Distributable Modular Software Framework for Manufacturing Systems

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

Distributable Modular Software Framework for Manufacturing Systems. / Papadoudis, Jan; Georgiadis, Anthimos.
Procedia CIRP: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems. Vol. 41 Elsevier Scientific Publishing, 2016. p. 712-716 (Procedia CIRP; Vol. 41).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Papadoudis, J & Georgiadis, A 2016, Distributable Modular Software Framework for Manufacturing Systems. in Procedia CIRP: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems. vol. 41, Procedia CIRP, vol. 41, Elsevier Scientific Publishing, pp. 712-716, 48th CIRP Conference on MANUFACTURING SYSTEMS 2015, Ischia, Italy, 24.06.15. https://doi.org/10.1016/j.procir.2015.12.079

APA

Papadoudis, J., & Georgiadis, A. (2016). Distributable Modular Software Framework for Manufacturing Systems. In Procedia CIRP: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems (Vol. 41, pp. 712-716). (Procedia CIRP; Vol. 41). Elsevier Scientific Publishing. https://doi.org/10.1016/j.procir.2015.12.079

Vancouver

Papadoudis J, Georgiadis A. Distributable Modular Software Framework for Manufacturing Systems. In Procedia CIRP: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems. Vol. 41. Elsevier Scientific Publishing. 2016. p. 712-716. (Procedia CIRP). doi: 10.1016/j.procir.2015.12.079

Bibtex

@inbook{2f3adf5b8de8479792fbd2323ae20539,
title = "Distributable Modular Software Framework for Manufacturing Systems",
abstract = "Modern production processes have a high demand on reliability, automation and accuracy in order to avoid defects during the manufacturing process. Each production differs in its demands, with which can be dealt by using intelligent decision making software. In current production systems for each evaluation of a vital process parameter a different software system is used. A modular software framework was developed which can be easily adapted to different production processes and different sensor inputs. It also supports an easy nearly “plug&play” integration of new processing algorithms. Thus making it possible to deal with multiple evaluation within one process and throughout different machines and processes using one common software framework architecture. The software consists of different basic modules connected via the framework and a common data structure. The modules can be customized using a simple configuration file. The framework connects the main modules data acquisition, data preparation, processing algorithms, decision making, a database and the controller integration. All of the modules are optional and can be adjusted with the configuration file. By using a common data structure and communication protocol it is also possible to distribute the modules over different PCs and machines as long as they are connected by a network. This features are creating a software framework able to be adapted easily to different use cases within one production process and also different production processes. This software was successfully integrated into production environments within a European project realizing an in-process real time control of the machine to minimize defects",
keywords = "Engineering, Programming, In-process measurement, Modelling",
author = "Jan Papadoudis and Anthimos Georgiadis",
note = "Funding Information: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: JBL is an employee of RTI International, an independent, nonprofit research institute that provides research services for governmental and commercial clients, including pharmaceutical companies. LM is an employee of and owns stock in NoviSci, Inc. AMB is supported by a grant from the National Center for Advancing Translational Sciences (NCATS), NIH under award number KL2 TR002346. The other authors report no conflicts. Funding Information: The work was supported by the United States National Institutes of Health [grant number 1R21AI38385 ]. Data programming for this study was conducted by the Center for Administrative Data Research, which is supported in part by the Washington University Institute of Clinical and Translational Sciences grant UL1 TR002345 from the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) and by grant number R24 HS19455 through the Agency for Healthcare Research and Quality (AHRQ). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Publisher Copyright: {\textcopyright} 2016 The Authors.; 48th CIRP Conference on MANUFACTURING SYSTEMS 2015 : Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future, CIRP CMS 2015 ; Conference date: 24-06-2015 Through 26-06-2015",
year = "2016",
month = jan,
day = "1",
doi = "10.1016/j.procir.2015.12.079",
language = "English",
volume = "41",
series = "Procedia CIRP",
publisher = "Elsevier Scientific Publishing",
pages = "712--716",
booktitle = "Procedia CIRP",
address = "Netherlands",
url = "http://www.icme.unina.it/CMS%202015/CMS2015.htm",

}

RIS

TY - CHAP

T1 - Distributable Modular Software Framework for Manufacturing Systems

AU - Papadoudis, Jan

AU - Georgiadis, Anthimos

N1 - Conference code: 48

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Modern production processes have a high demand on reliability, automation and accuracy in order to avoid defects during the manufacturing process. Each production differs in its demands, with which can be dealt by using intelligent decision making software. In current production systems for each evaluation of a vital process parameter a different software system is used. A modular software framework was developed which can be easily adapted to different production processes and different sensor inputs. It also supports an easy nearly “plug&play” integration of new processing algorithms. Thus making it possible to deal with multiple evaluation within one process and throughout different machines and processes using one common software framework architecture. The software consists of different basic modules connected via the framework and a common data structure. The modules can be customized using a simple configuration file. The framework connects the main modules data acquisition, data preparation, processing algorithms, decision making, a database and the controller integration. All of the modules are optional and can be adjusted with the configuration file. By using a common data structure and communication protocol it is also possible to distribute the modules over different PCs and machines as long as they are connected by a network. This features are creating a software framework able to be adapted easily to different use cases within one production process and also different production processes. This software was successfully integrated into production environments within a European project realizing an in-process real time control of the machine to minimize defects

AB - Modern production processes have a high demand on reliability, automation and accuracy in order to avoid defects during the manufacturing process. Each production differs in its demands, with which can be dealt by using intelligent decision making software. In current production systems for each evaluation of a vital process parameter a different software system is used. A modular software framework was developed which can be easily adapted to different production processes and different sensor inputs. It also supports an easy nearly “plug&play” integration of new processing algorithms. Thus making it possible to deal with multiple evaluation within one process and throughout different machines and processes using one common software framework architecture. The software consists of different basic modules connected via the framework and a common data structure. The modules can be customized using a simple configuration file. The framework connects the main modules data acquisition, data preparation, processing algorithms, decision making, a database and the controller integration. All of the modules are optional and can be adjusted with the configuration file. By using a common data structure and communication protocol it is also possible to distribute the modules over different PCs and machines as long as they are connected by a network. This features are creating a software framework able to be adapted easily to different use cases within one production process and also different production processes. This software was successfully integrated into production environments within a European project realizing an in-process real time control of the machine to minimize defects

KW - Engineering

KW - Programming

KW - In-process measurement

KW - Modelling

UR - http://www.scopus.com/inward/record.url?scp=84968830711&partnerID=8YFLogxK

U2 - 10.1016/j.procir.2015.12.079

DO - 10.1016/j.procir.2015.12.079

M3 - Article in conference proceedings

VL - 41

T3 - Procedia CIRP

SP - 712

EP - 716

BT - Procedia CIRP

PB - Elsevier Scientific Publishing

T2 - 48th CIRP Conference on MANUFACTURING SYSTEMS 2015

Y2 - 24 June 2015 through 26 June 2015

ER -

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