This thesis presents a comprehensive analysis of three projects undertaken at Castel s.r.l., a prominent Italian company specializing in refrigeration and air conditioning component manufacturing. The projects, namely the Warehouse Project, Pickling Project, and 762 Project, aimed at improving operational efficiency, product quality, and performance across various aspects of the company’s operations. The Warehouse Project addressed issues related to elevated warehouse workload and operational inefficiencies. Through data collection, Gemba Walks, and root cause analysis, key problem areas were identified, such as list preparation, placement of arrivals, and returns management. Short-term, medium-term, and long-term countermeasures were developed to enhance warehouse operations, with ongoing monitoring to assess their impact. The Pickling Project focused on challenges in the pickling process, including product quality and material management. By creating qualitative goals, analysing root causes through Fishbone diagrams, and implementing targeted countermeasures, improvements were achieved. Further enhancements are planned, including real-time data integration and quality control of incoming acids. The 762 Project centred on optimizing a new assembly line’s performance and quality parameters. Detailed process analysis led to the identification of root causes for defects, machine stoppages, and bottlenecks. Countermeasures were devised and implemented to reduce scrap rates and enhance efficiency. Monitoring results demonstrated substantial improvements in both quality and performance, with the OEE also significantly increasing. In conclusion, this thesis highlights the success of the Lean Thinking and A3 Thinking methodologies in improving different business areas in Castel. The results obtained from these projects highlight the potential for continuous improvement in manufacturing processes and provide a solid foundation for future efficiency enhancements.
Questa tesi esamina dettagliatamente tre progetti svolti presso Castel S.r.l., un’importante azienda italiana specializzata nella produzione di componenti per il condizionamento dell’aria e la refrigerazione. I tre progetti, nominati come Warehouse Project, Pickling Project e 762 Project, sono stati concepiti con l’obiettivo di migliorare l’efficienza operativa, la qualità del prodotto e le prestazioni in tre diverse aree aziendali. Il Warehouse Project si è focalizzato sul carico di lavoro elevato del magazzino e sulle inefficienze operative. Attraverso la raccolta di dati, Gemba Walks e la root cause analysis, sono state identificate le principali attività con maggiore impatto sul carico di lavoro complessivo del magazzino. Sono state quindi sviluppate contromisure a breve, medio e lungo termine per migliorarle, con un monitoraggio continuo per valutarne l’efficacia. Il Pickling Project ha affrontato sfide legate alla qualità e alla gestione dei materiali nel processo di decapaggio. Dopo un’ analisi delle cause, sfruttando principalmente i diagrammi Fishbone e l’implementazione di contromisure mirate, ha migliorato il consumo dell’acido, la qualità delle componenti e il flusso dei materiali. È stato inoltre suggerito di implementare azioni future come il controllo della qualità degli acidi in ingresso. Il 762 Project si è concentrato sul miglioramento dei parametri di rendimento e qualità di una nuova linea di assemblaggio. Un’analisi del processo ha portato all’individuazione delle root causes degli scarti e delle fermate della macchina. Sono state sviluppate e implementate dunque contromisure per ridurre tali inefficienze, migliorando notevolmente sia in termini di qualità che di rendimento, con un notevole aumento anche dell’OEE. In conclusione, questa tesi mette in evidenza il successo delle metodologie Lean Thinking e A3 Thinking nel miglioramento di diverse aree aziendali in Castel. I risultati ottenuti da questi progetti evidenziano il potenziale per un miglioramento continuo nei processi di produzione e forniscono una solida base per futuri progressi.
Exploiting the A3 model and lean methodology for three improvement projects in a manufacturing company
ROMANO, ANDREA
2022/2023
Abstract
This thesis presents a comprehensive analysis of three projects undertaken at Castel s.r.l., a prominent Italian company specializing in refrigeration and air conditioning component manufacturing. The projects, namely the Warehouse Project, Pickling Project, and 762 Project, aimed at improving operational efficiency, product quality, and performance across various aspects of the company’s operations. The Warehouse Project addressed issues related to elevated warehouse workload and operational inefficiencies. Through data collection, Gemba Walks, and root cause analysis, key problem areas were identified, such as list preparation, placement of arrivals, and returns management. Short-term, medium-term, and long-term countermeasures were developed to enhance warehouse operations, with ongoing monitoring to assess their impact. The Pickling Project focused on challenges in the pickling process, including product quality and material management. By creating qualitative goals, analysing root causes through Fishbone diagrams, and implementing targeted countermeasures, improvements were achieved. Further enhancements are planned, including real-time data integration and quality control of incoming acids. The 762 Project centred on optimizing a new assembly line’s performance and quality parameters. Detailed process analysis led to the identification of root causes for defects, machine stoppages, and bottlenecks. Countermeasures were devised and implemented to reduce scrap rates and enhance efficiency. Monitoring results demonstrated substantial improvements in both quality and performance, with the OEE also significantly increasing. In conclusion, this thesis highlights the success of the Lean Thinking and A3 Thinking methodologies in improving different business areas in Castel. The results obtained from these projects highlight the potential for continuous improvement in manufacturing processes and provide a solid foundation for future efficiency enhancements.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/211064