Pub Date : 1900-01-01DOI: 10.5220/0011527000003329
Mario Toussaint, Sylvère Krima, A. B. Feeney, H. Panetto
: The recent and ongoing digital transformation of the manufacturing world has led to numerous benefits, from higher quality products to increased productivity and reduced time to market. In this digital world, data has become a critical element in many essential decisions and processes within and across organizations. Data exchange is now a key process for the organizations’ communication, collaboration, and efficiency. Industry 4.0/Industry of the Future adoption of modern communication technologies has made data available and shareable at a speed faster than we can consume or track it. This speed is a double edge sword and comes with key challenges, such as data interoperability and data traceability, which manufacturers need to understand in order to adopt the best mitigation strategies. This paper is a summarized introduction to these challenges, their origins, and what they mean to manufacturers.
{"title":"Speed, the Double-edged Sword of the Industry 4.0","authors":"Mario Toussaint, Sylvère Krima, A. B. Feeney, H. Panetto","doi":"10.5220/0011527000003329","DOIUrl":"https://doi.org/10.5220/0011527000003329","url":null,"abstract":": The recent and ongoing digital transformation of the manufacturing world has led to numerous benefits, from higher quality products to increased productivity and reduced time to market. In this digital world, data has become a critical element in many essential decisions and processes within and across organizations. Data exchange is now a key process for the organizations’ communication, collaboration, and efficiency. Industry 4.0/Industry of the Future adoption of modern communication technologies has made data available and shareable at a speed faster than we can consume or track it. This speed is a double edge sword and comes with key challenges, such as data interoperability and data traceability, which manufacturers need to understand in order to adopt the best mitigation strategies. This paper is a summarized introduction to these challenges, their origins, and what they mean to manufacturers.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"2223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123703049","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 : 1900-01-01DOI: 10.5220/0010641700003062
Gerhard Benedikt Weiß, D. Pietraroia, Claudio Sassanelli, Hugo Daniel Macedo
: Model-based design of manufacturing robotic systems involving the usage of different tools, models and the co-simulation of the system behaviour benefits from collaborative platforms enabling ready-to-use and cloud-hosted tools and models. Nonetheless, due to market segmentation and the difficulty to deploy and support all the existing tools and models in such a platform, it is, therefore, reasonable to consider a hybrid cloud-setup where some tools run in the public cloud and other are only available in private clouds or dedicated machines behind the walls of the licensed institution. In this paper, we report on a experiment of such scenario, where a Matlab/Simulink TM , LS-Dyna, and Model.CONNECT TM powered co-simulation tool suite running in a private cloud is combined with the DDD Simulation tool running inside a public cloud. Due to this setup it was possible to combine a 1D hot stamping process simulation with a 3D visualisation. Finally the results of the process simulation were improved by considering realistic movement of the robot. Our study elicited several limitations and feature requests that need to be addressed to better support a hybrid cloud setup for model-based design practitioners. We expect this initial contribution to trigger ground breaking research encompassing all the community members interested in hybrid co-simulation setups.
{"title":"Manufacturing Process Simulation in a Hybrid Cloud Setup","authors":"Gerhard Benedikt Weiß, D. Pietraroia, Claudio Sassanelli, Hugo Daniel Macedo","doi":"10.5220/0010641700003062","DOIUrl":"https://doi.org/10.5220/0010641700003062","url":null,"abstract":": Model-based design of manufacturing robotic systems involving the usage of different tools, models and the co-simulation of the system behaviour benefits from collaborative platforms enabling ready-to-use and cloud-hosted tools and models. Nonetheless, due to market segmentation and the difficulty to deploy and support all the existing tools and models in such a platform, it is, therefore, reasonable to consider a hybrid cloud-setup where some tools run in the public cloud and other are only available in private clouds or dedicated machines behind the walls of the licensed institution. In this paper, we report on a experiment of such scenario, where a Matlab/Simulink TM , LS-Dyna, and Model.CONNECT TM powered co-simulation tool suite running in a private cloud is combined with the DDD Simulation tool running inside a public cloud. Due to this setup it was possible to combine a 1D hot stamping process simulation with a 3D visualisation. Finally the results of the process simulation were improved by considering realistic movement of the robot. Our study elicited several limitations and feature requests that need to be addressed to better support a hybrid cloud setup for model-based design practitioners. We expect this initial contribution to trigger ground breaking research encompassing all the community members interested in hybrid co-simulation setups.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124895296","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 : 1900-01-01DOI: 10.1007/978-3-031-37228-5_3
Janis Grabis, Kristina Jegorova, Krisjanis Pinka
{"title":"Design of Ambient Conditions Control Capability in Retail","authors":"Janis Grabis, Kristina Jegorova, Krisjanis Pinka","doi":"10.1007/978-3-031-37228-5_3","DOIUrl":"https://doi.org/10.1007/978-3-031-37228-5_3","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127663609","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 : 1900-01-01DOI: 10.5220/0011562300003329
Yuhong Fu, G. Grossmann, Karamjit Kaur, Matt Selway, M. Stumptner
{"title":"Multi-level Risk Modelling for Interoperability of Risk Information","authors":"Yuhong Fu, G. Grossmann, Karamjit Kaur, Matt Selway, M. Stumptner","doi":"10.5220/0011562300003329","DOIUrl":"https://doi.org/10.5220/0011562300003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"35 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122982190","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 : 1900-01-01DOI: 10.5220/0011537300003329
N. Iftikhar, Yi-Chen Lin, F. Nordbjerg
{"title":"Machine Learning based Predictive Maintenance in Manufacturing Industry","authors":"N. Iftikhar, Yi-Chen Lin, F. Nordbjerg","doi":"10.5220/0011537300003329","DOIUrl":"https://doi.org/10.5220/0011537300003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128430524","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 : 1900-01-01DOI: 10.5220/0010676400003062
Selvine G. Mathias, Daniel Grossmann
: Acoustic emission (AE) signals obtained during machining processes can be used to detect, locate and assess flaws in structures made of metal, concrete or composites. This paper aims to characterize AE signals using derived parameters from raw signatures along with statistical feature extractions to correlate with tool wear readings. Missing tool wear values are imputed using domain knowledge rules and compared to AE signals using machine learning models. The amount of effect on tool wear is formulated using Bayesian Inferences on derived parameters such as areas under the raw signal curve in addition to comparisons with the supervised models for predictions. Using the constructed models and formulation, the presented study also includes a trace-back pseudo-algorithm for determining the stage in process where tool wear values begin to approach the wear limits.
{"title":"Efficacy of Statistical Formulations on Acoustic Emission Signals for Tool Wear Predictions","authors":"Selvine G. Mathias, Daniel Grossmann","doi":"10.5220/0010676400003062","DOIUrl":"https://doi.org/10.5220/0010676400003062","url":null,"abstract":": Acoustic emission (AE) signals obtained during machining processes can be used to detect, locate and assess flaws in structures made of metal, concrete or composites. This paper aims to characterize AE signals using derived parameters from raw signatures along with statistical feature extractions to correlate with tool wear readings. Missing tool wear values are imputed using domain knowledge rules and compared to AE signals using machine learning models. The amount of effect on tool wear is formulated using Bayesian Inferences on derived parameters such as areas under the raw signal curve in addition to comparisons with the supervised models for predictions. Using the constructed models and formulation, the presented study also includes a trace-back pseudo-algorithm for determining the stage in process where tool wear values begin to approach the wear limits.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127434701","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 : 1900-01-01DOI: 10.5220/0010740100003062
Qing Li, Bo Liang, Zhixiong Fang
: Architecture, methodology and system modelling are systems engineering tools to understand, design, develop, implement and integrate complex systems, software and enterprises. In order to solve the problem of complex system integration, Zachman Framework, CIM-OSA, GERAM, FEAF, DoDAF, TOGAF and other architectures have been developed. Model has become the main means of system analysis and design, and gave birth to model-based systems engineering (MBSE). There are several methodologies of MBSE, such as Harmony, Magic Grid and so forth. Therefore, it is necessary to develop a general architecture and modelling framework to support models and systems, software, enterprise integration based on different architecture and methodologies. This paper presents a General Architecture Framework and a relative General Modelling Framework (GMF). GAF provides tools and methodology of model-based systems engineering (MBSE) to systems design and development. GMF involves a set of models and methods to describes different aspects of a system. The paper also discusses the mapping and integration relationship between GAF, GMF with mainstream architecture and modelling frameworks. Performance Business reference models, Data reference models,
{"title":"Mapping and Integration of Architecture and Modelling Frameworks","authors":"Qing Li, Bo Liang, Zhixiong Fang","doi":"10.5220/0010740100003062","DOIUrl":"https://doi.org/10.5220/0010740100003062","url":null,"abstract":": Architecture, methodology and system modelling are systems engineering tools to understand, design, develop, implement and integrate complex systems, software and enterprises. In order to solve the problem of complex system integration, Zachman Framework, CIM-OSA, GERAM, FEAF, DoDAF, TOGAF and other architectures have been developed. Model has become the main means of system analysis and design, and gave birth to model-based systems engineering (MBSE). There are several methodologies of MBSE, such as Harmony, Magic Grid and so forth. Therefore, it is necessary to develop a general architecture and modelling framework to support models and systems, software, enterprise integration based on different architecture and methodologies. This paper presents a General Architecture Framework and a relative General Modelling Framework (GMF). GAF provides tools and methodology of model-based systems engineering (MBSE) to systems design and development. GMF involves a set of models and methods to describes different aspects of a system. The paper also discusses the mapping and integration relationship between GAF, GMF with mainstream architecture and modelling frameworks. Performance Business reference models, Data reference models,","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124431580","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 : 1900-01-01DOI: 10.5220/0011524100003329
A. Smirnov, A. Kashevnik, N. Shilov, N. Teslya, M. Petrov, Mario Sinko, Jens Arneving, Michael Humpf, Thorsten Kolmer
{"title":"Product Configuration Automation: Digital Transformation Platform and Case Study","authors":"A. Smirnov, A. Kashevnik, N. Shilov, N. Teslya, M. Petrov, Mario Sinko, Jens Arneving, Michael Humpf, Thorsten Kolmer","doi":"10.5220/0011524100003329","DOIUrl":"https://doi.org/10.5220/0011524100003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"155 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128665529","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 : 1900-01-01DOI: 10.5220/0011598000003329
K. Krämer, L. V. Elst, A. Arteaga
{"title":"Traveling Salesman Problem: A Case Study of a Scheduling Problem in a Steelmaking Plant","authors":"K. Krämer, L. V. Elst, A. Arteaga","doi":"10.5220/0011598000003329","DOIUrl":"https://doi.org/10.5220/0011598000003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114691205","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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