CBI4.0: A Cross-Layer Approach for Big Data Gathering for Active Monitoring and Maintenance in the Manufacturing Industry 4.0

dc.contributor.author Faheem, Muhammad
dc.contributor.author Butt, Rizwan Aslam
dc.contributor.author Ali, Rashid
dc.contributor.author Raza, Basit
dc.contributor.author Ngadi, Md Asri
dc.contributor.author Gungor, Vehbi Cagri
dc.date.accessioned 2022-03-04T11:03:28Z
dc.date.available 2022-03-04T11:03:28Z
dc.date.issued 2021 en_US
dc.date.issued 2021
dc.description Phd, Muhammad Faheem,/0000-0003-4628-4486; Raza, Basit/0000-0001-6711-2363; Butt, Rizwan Aslam/0000-0002-4784-0918 en_US
dc.description.abstract Industry 4.0 (I4.0) defines a new paradigm to produce high-quality products at the low cost by reacting quickly and effectively to changing demands in the highly volatile global markets. In Industry 4.0, the adoption of Internet of Things (IoT)-enabled Wireless Sensors (WSs) in the manufacturing processes, such as equipment, machining, assembly, material handling, inspection, etc., generates a huge volume of data known as Industrial Big Data (IBD). However, the reliable and efficient gathering and transmission of this big data from the source sensors to the floor inspection system for the real-time monitoring of unexpected changes in the production and quality control processes is the biggest challenge for Industrial Wireless Sensor Networks (IWSNs). This is because of the harsh nature of the indoor industrial environment that causes high noise, signal fading, multipath effects, heat and electromagnetic interference, which reduces the transmission quality and trigger errors in the IWSNs. Therefore, this paper proposes a novel cross-layer data gathering approach called CBI4.0 for active monitoring and control of manufacturing processes in the Industry 4.0. The key aim of the proposed CBI4.0 scheme is to exploit the multi-channel and multi-radio architecture of the sensor network to guarantee quality of service (QoS) requirements, such as higher data rates, throughput, and low packet loss, corrupted packets, and latency by dynamically switching between different frequency bands in the Multichannel Wireless Sensor Networks (MWSNs). By performing several simulation experiments through EstiNet 9.0 simulator, the performance of the proposed CBI4.0 scheme is compared against existing studies in the automobile Industry 4.0. The experimental outcomes show that the proposed scheme outperforms existing schemes and is suitable for effective control and monitoring of various events in the automobile Industry 4.0. en_US
dc.identifier.doi 10.1016/j.jii.2021.100236
dc.identifier.issn 2467-964X
dc.identifier.issn 2452-414X
dc.identifier.scopus 2-s2.0-85108726536
dc.identifier.uri https://doi.org/10.1016/j.jii.2021.100236
dc.identifier.uri https://hdl.handle.net/20.500.12573/1232
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartof Journal of Industrial Information Integration en_US
dc.relation.isversionof 10.1016/j.jii.2021.100236 en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Internet of Things en_US
dc.subject Industry 4.0 en_US
dc.subject Big Data en_US
dc.subject Multi-Channel Communication en_US
dc.subject Wireless Sensor Network en_US
dc.title CBI4.0: A Cross-Layer Approach for Big Data Gathering for Active Monitoring and Maintenance in the Manufacturing Industry 4.0 en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Phd, Muhammad Faheem,/0000-0003-4628-4486
gdc.author.id Raza, Basit/0000-0001-6711-2363
gdc.author.id Butt, Rizwan Aslam/0000-0002-4784-0918
gdc.author.scopusid 58648789900
gdc.author.scopusid 54790836600
gdc.author.scopusid 57193622464
gdc.author.scopusid 24776735600
gdc.author.scopusid 24923511700
gdc.author.scopusid 10739803300
gdc.author.wosid Faheem, Muhammad/Abe-4074-2020
gdc.author.wosid Raza, Basit/V-5424-2019
gdc.author.wosid Ngadi, Md/G-3174-2011
gdc.author.wosid Ali, Rashid/Jnr-6234-2023
gdc.author.wosid Butt, Rizwan Aslam/Abg-5329-2020
gdc.bip.impulseclass C4
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department Abdullah Gül University en_US
gdc.description.departmenttemp [Faheem, Muhammad; Gungor, Vehbi Cagri] Abdullah Gul Univ, Dept Comp Engn, TR-38080 Kayseri, Turkey; [Faheem, Muhammad; Ngadi, Md Asri] Univ Teknol Malaysia, Dept Comp Sci, Johor Baharu 801310, Malaysia; [Butt, Rizwan Aslam] NED Univ Engn & Technol, Dept Elect Engn, Karachi 75270, Pakistan; [Ali, Rashid] Sejong Univ, Sch Intelligent Mechatron Engn, Seoul 05006, South Korea; [Raza, Basit] COMSATS Univ Islamabad CUI, Dept Comp Sci, Islamabad 45550, Pakistan en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.volume 24 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q1
gdc.identifier.openalex W3177048707
gdc.identifier.wos WOS:000725689200003
gdc.index.type WoS
gdc.index.type Scopus
gdc.oaire.diamondjournal false
gdc.oaire.impulse 30.0
gdc.oaire.influence 4.6510946E-9
gdc.oaire.isgreen false
gdc.oaire.keywords 670
gdc.oaire.keywords QA75 Electronic computers. Computer science
gdc.oaire.popularity 2.7257261E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration International
gdc.openalex.fwci 7.2648
gdc.openalex.normalizedpercentile 0.97
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 34
gdc.plumx.crossrefcites 33
gdc.plumx.facebookshareslikecount 62
gdc.plumx.mendeley 95
gdc.plumx.scopuscites 48
gdc.scopus.citedcount 52
gdc.wos.citedcount 43
relation.isOrgUnitOfPublication 665d3039-05f8-4a25-9a3c-b9550bffecef
relation.isOrgUnitOfPublication.latestForDiscovery 665d3039-05f8-4a25-9a3c-b9550bffecef

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
CBI4.0 A cross-layer approach for big data gathering for active monitoring and maintenance in the manufacturing industry 4.0.pdf
Size:
5.58 MB
Format:
Adobe Portable Document Format
Description:
Makale Dosyası

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.44 KB
Format:
Item-specific license agreed upon to submission
Description: