The measurement of lots to check process quality is crucial but also a non-added value operation in manufacturing systems. This paper is motivated by semiconductor manufacturing, where metrology tools are expensive, thus limiting metrology capacity which must be optimally used. In a context where multiple heterogeneous machines are sharing a common metrology workshop, the problem of minimising risk while considering metrology capacity arises. An integer linear programming (ILP) model is presented, which corresponds to a multiple-choice knapsack problem. Simple rounding heuristics are proposed, whose results on randomly generated instances are compared with the optimal solutions obtained using a standard solver on the ILP. Additionally, numerical experiments on industrial data are presented and discussed.