Software development for industrial automation applications is a growing market with high economic impact. Control engineers design and implement software for such systems using standardized programming languages (IEC 61131-3) and still require substantial manual work causing high engineering costs and potential quality issues. Methods for automatically generating control logic using knowledge extraction from formal requirements documents have been developed, but so far only been demonstrated in simplified lab settings. We have executed four case studies on large industrial plants with thousands of sensors and actuators for a rule-based control logic generation approach called CAYENNE to determine its practicability. We found that we can generate more than 70 percent of the required interlocking control logic with code generation rules that are applicable across different plants. This can lead to estimated overall development cost savings of up to 21 percent, which provides a promising outlook for methods in this class.