PMID- 37050828
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20230413
LR  - 20230415
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 23
IP  - 7
DP  - 2023 Apr 6
TI  - Where to Place Monitoring Sensors for Improving Complex Manufacturing Systems? 
      Discussing a Real Case in the Food Industry.
LID - 10.3390/s23073768 [doi]
LID - 3768
AB  - Industry 4.0 technologies offer manufacturing companies numerous tools to enhance 
      their core processes, including monitoring and control. To optimize efficiency, 
      it is crucial to effectively install monitoring sensors. This paper proposes a 
      Multi-Criteria Decision-Making (MCDM) approach as a practical solution to the 
      sensor placement problem in the food industry, having been applied to wine 
      bottling line equipment at a real Italian winery. The approach helps 
      decision-makers when discriminating within a set of alternatives based on 
      multiple criteria. By evaluating the interconnections within the different 
      equipment, the ideal locations of sensors are suggested, with the goal of 
      improving the process's performance. The results indicated that the system of 
      electric pumps, corker, conveyor, and capper had the most influence on the other 
      equipment which are then recommended for sensor control. Monitoring this 
      equipment will result in the early discovery of failures, potentially also 
      involving other dependant equipment, contributing to enhance the level of 
      performance for the whole bottling line.
FAU - Rivas Pellicer, Miguel
AU  - Rivas Pellicer M
AD  - Department of Manufacturing Systems Engineering and Management, College of 
      Engineering and Computer Science, California State University Northridge, 18111 
      Nordhoff Street, Northridge, CA 91330, USA.
FAU - Tungekar, Mohamed Yoosha
AU  - Tungekar MY
AD  - Department of Manufacturing Systems Engineering and Management, College of 
      Engineering and Computer Science, California State University Northridge, 18111 
      Nordhoff Street, Northridge, CA 91330, USA.
FAU - Carpitella, Silvia
AU  - Carpitella S
AUID- ORCID: 0000-0003-0171-2504
AD  - Department of Manufacturing Systems Engineering and Management, College of 
      Engineering and Computer Science, California State University Northridge, 18111 
      Nordhoff Street, Northridge, CA 91330, USA.
LA  - eng
PT  - Journal Article
DEP - 20230406
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC10098759
OTO - NOTNLM
OT  - Industry 4.0
OT  - MCDM
OT  - food industry
OT  - fuzzy DEMATEL
OT  - manufacturing
OT  - sensor placement
COIS- The authors declare no conflict of interest.
EDAT- 2023/04/14 06:00
MHDA- 2023/04/14 06:01
PMCR- 2023/04/06
CRDT- 2023/04/13 01:32
PHST- 2023/03/02 00:00 [received]
PHST- 2023/03/30 00:00 [revised]
PHST- 2023/04/04 00:00 [accepted]
PHST- 2023/04/14 06:01 [medline]
PHST- 2023/04/13 01:32 [entrez]
PHST- 2023/04/14 06:00 [pubmed]
PHST- 2023/04/06 00:00 [pmc-release]
AID - s23073768 [pii]
AID - sensors-23-03768 [pii]
AID - 10.3390/s23073768 [doi]
PST - epublish
SO  - Sensors (Basel). 2023 Apr 6;23(7):3768. doi: 10.3390/s23073768.