TY  - CHAP
A1  - Schuh, Günther
A1  - Stich, Volker
A1  - Reuter, Christina
A1  - Blum, Matthias
A1  - Brambring, Felix
A1  - Hempel, T.
A1  - Reschke, Jan
A1  - Schiemann, Dennis
A2  - Jeschke, Sabina
A2  - Brecher, Christian
A2  - Song, Houbing
A2  - Rawat, Danda B.
T1  - Cyber Physical Production Control
T2  - Industrial Internet of Things: Cybermanufacturing Systems
N2  - One major problem of today’s producing companies is to reach a high adherence to delivery dates while considering the volatile market situation as well as economic aspects. This problem can only be solved by using a production control that is optimally adapted to the processes. A good working, process-oriented production control is essential for being able to control the production situation and to ensure a high adherence to delivery dates. Data generation and processing determine the success of production control. Current processes and IT systems have several shortcomings in meeting these challenges.
The solution for this problem is the so called “cyber physical production control” (CPPC). It optimally supports the production scheduler in his decision making process based on real-time high-resolution data. With the help of data analytics, the production controller receives decision support over various steps. Due to CPPC, the overall goal of a high adherence to delivery dates can be fundamentally increased.
KW  - Data analytics
KW  - Cyber physical production control
KW  - Decision support
Y1  - 2023
UR  - https://epub.fir.de/frontdoor/index/index/docId/2564
UR  - https://link.springer.com/chapter/10.1007/978-3-319-42559-7_21
SN  - 978-3-319-82608-0
SN  - 2365-4139
SP  - 519
EP  - 539
PB  - Springer
CY  - Cham [u. a.]
ER  -