Innovative hybrid kitting systems for automotive manufacturing: performance analysis and optimisation
研究了汽车制造中利用工业4.0技术改进拣货系统，提出异步和顺序两种混合策略，通过真实数据建模优化组件分配以缩短周期时间，帮助决策者选择合适系统。
The automotive industry holds significant potential for robotic kitting systems. This potential depends on item characteristics, process speed, and available space. With mass customisation on the rise, this work explores how Industry 4.0 technologies can enhance kitting processes. It delves into the advantages and challenges of kitting systems, proposing innovative hybrid strategies to overcome these challenges. The study identifies critical research questions, quantitatively models inherent operations, and defines operational research tools for designing automated and collaborative kitting operations. Asynchronous and Sequential Hybrid Kitting Systems layouts are presented alongside an analysis of Mixed Integer Programming models proposed for optimal component allocation to minimise the cycle time. Real-world data from an automotive manufacturer is used to assess critical parameter impacts. Results show increased picking errors lead to more collaborative area allocation and longer cycle times. Simultaneous operator picking significantly reduces cycle times. Various component allocation scenarios highlight that optimal assignments yield lower cycle times, favouring the Sequential system. This work empowers industry decision-makers to choose a kit preparation system that enhances kit preparation quality through Asynchronous Hybrid Kitting or to adopt a faster assembly line-like approach for kitting preparation through Sequential Hybrid Kitting System.