On the Integration of Additive Manufacturing for Aircraft Spare Parts Inventory Control

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This study evaluates additive manufacturing integration in multi-echelon aircraft spare parts inventory, finding decentralized AM optimal when repair times are shorter or repair probabilities are high, and centralized AM optimal otherwise, with non-moving and slow-moving parts being most suitable.

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This preprint evaluates whether integrating additive manufacturing (AM) into a multi-echelon aircraft spare parts inventory system improves optimization under intermittent demand. Using a scenario-based model, it compares no-AM baseline, AM integrated only at a central maintenance center (CMC), and AM integrated at both CMC and regional maintenance centers (RMC), across non-moving, slow-moving, and fast-moving spare parts, with outcomes depending on AM repair time relative to conventional process (CP) repair time and AM repair probability. The analysis finds decentralized AM allocation is optimal when AM repair time is faster than CP, and still optimal when AM repair time equals CP with AM repair probability above 70%, whereas centralized AM is optimal when AM repair time equals CP with AM repair probability below 70%. The work explicitly notes it is a preprint and not peer reviewed. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract Spare parts inventory management represents a challenge for aircraft companies. Determining the optimal allocation and consumption of spare parts is problematic due to the intermittent demand. Original equipment manufacturer (OEM) uses different models to evaluate inventory stock level to avoid the non-availability of the desired spare parts when required. With the recent implementation of additive manufacturing (AM) in many sectors, the implications of AM for spare parts inventory management and control models need more attention. This paper aims to evaluate the advantage of AM integration for spare parts optimization in a multi-echelon inventory system. It compares three scenarios for non-moving, slow-moving, and fast-moving spare parts. A scenario-based modeling approach is followed to draw out insights for managers. The first scenario considers the conventional case where there is no integration of AM. The second scenario considers AM integration only in the central maintenance center (CMC). The third scenario assumes AM integration in CMC and regional maintenance centers (RMC). This analysis showed that when AM repair time is inferior to conventional process (CP) repair time, the best scenario for AM manufacturing integration is a decentralized AM location. And when AM repair time equals CP repair time, and AM repair probability is superior to 70%, the decentralized scenario still the optimal integration solution. However, when the AM repair time equals CP repair time, and the AM repair probability is inferior to 70%, the centralized scenario is the optimal integration solution. Moreover, non-moving and slow-moving spare parts are the most suitable categories for optimal AM allocation. Finally, the paper offers guidelines on adopting AM in the aircraft supply chain and the impact on spare part inventory management.
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On the Integration of Additive Manufacturing for Aircraft Spare Parts Inventory Control | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article On the Integration of Additive Manufacturing for Aircraft Spare Parts Inventory Control Youssef Abidar, Amin Chaabane This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2113133/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Spare parts inventory management represents a challenge for aircraft companies. Determining the optimal allocation and consumption of spare parts is problematic due to the intermittent demand. Original equipment manufacturer (OEM) uses different models to evaluate inventory stock level to avoid the non-availability of the desired spare parts when required. With the recent implementation of additive manufacturing (AM) in many sectors, the implications of AM for spare parts inventory management and control models need more attention. This paper aims to evaluate the advantage of AM integration for spare parts optimization in a multi-echelon inventory system. It compares three scenarios for non-moving, slow-moving, and fast-moving spare parts. A scenario-based modeling approach is followed to draw out insights for managers. The first scenario considers the conventional case where there is no integration of AM. The second scenario considers AM integration only in the central maintenance center (CMC). The third scenario assumes AM integration in CMC and regional maintenance centers (RMC). This analysis showed that when AM repair time is inferior to conventional process (CP) repair time, the best scenario for AM manufacturing integration is a decentralized AM location. And when AM repair time equals CP repair time, and AM repair probability is superior to 70%, the decentralized scenario still the optimal integration solution. However, when the AM repair time equals CP repair time, and the AM repair probability is inferior to 70%, the centralized scenario is the optimal integration solution. Moreover, non-moving and slow-moving spare parts are the most suitable categories for optimal AM allocation. Finally, the paper offers guidelines on adopting AM in the aircraft supply chain and the impact on spare part inventory management. Spare parts inventory model aircraft additive manufacturing multi-echelon supply chain Full Text Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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