The transition to mixed-model assembly lines in luxury automotive manufacturing demands increasingly sophisticated production system optimizations, particularly during strategic ramp-up phases where takt time reductions fundamentally reshape operational dynamics. This thesis presents a comprehensive industrial engineering project focused on the optimization of assembly line operations through a takt time reduction, from 32.25 to 24.78 minutes at Automobili Lamborghini’s SSC line, necessitated by the rump up of the Temerario model alongside continued Revuelto production. The project is based on a data-driven methodology structured around the AS-IS/TO-BE paradigm: initially, a detailed analysis of the existing 46-station hybrid system, 30 main line stations and 16 pre-assembly modules, identified critical bottlenecks and imbalances. Afterwards, a TO-BE redesign was developed and implemented, encompassing four integrated pillars: 1) the logistical re-dimensioning of the kitting system ("Normaleria"), achieving a 45% increase in component handling with 8.7% fewer trolleys; 2) the establishment of a rigorous RT1-driven data architecture for flexible fastener logistics in a mixed-model environment; 3) the strategic management and physical reconfiguration of safety-critical tooling via a dedicated Tools Relocation Matrix; and 4) the deployment of a Virtual Training platform for accelerated operator cycle re-learning. The implementation, executed during the Summer 2025 production closure, validated the redesign's efficacy. Key outcomes include improved system saturation, optimized workstation balance, and the creation of a resilient framework capable of supporting the accelerated production pace. The project demonstrates how systematic, integrated approaches combining lean logistics, digital data validation, and human-centric training, are essential for maintaining manufacturing excellence and flexibility in the high-stakes, low-volume production of ultra-luxury vehicles. The established methodologies provide a scalable template for future model introductions and further production system optimizations.
Takt Time Optimization and Mixed-Model Assembly Line Rebalancing at Automobili Lamborghini S.p.A.
MARCHESINI, PETRA
2024/2025
Abstract
The transition to mixed-model assembly lines in luxury automotive manufacturing demands increasingly sophisticated production system optimizations, particularly during strategic ramp-up phases where takt time reductions fundamentally reshape operational dynamics. This thesis presents a comprehensive industrial engineering project focused on the optimization of assembly line operations through a takt time reduction, from 32.25 to 24.78 minutes at Automobili Lamborghini’s SSC line, necessitated by the rump up of the Temerario model alongside continued Revuelto production. The project is based on a data-driven methodology structured around the AS-IS/TO-BE paradigm: initially, a detailed analysis of the existing 46-station hybrid system, 30 main line stations and 16 pre-assembly modules, identified critical bottlenecks and imbalances. Afterwards, a TO-BE redesign was developed and implemented, encompassing four integrated pillars: 1) the logistical re-dimensioning of the kitting system ("Normaleria"), achieving a 45% increase in component handling with 8.7% fewer trolleys; 2) the establishment of a rigorous RT1-driven data architecture for flexible fastener logistics in a mixed-model environment; 3) the strategic management and physical reconfiguration of safety-critical tooling via a dedicated Tools Relocation Matrix; and 4) the deployment of a Virtual Training platform for accelerated operator cycle re-learning. The implementation, executed during the Summer 2025 production closure, validated the redesign's efficacy. Key outcomes include improved system saturation, optimized workstation balance, and the creation of a resilient framework capable of supporting the accelerated production pace. The project demonstrates how systematic, integrated approaches combining lean logistics, digital data validation, and human-centric training, are essential for maintaining manufacturing excellence and flexibility in the high-stakes, low-volume production of ultra-luxury vehicles. The established methodologies provide a scalable template for future model introductions and further production system optimizations.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14251/4664