Automated Algorithm for Nonlinear Optimization of Mechanical Pre-Processing

One of the urgent tasks for automated multivariant design of the technological process is the selection of optimal regimes of mechanical treatment on all key transitions of each technological operation. When implementing this specific task, one faces numerous problems, such as the choice of the solution method, the choice of the optimization criterion at different stages of treatment, definition of feasible solutions area. The use of linear programming techniques in implementing this algorithm requires a certain simplification of the resulting solutions. This technique works very well with limited computational resources. As the target function and system of constraints are nonlinear when describing the optimal metal cutting process, the most appropriate computing algorithm to efficiently solve the nonlinear programming problem is based on Lagrangian multiplier method. This paper focuses on automation of such specific task for one-tool mechanical metal-working

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