A system (200, 300) supporting predictive and preventative maintenance, the system (200, 300) comprising: a plurality of manufacturing cells (10, 210, 310) within a manufacturing environment, wherein each manufacturing cell (10, 210, 310) of the plurality of manufacturing cells (10, 210, 310) includes a cell controller and at least one of welding equipment, cutting equipment, or additive manufacturing equipment; a central controller (220, 320); a communication network (230, 330) operatively connected to the central controller (220, 320) and the plurality of manufacturing cells (10, 210, 310) and configured to support data communications between the central controller (220, 320) and the cell controller of each of the plurality of manufacturing cells (10, 210, 310), characterised in that a feedback mechanism is provided on a manufacturing cell to provide feedback data as cell data, the feedback data being based on the amount of damage suffered by a component, and in that the central controller (220, 320) is configured to: collect cell data over time from the cell controller of each of the plurality of manufacturing cells (10, 210, 310), via the communication network (230, 330), wherein the cell data is related to at least one of operation, performance, or servicing of a same component type of each of the plurality of manufacturing cells (10, 210, 310) to form a set of aggregated cell data for the component type, wherein a component of the component type is associated with the at least one of the welding equipment, the cutting equipment, or the additive manufacturing equipment, and analyze with machine learning technology the set of aggregated cell data, including the feedback data, to generate a predictive model related to future maintenance of the component type. a plurality of manufacturing cells (10, 210, 310) within a manufacturing environment, wherein each manufacturing cell (10, 210, 310) of the plurality of manufacturing cells (10, 210, 310) includes a cell controller and at least one of welding equipment, cutting equipment, or additive manufacturing equipment; a central controller (220, 320); a communication network (230, 330) operatively connected to the central controller (220, 320) and the plurality of manufacturing cells (10, 210, 310) and configured to support data communications between the central controller (220, 320) and the cell controller of each of the plurality of manufacturing cells (10, 210, 310), characterised in that a feedback mechanism is provided on a manufacturing cell to provide feedback data as cell data, the feedback data being based on the amount of damage suffered by a component, and in that the central controller (220, 320) is configured to: collect cell data over time from the cell controller of each of the plurality of manufacturing cells (10, 210, 310), via the communication network (230, 330), wherein the cell data is related to at least one of operation, performance, or servicing of a same component type of each of the plurality of manufacturing cells (10, 210, 310) to form a set of aggregated cell data for the component type, wherein a component of the component type is associated with the at least one of the welding equipment, the cutting equipment, or the additive manufacturing equipment, and analyze with machine learning technology the set of aggregated cell data, including the feedback data, to generate a predictive model related to future maintenance of the component type. collect cell data over time from the cell controller of each of the plurality of manufacturing cells (10, 210, 310), via the communication network (230, 330), wherein the cell data is related to at least one of operation, performance, or servicing of a same component type of each of the plurality of manufacturing cells (10, 210, 310) to form a set of aggregated cell data for the component type, wherein a component of the component type is associated with the at least one of the welding equipment, the cutting equipment, or the additive manufacturing equipment, and analyze with machine learning technology the set of aggregated cell data, including the feedback data, to generate a predictive model related to future maintenance of the component type.