%0 Book Section %1 GoetzKeitzelKlocke17p401 %A Goetz, Sven %A Keitzel, Gunnar %A Klocke, Fritz %B Industrial Internet of Things %C Cham %D 2017 %E Jeschke, Sabina %E Brecher, Christian %E Song, Houbing %E Rawat, Danda B. %I Springer %K 01821 springer paper embedded ai factory knowledge semantic sensor data processing user interaction interface application architecture zzz.i40 %P 401--422 %R 10.1007/978-3-319-42559-7_15 %T Going Smart---CPPS for Digital Production %X The Smart Factory is able to receive production orders and to control its value streams by communication between all involved elements. The whole production process is monitored by sensor systems generating a seamless blend of data that is condensed to information and key values using process models. Unknown states and critical situations are presented with full transparency to the worker that acts as the final decision maker. The required ability to gather and process information and to communicate this information to other entities is granted by Cyber-Physical Production Systems (CPPS). The structure of this article represents the pathway from data to knowledge and the subsequent knowledge exploitation. In the first part, the concepts of contemporary sensors and sensor systems are highlighted. The integration and fusion of single metering elements to measuring systems with suitable data pre-processing ensures the direct utilizability of high complex measuring data by CPPS. Actual examples of application demonstrate the implementation in production systems. The second part deals with the CPPS as the architecture for smart applications. Therefore, models are introduced as carriers of technology knowledge for the digital production. The interpretation of the measurement data in an adequate manner will empower the CPPS to adapt manufacturing processes and make the right decisions. By this, safety buffers may be reduced or quality requirements increased, as the system 'knows' more about its state and boundaries. Since the final controller of the smart factory will still be a human being, CPPS also need a sound interface to the real, human world. The article closes with the introduction of tech apps that provide on the one hand an added value to the user by presenting machine states and key value and on the other hand enriches the model qualities by requesting expert knowledge from the machine operator. This finally makes the production system 'smart', as it enables the hardware of a factory to blend with the software and the human worker into one, seamless system. %@ 978-3-319-42558-0

@incollection{GoetzKeitzelKlocke17p401, abstract = {The Smart Factory is able to receive production orders and to control its value streams by communication between all involved elements. The whole production process is monitored by sensor systems generating a seamless blend of data that is condensed to information and key values using process models. Unknown states and critical situations are presented with full transparency to the worker that acts as the final decision maker. The required ability to gather and process information and to communicate this information to other entities is granted by Cyber-Physical Production Systems (CPPS). The structure of this article represents the pathway from data to knowledge and the subsequent knowledge exploitation. In the first part, the concepts of contemporary sensors and sensor systems are highlighted. The integration and fusion of single metering elements to measuring systems with suitable data pre-processing ensures the direct utilizability of high complex measuring data by CPPS. Actual examples of application demonstrate the implementation in production systems. The second part deals with the CPPS as the architecture for smart applications. Therefore, models are introduced as carriers of technology knowledge for the digital production. The interpretation of the measurement data in an adequate manner will empower the CPPS to adapt manufacturing processes and make the right decisions. By this, safety buffers may be reduced or quality requirements increased, as the system 'knows' more about its state and boundaries. Since the final controller of the smart factory will still be a human being, CPPS also need a sound interface to the real, human world. The article closes with the introduction of tech apps that provide on the one hand an added value to the user by presenting machine states and key value and on the other hand enriches the model qualities by requesting expert knowledge from the machine operator. This finally makes the production system 'smart', as it enables the hardware of a factory to blend with the software and the human worker into one, seamless system.}, added-at = {2017-01-01T15:27:27.000+0100}, address = {Cham}, author = {Goetz, Sven and Keitzel, Gunnar and Klocke, Fritz}, biburl = {https://www.bibsonomy.org/bibtex/22322efe7a0f11b1a7237c010e6dbfe74/flint63}, booktitle = {Industrial Internet of Things}, crossref = {JeschkeBrecherEtAl2017}, doi = {10.1007/978-3-319-42559-7_15}, editor = {Jeschke, Sabina and Brecher, Christian and Song, Houbing and Rawat, Danda B.}, file = {SpringerLink:2017/GoetzKeitzelKlocke17p401.pdf:PDF}, groups = {public}, interhash = {2dc47136bccf1dd084e958e66049331e}, intrahash = {2322efe7a0f11b1a7237c010e6dbfe74}, isbn = {978-3-319-42558-0}, issn = {2365-4139}, keywords = {01821 springer paper embedded ai factory knowledge semantic sensor data processing user interaction interface application architecture zzz.i40}, pages = {401--422}, publisher = {Springer}, series = {Springer Series in Wireless Technology}, timestamp = {2018-04-16T12:15:21.000+0200}, title = {Going Smart---{CPPS} for Digital Production}, username = {flint63}, year = 2017 }