A method for optimizing a manufacturing assembly line using a predictive model generated using cell and line production data associated with an active manufacturing assembly line, the manufacturing assembly line comprising a plurality of cells, each cell being configured to successively process a workpiece along the manufacturing assembly line, the manufacturing assembly line being different from the active manufacturing assembly line, the method comprising operating a processor to: receive an active cell data associated with at least one active cell during an operation of the active manufacturing assembly line, the active cell data comprising, for each active cell, at least one input state of that active cell and an active cell position of that active cell within the active manufacturing assembly line; receive an active line production data associated with the active cell data, the active line production data being representative of a production level of the active manufacturing assembly line in association with the respective active cell data; determine one or more production associations between the active cell data of each active cell and the production level of the active manufacturing assembly line, the one or more production associations identifying one or more relationships between the active cell data and the production level of the active manufacturing assembly line; evaluate the one or more production associations to identify one or more critical production associations to the operation of the active manufacturing assembly line, the one or more critical production associations corresponding to one or more statistically significant production associations; retrieve the active cell data and the active line production data associated with the one or more critical production associations; train the predictive model with the retrieved active cell data and the retrieved active line production data to predict the production level of the manufacturing assembly line; receive data associated with at least one cell of the manufacturing assembly line, the cell data including, for each cell, at least one input state of that cell and a cell position of that cell; extract feature data from the received data; determine a plurality of cell configurations for a cell, each cell configuration defining a different process for processing the workpiece by that cell; determine an efficiency score for each cell configuration by applying the extracted feature data to the predictive model to determine the production level of the manufacturing assembly line using that cell configuration; determine at least one target cell configuration from the plurality of cell configurations based on the efficiency score for each cell configuration; and apply the at least one target cell configuration to at least one corresponding cell of the manufacturing assembly line. receive an active cell data associated with at least one active cell during an operation of the active manufacturing assembly line, the active cell data comprising, for each active cell, at least one input state of that active cell and an active cell position of that active cell within the active manufacturing assembly line; receive an active line production data associated with the active cell data, the active line production data being representative of a production level of the active manufacturing assembly line in association with the respective active cell data; determine one or more production associations between the active cell data of each active cell and the production level of the active manufacturing assembly line, the one or more production associations identifying one or more relationships between the active cell data and the production level of the active manufacturing assembly line; evaluate the one or more production associations to identify one or more critical production associations to the operation of the active manufacturing assembly line, the one or more critical production associations corresponding to one or more statistically significant production associations; retrieve the active cell data and the active line production data associated with the one or more critical production associations; train the predictive model with the retrieved active cell data and the retrieved active line production data to predict the production level of the manufacturing assembly line; receive data associated with at least one cell of the manufacturing assembly line, the cell data including, for each cell, at least one input state of that cell and a cell position of that cell; extract feature data from the received data; determine a plurality of cell configurations for a cell, each cell configuration defining a different process for processing the workpiece by that cell; determine an efficiency score for each cell configuration by applying the extracted feature data to the predictive model to determine the production level of the manufacturing assembly line using that cell configuration; determine at least one target cell configuration from the plurality of cell configurations based on the efficiency score for each cell configuration; and apply the at least one target cell configuration to at least one corresponding cell of the manufacturing assembly line.