industrial control applications requiring a sampling rate of up to 1 kHz, even in presence of non negligible communication errors.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115360002","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 automatic state machine reconstruction from legacy PLC using data collection 利用数据收集实现对传统PLC的自动状态机重建

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972143

D. Chivilikhin, Sandeep Patil, Anthony Cordonnier, V. Vyatkin

引用次数: 2

Machine Learning Applied to an Intelligent and Adaptive Robotic Inspection Station 机器学习在智能自适应机器人检测站中的应用

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972298

Luis Variz, Luis Piardi, P. J. Rodrigues, P. Leitão

{"title":"Machine Learning Applied to an Intelligent and Adaptive Robotic Inspection Station","authors":"Luis Variz, Luis Piardi, P. J. Rodrigues, P. Leitão","doi":"10.1109/INDIN41052.2019.8972298","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972298","url":null,"abstract":"Industry 4.0 promotes the use of emergent technologies, such as Internet of Things (IoT), Big Data, artificial intelligence (AI) and cloud computing, sustained by cyber-physical systems to reach smart factories. The idea is to decen-tralize the production systems and allow to reach monitoring, adaptation and optimization to be made in real time, based on the large amount of data available at shop floor that feed the use of machine learning techniques. This technological revolution will bring significant productivity gains, resources savings and reduced maintenance costs, as machines will have information to operate more efficiently, adaptable and following demand fluctuations. This paper discusses the application of supervised Machine Learning techniques allied with artificial vision, to implement an intelligent, collaborative and adaptive robotic inspection station, which carries out the quality control of Human Machine Interface (HMI) consoles, equipped with pressure buttons and LCD displays. Machine learning techniques were applied for the recognition of the operator’s face, to classify the type of HMI console to be inspected, to classify the state condition of the pressure buttons and detect anomalies in the LCD displays. The developed solution reaches promising results, with almost 100% accuracy in the correct classification of the consoles and anomalies in the pressure buttons, and also high values in the detection of defects in the LCD displays.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123086436","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: 6

An Approach for adapting a Cobot Workstation to Human Operator within a Deep Learning Camera 深度学习相机中协作机器人工作站适应人类操作者的方法

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972238

Olatz De Miguel Lázaro, Wael M. Mohammed, Borja Ramis, Ronal Bejarano, J. Lastra

{"title":"An Approach for adapting a Cobot Workstation to Human Operator within a Deep Learning Camera","authors":"Olatz De Miguel Lázaro, Wael M. Mohammed, Borja Ramis, Ronal Bejarano, J. Lastra","doi":"10.1109/INDIN41052.2019.8972238","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972238","url":null,"abstract":"One of the major objectives of international projects in the field of Industrial Automation is to achieve a proper and safe human-robot collaboration. This will permit the coexistence of both humans and robots at factory shop floors, where each one has a clear role along the industrial processes. It’s a matter of fact that machines, including robots, have specific features that determine the kind of operation(s) that they can perform better. Similarly, human operators have a set of skills and knowledge that permits them to accomplish their tasks at work. This article proposes the adaptation of robots to the skills of human operators in order to implement an efficient, safe and comfortable synergy between robots and humans that are working at the same workspace. As a representative case of study, this research work describes an approach for adapting a cobot workstation to human operators within an installed deep learning camera on the cobot. First, the camera is used to recognize the human operator that collaborates with the robot. Then, the corresponding profile is processed and serves as an input to a module in charge of adapting specific features of the robot. In this manner, the robot can adapt e.g., to the speed of operation according to the skills of the worker or deliver parts to be manipulated according to the handedness of the human worker. In addition, the deep learning camera is used for stopping the process at any time that the worked leaves unexpectedly the workstation.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115754868","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: 14

Formalization of natural language requirements into temporal logics: a survey 将自然语言需求形式化为时间逻辑:综述

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972130

I. Buzhinsky

引用次数: 15

Applying semantics into Service-oriented IoT Framework 在面向服务的物联网框架中应用语义

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972295

An Ngoc Lam, Øystein Haugen

{"title":"Applying semantics into Service-oriented IoT Framework","authors":"An Ngoc Lam, Øystein Haugen","doi":"10.1109/INDIN41052.2019.8972295","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972295","url":null,"abstract":"Introducing semantics into the Internet of Things (IoT) has been attracting increasing attention from researchers and industrial practitioners. Semantic technologies have been used to enable interoperability as well as deal with the heterogeneity, massive scale, and dynamic nature of IoT resources. With the emergence of Industry 4.0, semantic technologies arise as a potential approach toward information modeling and dynamic reconfiguration of highly complex automation systems with high diversity of domains, protocols, tools or hardware platforms. Applying semantics into existing IoT frameworks requires a thorough understanding of the framework architectures as well as careful considerations of different semantic technologies. To support this process, we survey the literature on the contributions and usage of semantics in IoT. We find that semantics are mainly used to handle interoperable systems and heterogeneous standards. In this paper, we also propose procedures for applying semantics into IoT frameworks. Further, we present our idea of using semantics to enable dynamical orchestration of services within the Arrowhead Framework - an IoT framework that supports the development of industrial automation systems.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127164557","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

Comparing Decoding Performance of LDPC Codes and Convolutional Codes for Short Packet Transmission LDPC码与卷积码在短分组传输中的解码性能比较

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972062

Yi Deng, Ming Zhan, Meng Wang, Chao Yang, Xiaohong Luo, Jie Zeng, Jing Guo

引用次数: 4

Production Planning with IEC 62264 and PDDL 符合IEC 62264和PDDL的生产计划

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972050

Bernhard Wally, J. Vyskočil, Petr Novák, C. Huemer, R. Šindelář, Petr Kadera, Alexandra Mazak, M. Wimmer

引用次数: 11

A Method to Estimate Exogenous Disturbances in Nonlinear Systems Based on Equivalent-Input-Disturbance Approach 基于等效输入扰动法的非线性系统外源扰动估计方法

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972265

Xiang Yin, Jinhua She, Zhentao Liu, Min Wu, Daiki Sato, K. Hirota

引用次数: 0

IASelect: Finding Best-fit Agent Practices in Industrial CPS Using Graph Databases IASelect:使用图数据库在工业CPS中找到最适合的代理实践

2019 IEEE 17th International Conference on Industrial Informatics (INDIN) Pub Date : 2019-07-01 DOI: 10.1109/INDIN41052.2019.8972272

Chandan Sharma, R. Sinha, P. Leitão

{"title":"IASelect: Finding Best-fit Agent Practices in Industrial CPS Using Graph Databases","authors":"Chandan Sharma, R. Sinha, P. Leitão","doi":"10.1109/INDIN41052.2019.8972272","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972272","url":null,"abstract":"The ongoing fourth Industrial Revolution depends mainly on robust Industrial Cyber-Physical Systems (ICPS). ICPS includes computing (software and hardware) abilities to control complex physical processes in distributed industrial environments. Industrial agents, originating from the well-established multi-agent systems field, provide complex and cooperative control mechanisms at the software level, allowing us to develop larger and more feature-rich ICPS. The IEEE P2660.1 standardisation project, \"Recommended Practices on Industrial Agents: Integration of Software Agents and Low Level Automation Functions\" focuses on identifying Industrial Agent practices that can benefit ICPS systems of the future. A key problem within this project is identifying the best-fit industrial agent practices for a given ICPS. This paper reports on the design and development of a tool to address this challenge. This tool, called IASelect, is built using graph databases and provides the ability to flexibly and visually query a growing repository of industrial agent practices relevant to ICPS. IASelect includes a front-end that allows industry practitioners to interactively identify best-fit practices without having to write manual queries.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125079530","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: 7