Research on used power battery cutting parameters optimization for low carbon and high efficiency

The cutting process of used power battery is a key step for recycling its materials, and it is energy-intensive and high carbon emission process. To reduce the carbon emissions of the used power battery cutting process, the relationship between the carbon emissions of the cutting process and its process parameters was analyzed based on the safety requirements. Next, the multi-objective optimization model for cutting process parameters is established with the goal of minimum carbon emissions and shortest cutting time, which takes into account the constraints of the cutting device’s and the safety requirements. For the strong nonlinear characteristics of the optimization model, an improved PSO algorithm is used to solve the model. A case study of cutting a certain type of used power battery is illustrated to verify the validity of the established model.

OPTIMIZATION OF TURNING PARAMETERS USING AN ALGORTIM BASED ON COMBINED LINEAR AND BINARY SEARCH METHODS

Optimization of cutting parameters in machining operations is a complex task requiring extensive knowledge and experience to reach the maximum potential for cost reductions in manufacturing. Through the work presented in this paper a cutting parameters optimization algorithm for roughing and finishing turning has been realized. The proposed optimization algorithm is based on a combination of linear search and binary search methods, heaving as objective criterion the minimization of the machining time. Examples for roughing and finishing turning have been presented to illustrate the application of the proposed algorithm and analyse the results.

OPTIMIZATION OF TURNING PARAMETERS USING AN ALGORTIM BASED ON COMBINED LINEAR AND BINARY SEARCH METHODS

Optimization of cutting parameters in machining operations is a complex task requiring extensive knowledge and experience to reach the maximum potential for cost reductions in manufacturing. Through the work presented in this paper a cutting parameters optimization algorithm for roughing and finishing turning has been realized. The proposed optimization algorithm is based on a combination of linear search and binary search methods, heaving as objective criterion the minimization of the machining time. Examples for roughing and finishing turning have been presented to illustrate the application of the proposed algorithm and analyse the results.

Research on Parameter Optimization of Micro-Milling Al7075 Based on Edge-Size-Effect

In the process of micro-milling, the appearance of the edge-size-effect of micro-milling tools cannot be ignored when the cutting parameters are smaller than the cutting edge arc radius (r0) of the micro-milling tool or close to it, and it could easily lead to low cutting efficiency and poor surface quality of the micro-slot. Through micro-milling experiments on Al7075-T6 materials, the change of milling force in the plough zone and shear zone during micro-milling was studied, and the minimum cutting thickness (hmin) range was determined to be 0.2r0–0.4r0 based on r0 of the micro-milling tool. Subsequently, the effect of fz/r0 (fz denotes feed rate per tooth) on the top burr formation of the micro-slot, the surface roughness (Ra) of the micro-slot bottom, and the milling force was studied, and a size-effect band of micro milling was established to determine the strong size-effect zone, transition size-effect zone, and the weak size-effect zone. Finally, two different fz/r0 in the strong size-effect zone and the weak size-effect zone are compared, which proves that the main purpose of the cutting parameters optimization of micro-milling is to avoid cutting parameters locating in the strong edge-size-effect zone. The above conclusions provide a theoretical basis for the selection of micro-milling cutting parameters, and an important reference in improving the surface quality of micro-milling.

Optimization of machining parameters in turning of Inconel 718 Nickel-base super alloy

The high hardness and low thermal diffusivity along with the tremendous strength at high temperatures has rendered the nickel-base super alloys Inconel 718 one of the most difficult to cut material. It possesses a wide range of applications including aerospace as well as chemical and petrochemical industries, and is primarily used in the manufacture of aircraft gas turbines, space vehicles, nuclear power systems, and medical equipment. The present study is mainly focused on the cutting parameters optimization that leads to minimum surface roughness, cutting force and power, specific energy and maximum productivity during the turning of the molded Inconel 718 using a carbide cutting tool. The analysis of variance (ANOVA) method is applied to identify the cutting parameters that most influence the response criteria, and the response surface methodology (RSM) along with the desirability function (DF) approaches are further used to develop the prediction model that addresses the optimization procedure. The different parameters are considered one at a time in order to evaluate the sensitivity of the response (OFAT). This procedure led to identify the nose radius (rε), the feed rate (f), the depth of cut (ap) and the cutting speed (Vc) as the most significant factors on both the surface roughness and the cutting forces. Furthermore, the product (f × ap) and the cutting speed (Vc) were found to be the most dominant factors on the specific energy.