Optimizing the parameters of the manufacturing process for products in terms of metalworking equipment is one of the key tasks in technological preparation for production. This process is structurally complex, characterized by an ordered set of actions of various types. The basis for improving the efficiency of the technological process is the comprehensive optimization of the parameters of individual elements that form its structure. To solve this problem, an integrated model for comprehensive multi-criteria optimization of a structurally complex process has been developed, establishing a clear hierarchical relationship between its elements. The model is based on the structural decomposition of two processes: the process of forming individual design elements and the technological process of manufacturing a product. Structural hierarchical models have been developed for each process. The structure of the integrated model contains six levels of control. For each level of control, a set of target indicators and control parameters has been formed. The article presents the results of testing the proposed model using the example of optimizing the technological process of mechanical processing for the “Housing” product. As part of the study, structural and parametric optimization of the manufacturing process for this part was carried out. During the study, the structure of the technological processing route was optimized, as well as individual technological operations and technological transitions. Over the course of the work, the technological equipment and processing methods used for shaping a number of surfaces were replaced. As a result of the optimization, the overall labor intensity of the technological process for manufacturing the “Housing” product was reduced by 19.8%, and the manufacturing accuracy of the most critical surfaces was increased by 16.4%. The results confirm the effectiveness of the proposed model for comprehensive optimization of the mechanical processing technological process.

The article is devoted to the current problem of optimizing transport flows implemented within a mechanical engineering enterprise, where the efficiency of logistics operations directly affects the productivity and competitiveness of production. Optimization of the parameters of transport flows implemented within a mechanical engineering enterprise is a crucial component of technical production planning. The paper presents the results of the cargo transportation process analysis, defining many of its structural elements. Using these structural components, a multi-level model for designing and comprehensive optimization of transport flows has been developed. A two-level model of comprehensive structural and parametric optimization of individual transport operations has been proposed. A multi-level system of indicators for assessing the effectiveness of individual transport operations and transport routes has been developed. The article presents the results of testing the proposed model. During the study, a structural analysis of transport flows at a mechanical engineering enterprise was conducted, and a system for their comprehensive optimization was developed. The key element of the system was a modular algorithm for designing transport operations, ensuring flexible planning taking into account actual production constraints. The use of a robust approach and vector optimization criteria made it possible to develop solutions that are robust to uncertainties: a reduction in the target indicator of uniformity of labor intensity distribution by 22.5% and in the indicator of uniformity of cargo weight distribution by 17.33% was achieved. Moreover, the efficiency coefficient of vehicle utilization in terms of carrying capacity increased by 21.67%, and the actual values of the target indicators exceeded the optimization ones by an average of 6.4% and 2.72%, respectively, which confirmed the operability and stability margin of the solutions. The practical significance of the approach lies in the possibility of autonomous use of the system or its integration into the general production management system. The implementation of the subsystem will improve the rhythm of transport operations, reduce downtime, and minimize the risk of disruptions to production cycles.