dc.contributor.author | Cosgrove, John | |
dc.contributor.author | Walsh, Patrick | |
dc.contributor.author | Ruane, Patrick | |
dc.date.accessioned | 2023-01-20T13:45:46Z | |
dc.date.available | 2023-01-20T13:45:46Z | |
dc.date.copyright | 2022 | |
dc.date.issued | 2022 | |
dc.identifier.citation | Ruane, P., Walsh, P. and Cosgrove, J. (2022) Development of a digital model and metamodel to improve the performance of an automated manufacturing line, Journal of Manufacturing Systems, 65, pp. 538-549. https://doi.org/10.1016/j.jmsy.2022.10.011 | en_US |
dc.identifier.issn | 0278-6125 | |
dc.identifier.uri | https://research.thea.ie/handle/20.500.12065/4371 | |
dc.description.abstract | Digitalization in manufacturing is the conversion of information into digital format, the integration of this digital
data and technologies into the manufacturing process and the use of those technologies (eg: simulation) to
change a business model to provide new revenue and value-producing opportunities. Digitalization may be seen
as the increased generation, analysis, and use of data to improve the efficiency of the overall manufacturing
system. Simulation in manufacturing is often applied in situations where conducting experiments on a real
system is impossible or very difficult due to cost or time to carry out the experiment is too long. A key input to the
simulation model of automated equipment is the acquisition of valid data in relation to cycle time and reliability
of various workstations on this line. As a consequence of being able to simulate equipment processes and interact
with this validated simulation model, both the understanding of how the production system will perform under
varying reliability and cycle time conditions is achieved. The simulation model then enables the experimentation
of ‘what if scenarios’ that can be tested easily, while also providing a valuable tool to inform the maintenance
personnel what station reliabilities they need to target in order to sustain a high performing manufacturing line.
Simulation metamodeling is an approach to line design which is of great interest to design engineers and research
experts. However, its application in automated medical devices manufacturing line design has never been well
explored. The author has adopted an open-source simulation tool (JaamSim) to develop a digital model of an
automated medical devices manufacturing line in the Johnson & Johnson Vision Care (JJVC) manufacturing
facility. This paper demonstrates with a high level of rigour, fidelity and overall system design/approach, how a
digital model along with the use of a metamodel can be used for the development of an automated manufacturing
line in the medical devices industry. The digital model and metamodel can be used by manufacturing engineering
teams to perform scenario testing during the design and development phase of the line or as part of the
continuous improvement stage when the line is in full operation. The overall average absolute error when
comparing the simulation model outputs to the metamodel outputs was 0.87% was achieved with the metamodel
for the actual industrial application used by the author. | en_US |
dc.format | application/pdf | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | Journal of Manufacturing Systems | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Simulation | en_US |
dc.subject | Metamodel | en_US |
dc.subject | Digitalization | en_US |
dc.subject | OEE | en_US |
dc.subject | MTBF | en_US |
dc.subject | MTTR | en_US |
dc.subject | Reliability | en_US |
dc.title | Development of a digital model and metamodel to improve the performance of an automated manufacturing line | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.contributor.affiliation | Technological University of the Shannon: Midlands Midwest | en_US |
dc.description.peerreview | yes | en_US |
dc.identifier.doi | 10.1016/j.jmsy.2022.10.011 | en_US |
dc.identifier.endpage | 549 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-9003-7242 | en_US |
dc.identifier.startpage | 538 | en_US |
dc.identifier.volume | 65 | en_US |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | en_US |
dc.subject.department | Department of Mechanical & Automobile Engineering and Department of Electrical & Electronic Engineering | en_US |
dc.type.version | info:eu-repo/semantics/publishedVersion | en_US |