In today’s fast-changing business environment, organizations need to be adaptable and responsive to change. Effective decision-making enables companies to cope with uncertainty and adjust their strategies and operations promptly. In this context, the emergence of intelligent decision support systems (DSS) shows great promise. These systems enable companies to analyze data, identify patterns, and offer valuable insights to facilitate informed decision-making. An intelligent DSS for updating control plans is presented in this paper. The proposed system incorporates two methods to assist the decision-maker in choosing the optimal control scenario. The first involves making a manual decision based on several criteria. The second uses the case-based reasoning (CBR) technique to make an automatic recommendation. Moreover, the suggested recommender system (RS) enables the control plans to be updated regularly depending on the current state of the process quality. To increase the quality of decisions, CBR is used to acquire the necessary knowledge. The viability and applicability of the suggested RS are demonstrated through a practical case study.