Data acquisition and control at the edge: a hardware/software-reconfigurable approach

dc.contributor.authorStreit, F.
dc.contributor.authorWituschek, S.
dc.contributor.authorPschyklenk, M.
dc.contributor.authorBecher, A.
dc.contributor.authorLechner, M.
dc.contributor.authorWildermann, S.
dc.contributor.authorPitz, I.
dc.contributor.authorMerklein, M.
dc.contributor.authorTeich, J.
dc.date.accessioned2023-05-22
dc.date.available2023-10-16T20:44:53Z
dc.date.created2020
dc.date.issued2023-05-22
dc.description.abstractAbstract Today’s manufacturing facilities and processes offer the potential to collect data on an unprecedented scale. However, conventional Programmable Logic Controllers are often proprietary systems with closed-source hardware and software and not designed to also take over the seamless acquisition and processing of enormous amounts of data. Furthermore, their major focus on simple control tasks and a rigid number of static built-in I/O connectors make them not well suited for the big data challenge and an industrial environment that is changing at a high pace. This paper, advocates emerging hardware- and I/O reconfigurable Programmable System-on-Chip (PSoC) solutions based on Field-Programmable Gate Arrays to provide flexible and adaptable capabilities for both data acquisition and control right at the edge. Still, the design and implementation of applications on such heterogeneous PSoC platforms demands a comprehensive expertise in hardware/software co-design. To bridge this gap, a model-based design automation approach is presented to generate automatically optimized HW/SW configurations for a given PSoC. As a case study, a metal forming process is considered and the design automation of an industrial closed-loop control algorithm with the design objectives performance and resource costs is investigated to show the benefits of the approach.en
dc.format.extent6
dc.identifier.citationProduction Engineering 14.3 (2020): S. 365-371. <https://link.springer.com/article/10.1007/s11740-020-00964-x>
dc.identifier.doihttps://doi.org/10.1007/s11740-020-00964-x
dc.identifier.issn0944-6524
dc.identifier.issn1863-7353
dc.identifier.opus-id23139
dc.identifier.urihttps://open.fau.de/handle/openfau/23139
dc.identifier.urnurn:nbn:de:bvb:29-opus4-231392
dc.language.isoen
dc.publisherSpringer Berlin Heidelberg
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.de
dc.subjectFPGA
dc.subjectPSoC
dc.subjectHardware/software co-design
dc.subjectModel-based engineering
dc.subjectIndustrial automation
dc.subjectManufacturing technology
dc.subjectForming process
dc.subjectMotor control
dc.subject.ddcDDC Classification::0 Informatik, Informationswissenschaft, allgemeine Werke :: 00 Informatik, Wissen, Systeme :: 000 Informatik, Informationswissenschaft, allgemeine Werke
dc.titleData acquisition and control at the edge: a hardware/software-reconfigurable approachen
dc.typearticle
dcterms.publisherFriedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
local.date.prevpublished2020-06-01
local.document.pageend371
local.document.pagestart365
local.journal.issue3
local.journal.titleProduction Engineering
local.journal.volume14
local.sendToDnbfree*
local.subject.fakultaetTechnische Fakultät
local.subject.importimport
local.subject.sammlungUniversität Erlangen-Nürnberg / Eingespielte Open Access Artikel / Eingespielte Open Access Artikel 2023
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
23139_s11740-020-00964-x.pdf
Size:
689.7 KB
Format:
Adobe Portable Document Format
Description: