Nowadays, high flexibility and responsiveness towards capacity adjustments are key to successful production planning and control in manufacturing. Moreover, many companies – especially job shops – have to deal with short-term re-scheduling. This article presents an approach for knowledge-based process planning to enable an economic evaluation of re-scheduling in the manufacturing system. For that purpose, the manufacturing costs for each workpiece are calculated based on determined parameter sets and process time under consideration of potential capacity adjustments. The knowledge-based process planning is necessary to derive reliable process times for re-scheduling and cost calculating. Hence, a pre-study is carried out to define flexible machine learning algorithms for knowledge-based process planning. © 2019 The Authors. Published by Elsevier Ltd.