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Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems

Elshafei, Basem; Mo, Fan; Chaplin, Jack C.; Arellano, Giovanna Martinez; Ratchev, Svetan

Authors

Basem Elshafei

Fan Mo

Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
CRIPPS PROFESSOR OF PRODUCTION ENGINEERING & HEAD OF RESEARCH DIVISION



Contributors

Fan Mo
Researcher

Abstract

Aerospace manufacturing is improving its productivity and growth by expanding its capacity for production by investing in new tools and more equipment to provide additional capacity and flexibility in the face of widespread supply disruptions and unpredictable demand. However, the cost of such measures can result in increased unit costs. Alternatively, productivity and quality can be improved by utilizing available resources better to reach optimal performance and react to emerging disruptions and changes. Elastic Manufacturing is a new paradigm that aims to change the response behavior of firms to meet sudden market demands based on automated analysis of the utilization of the available resources, and autonomous allocation of capacity to use resources in the most efficient manner. Through digitalization of the shopfloor, streaming data from equipment enables companies to identify areas for improvement and boost the efficiency without large capital expenditure. Additionally, the impact of supply chain disruptions can be reduced through demand forecasting, inventory optimization, early warning systems, and flexible reallocation of resources; all of which could be managed elastically through integrated data collection in the supply chain. This paper describes how smart factories with more flexibility and resilience can be achieved with semantically-enhanced quality analytics, maintenance solutions, and automated key performance indicator monitoring. An example of measuring the capacity utilization rate, by following the measurement of multiple KPIs from a shopfloor level using data from a real aerospace project is demonstrated showing the significance of monitored process performance.

Citation

Elshafei, B., Mo, F., Chaplin, J. C., Arellano, G. M., & Ratchev, S. Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems. Presented at Aerotech 2023, Fort Worth, Texas, USA

Presentation Conference Type Conference Paper (published)
Conference Name Aerotech 2023
Acceptance Date Nov 1, 2023
Publication Date Mar 7, 2023
Deposit Date Sep 28, 2023
Journal SAE Technical Papers
Print ISSN 0148-7191
Electronic ISSN 2688-3627
Publisher SAE International
Peer Reviewed Peer Reviewed
Article Number 2023-01-0997
DOI https://doi.org/10.4271/2023-01-0997
Public URL https://nottingham-repository.worktribe.com/output/25383456
Publisher URL https://www.sae.org/publications/technical-papers/content/2023-01-0997/