Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems

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

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. (2023). Capacity Modelling and Measurement for Smart Elastic Manufacturing Systems. SAE Technical Papers, Article 2023-01-0997. https://doi.org/10.4271/2023-01-0997

• 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/