A Multidisciplinary Approach for Optimization Design of CNC Machine Tools

The main objective of this research is to propose a multidisciplinary approach for the development and design of Computer Numerical Control (CNC) machine tools using numerical optimization methods combined Multi-Body Dynamic (MBD) analysis and to control design co-simulation. Metamodels based Sequential Approximate Optimization (SAO) for the co-simulation optimization problems are developed. The metamodels are constructed as approximate models for exact dynamic analysis responses by using simultaneous Kriging metamodeling method. SAO problems for single objective and multi-objective optimization designs are carried out based on the augmented Lagrange multiplier (ALM) method. An application of the proposed method on optimizing Proportional-Integral-Derivative (P-I-D) coefficients of PID controllers of a CNC machine tool model is performed to demonstrate the usefulness of integrating different research methods in numerical simulation. Therefore, this work overcomes a difficult task in tuning the PID controller which requires extensive experience and understandings of research and development (R&D) engineers. Moreover, the optimal PID controllers obtained by the multidisciplinary approach can help to increase the contouring accuracy of the CNC machine tools.

Robust Optimization and Kriging Metamodeling of Deep-Drawing Process to Obtain a Regulation Curve of Blank Holder Force

In recent decades, the automotive industry has had a constant evolution with consequent enhancement of products quality. In industrial applications, quality may be defined as conformance to product specifications and repeatability of manufacturing process. Moreover, in the modern era of Industry 4.0, research on technological innovation has made the real-time control of manufacturing process possible. Moving from the above context, a method is proposed to perform real-time control of a deep-drawing process, using the stamping of the upper front cross member of a car chassis as industrial case study. In particular, it is proposed to calibrate the force acting on the blank holder, defining a regulation curve that considers the material yield stress and the friction coefficient as the main noise variables of the process. Firstly, deep-drawing process was modeled by using commercial Finite Element (FE) software AutoForm. By means of AutoForm Sigma tool, the stability and capability of deep-drawing process were analyzed. Numerical results were then exploited to create metamodels, by using the kriging technique, which shows the relationships between the process parameters and appropriate quality indices. Multi-objective optimization with a desirability function was carried out to identify the optimal values of input parameters for deep-drawing process. Finally, the desired regulation curve was obtained by maximizing total desirability. The resulting regulation curve can be exploited as a useful tool for real-time control of the force acting on the blank holder.

Butterfly optimization algorithm for optimum shape design of automobile suspension components

This article presents an implementation of one of the latest optimization methods of obtaining light vehicle designs. First, the problem of coupling with a bolted rim is optimized using the butterfly optimization algorithm (BOA). Finally, the BOA is used to solve the shape optimization of a vehicle suspension arm. It is utilized from the Kriging metamodeling method to obtain equations of objective and constraint functions in shape optimization. At the end of the research effort in this paper, the weight reduction of the suspension arm by using the BOA is 32.9 %. The results show the BOA’s ability to design better optimum components in the automotive industry.