Foundry is an industry that is both very old and very forward-looking. It is an essential base for several industrial sectors in today’s world. However, the metal casting industry faces a lot of challenges, including quality. There is a need for a converging system that orients all the resources towards meeting the quality requirements throughout the whole process. Zero Defect Manufacturing (ZDM) is a concept that aims to meet this need by adopting the four strategies of Detection, Prevention, Prediction and Repair. In that context, ZDM has been a subject of several collaborations between industrial sectors and the scientific community given its importance to the industrial field. Nevertheless, there is a lack of research into the implementation of this concept in certain types of industries, such as foundries. This thesis aims to fill this gap by presenting a generic review and a better understanding of the implementation of the ZDM approach in foundries. A systematic literature study has been conducted and the result has been compared to the empirical data collected via interviews with managers working in the metal casting industry. It was found that the nine key enablers of ZDM implementation in foundries are 1) Sensors & embedded systems, 2) AI & DigitalTwins, 3) Advanced robotics, 4) Connectivity & mobility, 5) Cloud computing, 6) Edge computing, 7) Forecasting & Modelling, 8) Business Solutions, 9) Intelligence & control systems. Automation enhances ZDM in foundries by enabling continuous and consistent data collection throughout the whole process. Ensuring skilled labour in specific disciplines such as PLC programming and statistics is seen to be a major challenge for foundries. At the end of the thesis, propositions for future studies in the field of ZDM in foundries and the role of future technologies, such as metal 3D printing, are proposed.