There is interest in the sheet metal industry on how to adopt Industry 4.0 into their legacy forming practices to significantly improve productivity and product quality. Figure 1 illustrates four important variables influencing part quality: material properties, die friction response, elastic deflection of the tool, and press dynamic characteristics. These variables are usually difficult to measure or track during the production runs. When these variables significantly influence the part quality and the scrap rate increases, the operators manually adjust the forming press parameters (speed and pressure), lubricant amount, and tooling setup. However, these manual adjustments are not always possible or effective and can be costly for the increased part complexity.
The ultimate vision for Industry 4.0 in sheet metal forming is an autonomous forming process with maximum process efficiency and minimum scrap rate. This is very similar to the full self-driving (FSD) vision of the electric vehicle today. This will be valuable for the automotive industry that has to process large production volumes with various steel grades.
For example, normal variations of the incoming material properties for Advanced High-Strength Steel (AHSS) may have a significant effect on part quality associated with necking, wrinkling, and cracking, which in turn drastically increases the production cost. This variation of the incoming material properties increases uncertainty in sheet metal forming by making consistent quality more challenging to achieve, thereby increasing the overall manufacturing cost. A nondestructive evaluation (NDE) can be a useful tool to measure incoming material properties.
There are several types of NDE sensors. Most of the sensors need further development or are not suitable for production applications. However, some of the NDE sensors, such as the eddy current tools, laser triangulation sensors equipment, and equipment developed by Fraunhofer IZFP called 3MA (micromagnetic, multiparametric microstructure, and stress analysis), have already been applied to a few limited production applications. These sensors can be used to provide data during production to select the optimal parameters. They also can be used to obtain material properties for finite element model (FEM) analysis. Studies in deep drawing of a kitchen sink production used a laser triangulation sensor to measure the sheet thickness and an eddy-current sensor to measure the yield strength, tensile strength, uniform elongation, elongation to break, and grain size of the incoming material. The material data is used as an input for simulations to generate the metamodels to determine the process window, and it is used as an input for the feed-forward control during the process.K-27
Figure 2 shows how NDE tools are used for feed-forward controls and cameras for feedback control to determine the optimum press setting on sink forming production.
Another study proposed the use of Fraunhofer’s 3MA equipment to determine the mechanical properties of incoming blanks for a sheet forming process. The 3MA sensor correlates the magnetic properties of the material with the mechanical properties and calibrates the system with the procedure outlined in Figure 3. The study showed a good correlation between the measurements from the sensor and the tensile testing results; however, the sensor should be calibrated for each material. Also, the study proposed to use a machine-learning algorithm instead of a feed-forward control to predict the most effective parameters during the drawing process.K-28
Technologies associated with Industry 4.0 have a natural fit with AHSS. The advanced slide motion capabilities of servo presses combined with active binder force control can be paired with stamping tonnage and edge location measurements from every hit to create closed-loop feedback control. With press hardening steels (PHS), vision sensors and thermal cameras can be used for controlling the press machine and transfer system.
Have a look at the Dr. Kim’s detailed article on Industry 4.0 for more examples of NDE sensors, as well as information on applying Industry 4.0 to forming process controls.
|Thanks are given to Hyunok Kim, Ph.D., Director of EWI Forming Center, who contributed this article.|