Offene, intelligente Services für die Produktion*/Open, intelligent services for production using the example of integrated quality assurance

2019 ◽  
Vol 109 (03) ◽  
pp. 116-121
Author(s):  
J. Klöber-Koch ◽  
M. Schreiber ◽  
C. Linder ◽  
J. Bömelburg-Zacharias ◽  
G. Reinhart
Keyword(s):  
Quality Assurance ◽  
Data Analysis ◽  
Product Quality ◽  
Production Systems ◽  
Cyber Physical Systems ◽  
Improve Product Quality ◽  
Physical Systems ◽  
Useful Knowledge ◽  
Know How ◽  
Production Processes

In Produktionssystemen steigt die erzeugte Datenmenge durch die Integration von cyber-physischen Systemen und zusätzlichen Sensoren kontinuierlich an. Diese Daten enthalten potenziell nützliches Wissen zur Verbesserung der Produktqualität und der Produktionsprozesse. Unternehmen haben jedoch oftmals nicht das notwendige Know-how, die anfallenden Daten zu analysieren sowie das darin enthaltene Wissen zu extrahieren. Das Ziel des Forschungsprojekts „OpenServ4P“ ist es, Services zu entwickeln, die von Unternehmen ohne tiefgreifendes Know-how im Bereich Datenanalyse erfolgreich angewendet und an ihre spezifischen Anforderungen angepasst werden können. Im Folgenden wird ein Service für die automatisierte, integrierte Qualitätssicherung vorgestellt.   The amount of data generated in production systems increases continuously due to the integration of cyber-physical systems and additional sensors. These data contain potentially useful knowledge to improve product quality and production processes. However, companies often do not have the necessary know-how to analyze the data and extract the contained knowledge. The goal of the OpenServ4P research project is to develop services that can be successfully applied by companies without in-depth know-how in the field of data analysis and can be adapted to their specific requirements. In the following, a service for automated, integrated quality assurance is presented.

scholarly journals The Industry 4.0 technological and information processes cyber-modelling

2021 ◽  
Vol 2094 (4) ◽  
pp. 042062
Author(s):  
A V Gurjanov ◽  
D A Zakoldaev ◽  
I O Zharinov ◽  
O O Zharinov
Keyword(s):  
Production Systems ◽  
Cyber Physical Systems ◽  
Time Interval ◽  
Control Laws ◽  
Physical Systems ◽  
Production Processes ◽  
Information Models ◽  
Number Of Cycles ◽  
Cyber Physical Production Systems ◽  
Parameter Values

Abstract Cyber-modelling is the information models simulation process describing in a mathematical and formal logic languages (phenomenon models) how cyber-physical systems interaction mechanisms are united with different control laws and parameter values. The equation complexity represented in different levels of cyber-physical production systems hierarchy and non-equations of algebra, logic, end-subtraction, vector and matrices form in a discreet and uninterrupted times are defined with an aggregated number in the industrial automatics element control loop. The cyber-modelling is done for statistic and dynamic processes and equipment states being monitored in a virtual environment fixating actual in a time interval technological data. The cyber-modelling is done with integrated calculation equipment systems with parallel physical production processes of item manufacturing. The model time faster than physical processes let prognosticate the corrections modifying control signals and phase variables of cyber-physical systems united in an assembly conveyor. The cyber-modelling advantage is an expanded number of cycles to optimize the technological processes, which are calculated with integrated calculation systems using consecutive approximation method. They describe the cyber-modelling technology and propose the information models based on phenomenon cyber-physical production processes descriptions with general control theory terms, calculations and connection for hierarchy controlling structures.

scholarly journals Case Study of Building a Digital Twin for a Production System

2021 ◽  
Vol 29 (49) ◽  
pp. 51-58
Author(s):  
Fedor Burčiar ◽  
Pavel Važan ◽  
Simona Pulišová
Keyword(s):  
Production System ◽  
Industry 4.0 ◽  
Production Systems ◽  
Simulation Models ◽  
Cyber Physical Systems ◽  
Production Data ◽  
Physical Systems ◽  
Production Processes ◽  
Gathering Data

Abstract As the term of Industry 4.0 becomes more and more relevant with each passing day, it is up to researchers and companies to find solutions to integrating all the technologies it covers. One of those technologies, even though not highly developed, is simulation and building Cyber-Physical Systems for gathering data and improving the production processes. In the research described in this paper, we focused on integrating production data with simulation models in order to make the process of understanding and learning about complex production systems as simple and as quick as possible. This paper contains three sections. The first one introduces the theoretical fundamentals of our research. The second one focuses on the methods used to create a digital model of production system. The final one discusses the results of the conducted experiments, and their impact on further research.

scholarly journals V-model based development of cyber-physical systems and cyber-physical production systems

Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 253-258
Author(s):  
Iris Gräßler ◽  
Dominik Wiechel ◽  
Daniel Roesmann ◽  
Henrik Thiele
Keyword(s):  
Production Systems ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Model Based ◽  
Cyber Physical Production Systems

Step-based evolution support among networked production automation systems

2018 ◽  
Vol 66 (10) ◽  
pp. 849-858
Author(s):  
Christopher Haubeck ◽  
Heiko Bornholdt ◽  
Winfried Lamersdorf ◽  
Abhishek Chakraborty ◽  
Alexander Fay
Keyword(s):  
Production Systems ◽  
Cyber Physical Systems ◽  
Peer To Peer ◽  
Evolution Process ◽  
Physical Systems ◽  
Model Based ◽  
Automation Systems ◽  
Production Automation ◽  
Isolated Systems

Abstract Production systems are no longer rigid, unyielding, and isolated systems anymore. They are rather interconnected cyber-physical systems with an evolution process that needs to be supported. To enable reusability in evolution, a change-first cooperative support is proposed that relies on model-based evolution steps. The approach establishes a network-wide evolution process in a peer-to-peer networked community. Thus, moving towards decentralised marketplaces for evolution steps.

scholarly journals Simulation of Production Processes Involving Cyber-physical Systems

Procedia CIRP ◽  
2017 ◽  
Vol 62 ◽  
pp. 577-582 ◽  
Author(s):  
Jens F. Lachenmaier ◽  
Heiner Lasi ◽  
Hans-Georg Kemper
Keyword(s):  
Cyber Physical Systems ◽  
Physical Systems ◽  
Production Processes

scholarly journals Pengaruh Kualitas Produk Terhadap Minat Beli Konsumen Pada Home Industri Pia Deisy Desa Kapitu Kecamatan Amurang Barat

2019 ◽  
Vol 8 (2) ◽  
pp. 83
Author(s):  
Nikita Karundeng ◽  
Johnny A. F. Kalangi ◽  
Olivia F. C. Walangitan
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Product Quality ◽  
Quantitative Research ◽  
Linear Regression Analysis ◽  
Test Validity ◽  
Improve Product Quality ◽  
Simple Linear Regression ◽  
Analysis Techniques

This study aims to determine whether Product Quality has an effect on Consumer Buying Interest. Speaking with quality and buying interest is certainly very tied to marketing. The essence of marketing according to Daryanto (2011) "marketing is a social and managerial process where individuals and groups get their needs and desires by creating, offering, and exchanging something of value with each other". This type of research is quantitative research with data analysis techniques using a skla likert research instrument, test validity, reliability, simple linear regression analysis and hypothesis testing. Based on the results of the study the influence of product quality is a variable that does not affect consumer buying interest. Then it can be concluded that product quality does not significantly influence consumer buying interest. If the quality of the product is good, there will be buying interest and consumers will feel satisfied. In this case, Pia Deisy's business must further improve product quality so that it will be more attractive and will have a good impact on Pia Deisy's home business.

scholarly journals Consumer Willingness to Pay for The Purchase of Spicy Acid Catfish at Pondok Gurih Restaurant, Pekanbaru

2020 ◽  
Vol 008 (01) ◽  
pp. 82-96
Author(s):  
Fitri Yuliasma ◽  
◽  
Trisla Warningsih ◽  
Darwis AN ◽  
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Willingness To Pay ◽  
Product Quality ◽  
Research Method ◽  
Secondary Data ◽  
Primary Data ◽  
Survey Method ◽  
Improve Product Quality ◽  
Analysis Method

This research was conducted at Pondok Gurih Restaurant, Pekanbaru which aims to calculate the value of the willingness to pay of consumers and to analyze the factors that affect the willingness to pay of consumers for the purchase of catfish spicy acid. This research can be used as information material for the restaurant to improve the quality and facilities for consumer demand. The research method used is a survey method that used primary data and secondary data. The data collection techniques through interviews. The sample in this study are consumers who eat at the restaurant and are willing to be interviewed. The number of respondents used in this study was 100 people. The data analysis method used in this research is logistic regression. The results showed that the average cost to be paid by consumers was IDR 87,410 with the lowest WTP value of IDR 40,000 and the highest was IDR 150,000. Then the variables that significantly affect the consumer's desire to pay are age, income, education, and product quality. The variables that did not have a significant effect were gender, service quality, and occupation. Suggestions for businesses are to continue to improve product quality.

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