Algorithm 1: Grid search

INPUT: The current machine parameters M, the current machine run time r, the vector E for ambient sensor data, allowed machine parameters ranges, and a preference function f which rates the desirability of a prediction goal and new machine parameters. OUTPUT: New machine settings M’best FOR each machine parameters vector M’ so that each element is within the defined range DO |   Compute the predicted surface quality s = Q1(M’, r, E) |   Compute the predicted weight w = Q2(M’, r, E) |   Compute the predicted dimensions d = Q3(M’, r, E) |   IF the current loop iteration is the first or if f(s, w, d, M’, M) > f(sbest, wbest, |    dbest, M’best, M) THEN |   |   Set M’best = M’. |   |   Set sbest = s. |   |   Set wbest = w. |_    |_   Set dbest = d. return M’best