Optimization of production processes by defining priorities with Analytic Hierarchy Process (AHP)

This paper explores the application of the Analytic Hierarchy Process (AHP) as a systematic methodology for optimizing manufacturing processes by defining strategic priorities. The research focuses on addressing the challenge of efficient allocation of limited resources in modern manufacturing environments, where multi- criteria decision-making is becoming increasingly complex. The paper develops a complete AHP model that includes four levels of hierarchical structure: strategic goal, main criteria (cost, quality, time, safety and sustainability), sub-criteria and alternative improvement strategies. Through the application of comparison matrices and mathematical calculations of priorities, the model allows for a quantitative assessment of four key alternatives: process automation, implementation of Lean methods, advanced data analysis and personnel training. The research results indicate that the implementation of Lean methods receives the highest priority (0.372), followed by advanced data analysis (0.285), automation (0.215) and training programs (0.128). These findings reveal the importance of balancing short-term operational improvements with long-term strategic investments. The case study demonstrates how the AHP methodology provides a transparent and demonstrable approach to decision-making, enabling better resource management and reducing subjectivity in the decision-making process. Sensitivity analysis confirms the robustness of the results and their applicability in real production conditions.

Keywords: ahp, optimization, production processes, multi-criteria decision making, prioritization