In this research, an experimental study is presented, which extends the usage of eddy current and load sensors in progressive stamping tools to optimize and continuously monitor the stamping process. The purpose of the research was to automatically detect material scrap before it leaves imprints on the part and based on the sensor’s readings, determine the optimal tool bottom position. The scrap thickness that needs to be detected was established in an experiment by visual evaluation of the result. To determine the optimal bottom position, a linear regression method was used, and the results were evaluated by part quality parameter. The research results consist of separate detection steps and the conclusion was made only after the serial type production. Overall results of scrap detection were influenced by the design of the existing tool. The bottom position detection consists of various readings interpretations and multi-step method descriptions. Based on the acquired results of both methods, implementing the in–die sensors was considered successful and applicable to new tools.