In most material removal processes, the size and shape of the stock material, the desired surface and the orientation of the part are known. If some or all of these factors are unknown, typical automatic systems will not be able to handle the situation. In reality, most of these cases are subsequently handled by human operators. This results in low productivity and inconsistency in the production and potential ergonomic problems for the human operators. Therefore, a new system needs to be designed to meet the requirements for material removal with unknown objects.;This dissertation presents a feasible and efficient automatic system for material removal with unknown processing factors. The characteristics of this type of processes were investigated. The corresponding inputs of the system were decided, while balancing the ease of use and the complexity of the system. A simple point sampling strategy was developed to sample the reference points, which are used to create the approximated surface for the unknown objects with a modified triangular based surface approximation method. A universal layer based path planning method was developed to guide the tool among the layers within the designated working area to remove the excess material effectively and efficiently without changing the programming codes.;This system was verified by simulations and a prototype of the grinding system
