MECHANICAL ENGINEERING MS THESIS DEFENSE BY BERKAY DEMIRYULEK



Title: Design and Implementation of Process Control for Deep Drawing Using Flange Draw-In

Speaker: Berkay Demiryülek

Time: August 10, 2022, 13.00

Thesis Committee Members:

Prof. Dr. Ismail Lazoglu (Advisor, Koç University)

Prof. Dr. Demircan Canadinc (Koç University)

Asst. Prof. Dr. Omer Music (TED University)

Abstract:

In sheet metal forming processes, using new materials with high strength and low formability and an increase in part design complexity leads to narrowing the process windows where high-quality parts can be formed without any defects. Moreover, these reductions in process limits increased the sensitivity to process variations such as changes in material properties and lubrication conditions, resulting in increased scrap rates and decreased productivity in mass production. In recent years, process control strategies and different blank holder systems have been developed and utilized in deep drawing to increase part formability and productivity. This thesis mainly focused on developing design methodologies for inline proportional plus integral (PI) process control to improve part quality and reproducibility in the existence of process variations. Moreover, a smart-compact cushion system containing a segment-elastic blank holder with multiple hydraulic actuators and process sensors for inline monitoring is designed and adapted in a servo-spindle press to conduct experiments. Finite element analysis (FEA) software tools are utilized to determine optimal process parameters such as blank holder force and material flow which are necessary for producing high-quality parts. Additionally, process variables such as flange draw-in and punch force are evaluated numerically and experimentally to determine their relationship with the failure, such as tearing and wrinkling. This work focuses on flange draw-in as a control variable that is manipulated by the blank holder force adjustments based on tracking a reference flange draw-in with the help of the PI process controller. The critical novelty presented is the use of draw-in as the reference parameter for PI-based process control, a combination that has not been previously investigated in the literature.

Systematic design and implementation of a process controller for deep drawing with a semi-complex rectangular sheet metal part are presented. First, according to the FEA simulation tool and experimental work, the deep drawing process model structure is derived in the form of discrete-time transfer functions. Second, the dynamic model parameters, which can vary with the die geometry, are estimated via system identification techniques based on experiments. Later, numerical simulation tools are utilized to develop a process controller based on the dynamic process model. The process controller is fine-tuned by using root-locus and frequency-response analysis. Eventually, the proposed inline process controller constructed in the simulation environment is implemented in the servo-spindle press via PLC. The experiments were performed in a servo-spindle press with the smart-compact cushion system that includes 16 hydraulic actuators to control draw-in outputs measured via displacement sensors placed around the sheet periphery. The results show that the proposed process control design has an excellent performance in tracking the reference flange draw-in and significantly improving the part quality and reproducibility in the presence of process variations.

Many in-development-phase and commercially available displacement sensors have been used to monitor flange draw-in during the deep drawing process. However, most of the sensors are not suitable for use in mass production conditions due to the high lubricant usage, vibration, and magnetic field variation affecting the measurement accuracy. Therefore, a robust sensor unaffected by these disturbances was also developed and validated as part of this thesis.