Optimization of Cutting Parameters for Deep Hole Boring of Ti-6Al-4V Deep Bottle Hole.

In this study, the cutting parameters for machining deep bottle holes (deep holes with complex profiles and length-to-diameter ratio greater than 10) were optimized based on cutting simulation, a regression analysis genetic algorithm, and experimental validation. The influence of cutting parameters on cutting force and cutting temperature was analyzed using the response surface method (RSM), and the regression prediction model of cutting parameters with cutting force and most cutting temperature was established. Based on this model, multi-objective optimization of cutting force and material removal rate was carried out based on a genetic algorithm, and a set of optimal cutting parameters ( = 139.

Multiobjective Optimization of Cutting Parameters for TA10 Alloy Deep-Hole Drilling.

In order to obtain better quality TA10 pipes, the Boring and Trepanning Association (BTA) deep-hole drilling process is used. However, this type of machining leads to difficult chip removal, tool wear, and poor hole-surface quality. In this study, a deep-hole drilling experiment was conducted on TA10 workpieces using the designed tool with different process parameters, and the process parameters were optimized by machining results with multiple objectives such as chip morphologies, tool wear, hole-axis deflection, and hole surface roughness.

Distributed Function Mining for Gene Expression Programming Based on Fast Reduction.

For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model.