A Hybrid Intelligent System for Stamping Process Planning in Progressive Die Design

This paper presents an intelligent, hybrid system for stamping process planning in progressive die design. The system combines the flexibility of blackboard architecture with case-based reasoning. The hybrid system has the advantage that it can use past knowledge and experience for case-based reasoning when it exists, and other reasoning approaches when it doesn’t exist. A prototype system has been implemented in CLIPS and interfaced with Solid Edge CAD system. An example is included to demonstrate the approach.Singapore-MIT Alliance (SMA

PRODUCTION OF METAL-BASED IMPLANTS FOR CYRO-FACIAL INJURIES (BLUEPRINTS)

The main objective of this project is to propose a design for a progressive die for the production of metal based implants for Cyro-facial injuries. The bulk of the work would be to produce the detailed design drawings or blueprints for each progressive die components and to suggest the appropriate process plans for the fabrication of the respective progressive die components. The main concentration is put in producing the blueprint~ of a progressive die to produce the I-shaped metal implants. Throughout the first semester, literature reviews are done to gain knowledge about the working principle of the progressive die and how to design the various die components needed in the progressive die. Other than that, literature reviews are also done to gain information about the minimum tolerances, clearances and angular relief that need to be applied to each die components to ensure the quality of the progressive die and also the metal implants that will be produced by the progressive die. The basic step in producing a progressive die is to produce the blank layout. There are many ways in laying out the scrap strip. However, for this particular project, the blanks are laid out by adopting the narrow-run, one-pass layout. To optimize the usage of the material strip while ensuring the quality of the produced implants, minimum bridge allowances are applied between blanks and between blanks and edges of the strip. After calculation, the blanking force needed to cut the blank from the strip is 33707.52 N and since the press capacities are usua:lly in tons, a press of more than 3. 789 tons should be chosen to produce this particular metal implants. Other than that, it is also found that, a total of 63 metal implants can be produced from a 1 m material strip. On the other hand, in designing the die components, care had been taken in assigning the correct clearances, angular relief, allowances and tolerances for each part of the die components. This is to ensure the success of the particular progressive die. In general, the material selected for the implants are titanium and stainless steel strips while for the die components, are tool steels, mild steel and cast steel. The main processes involved for fabricating the die components are Wire EDM and milling

Optimization of strip-layout using graph-theoretic methodology for stamping operations on progressive die: a case study

The design of the progressive die stamping process is optimized through minimizing the number of die stamping stations in the strip layout to reduce the die cost. In order to accomplish such end, in this study, a graph-theoretic based method is implemented to model and optimize the strip layout design. This method starts with mapping stamping features into stamping operations. This step is followed by constructing two graphs to model the precedence and adjacency constraints among stamping operations based on a set of manufacturing rules. These two graphs are called: operation precedence graph and operation adjacency graph. In the next step, a topological sorting algorithm clusters the operations into partially ordered sets. Then, a graph coloring algorithm clusters the partially ordered operations sets into final sequence of operations. The graph-theoretic technique has been implemented on a part currently manufactured by laser cutting process technology in some Egyptian factory in Cairo. This study indicated that the graph-theoretic technique offers several advantages including the ease of programming and transparency in understanding the obtained strip layout design. This is besides being a systematic and logically approach to obtain an optimized strip layout design. In general, the progressive die manufacturing can increase productivity of sheet metal works in Egypt, only in situations of mass production. The limitation is that it requires considerable skill level and training for labor to conduct die strip layout design

PRODUCTION OF METAL-BASED IMPLANTS FOR CYRO-FACIAL INJURIES (BLUEPRINTS)

The main objective of this project is to propose a design for a progressive die for the production of metal based implants for Cyro-facial injuries. The bulk of the work would be to produce the detailed design drawings or blueprints for each progressive die components and to suggest the appropriate process plans for the fabrication of the respective progressive die components. The main concentration is put in producing the blueprint~ of a progressive die to produce the I-shaped metal implants. Throughout the first semester, literature reviews are done to gain knowledge about the working principle of the progressive die and how to design the various die components needed in the progressive die. Other than that, literature reviews are also done to gain information about the minimum tolerances, clearances and angular relief that need to be applied to each die components to ensure the quality of the progressive die and also the metal implants that will be produced by the progressive die. The basic step in producing a progressive die is to produce the blank layout. There are many ways in laying out the scrap strip. However, for this particular project, the blanks are laid out by adopting the narrow-run, one-pass layout. To optimize the usage of the material strip while ensuring the quality of the produced implants, minimum bridge allowances are applied between blanks and between blanks and edges of the strip. After calculation, the blanking force needed to cut the blank from the strip is 33707.52 N and since the press capacities are usua:lly in tons, a press of more than 3. 789 tons should be chosen to produce this particular metal implants. Other than that, it is also found that, a total of 63 metal implants can be produced from a 1 m material strip. On the other hand, in designing the die components, care had been taken in assigning the correct clearances, angular relief, allowances and tolerances for each part of the die components. This is to ensure the success of the particular progressive die. In general, the material selected for the implants are titanium and stainless steel strips while for the die components, are tool steels, mild steel and cast steel. The main processes involved for fabricating the die components are Wire EDM and milling

3D strip model for continuous roll-forming process simulation

Abstract The paper addresses the complexities for a reliable numerical simulation of the roll forming process. During the process, the material is progressively bent accumulating plastic deformation at each forming step. Strain hardening limits the material formability and may causes flaws of the final shape. A simplified method for the FEM modeling of the process has been developed introducing a narrow-strip 3D model. This approach leads better performance than the classical modeling method, in terms of results reliability and low computational time. In order to verify the proposed model, an experimental campaign of testing, for a specific roll forming production process, was carried out. On the quasi-static regime, the post necking behavior of the sheet metal was characterized. The Vickers hardness and the plastic strain of uniaxial tests were empirically correlated. By the hardness correlation, the plastic strain accumulated at different stages of the process was evaluated and compared with the numerical results. Further possible improvements of the method are highlighted

Development of a network-integrated feature-driven engineering environment

Ph.DDOCTOR OF PHILOSOPH

A Methodology for Data-Informed Process Control in Progressive Die Sheet Metal Forming

This thesis investigates the coupled relationship between the strip transfer and forming operations in progressive die sheet metal forming, including the effects of the strip layout geometry, and its effect on the process speed and accuracy. Servo-actuated strip lifters and feeder are considered to assist in minimizing the dynamic response of the strip during the transfer process. A methodology is proposed for identifying suitable trajectories to prescribe the motion of active strip lifters and feeder to obtain consistent part quality without risk of process failures for a progressive die operation. Multiple iterations of a finite element (FE) model were constructed in LS-DYNA to simulate a progressive die operation. Various FE analysis techniques were used to reduce the computational cost of the simulations to allow for enough data to be generated for machine learning applications. Both explicit and implicit time-integration schemes were considered in iterations of the FE model. Both single and dual carrier strip layouts were considered. The results of the FE simulations suggest that the single carrier strip layouts produce larger predicted dynamic displacements and rotations of the work-piece as compared to the dual carrier strip layouts during strip transfer. Furthermore, the single carrier strip layout is shown to be susceptible to strip misalignment. The final version of the FE model utilized geometry based on a demonstrator tool being deployed at the Technische Universität München. A total of 1000 simulations were generated, 500 each for the ‘I’ and ‘O’ stretch-web types using a single carrier strip layout. Each simulation considered a unique permutation of control inputs sampled from the set of possible strokes rates and trajectories for the lifters and feeder. Cubic splines were used to generate the trajectories for the strip lifter and feeder by varying the position of two knots used to define the shape of the spline. The results from the 1000 simulations indicate that in general the ‘S’ stretch-web produces a larger variance in the predicted dynamic response and ‘work-piece placement as compared to the ‘I’ stretchweb. Furthermore, the stroke rate and lifter trajectory were shown to have a large influence on the overshooting of the work-pieces during strip transfer and the probability of whether tooling collisions occurred. Multiple machine learning models were trained on the data generated by the final FE model. Two types of classifiers were constructed using neural network and XGBoost architectures. The first classifier predicts whether the clearance between the strip and binder are within a specified tolerance (to prevent collision with the tooling) during strip transfer. The second classifier predicts whether the placement accuracy of the work-piece on the forming die after strip transfer is within a specified tolerance. A range of tolerances were considered when labeling the data for both classifiers. Nestedcross fold validation was used to select the hyperparameter tuning and model selection. The machine learning classifiers were used to test all possible control inputs using a ‘minimum feed clearance’ of 10 mm and a maximum ‘work-piece placement error of 0.11 mm. The maximum stroke rate at which a given pair of lifter and feeder trajectories can operate was identified for all permutations. Five permutations that achieved the highest predicted stroke rate were simulated for an additional five strokes. The classifiers showed a reasonable ability to predict the ‘minimum feed clearance’ and ‘workpiece placement in the extended FE simulations for the selected trajectories, but, was unable to account for the strip misalignment which occurred after several strokes in all simulations. This research successfully demonstrates a methodology for using machine learning models trained on FE simulations to predict process outcomes of a progressive die operation with variable feeder and lifter trajectories. The FE simulations used to train the machine learning models were generated by adopting computationally-effective FE modelling techniques in a single press stroke model. The machine learning models were shown to reasonably predict the process outcomes of novel input permutations in a multi-stroke FE simulation. One of the largest constraints in this research is the FE simulation time which limited the model complexity that could be considered in the training set generation. Furthermore, the demonstration of the machine learning predictions for a multi-stroke process was limited due to the susceptibility of the single carrier strip layout to misalign after strip progression. Future work should consider the use of dual carrier strip layouts for the generation of the training data. Alternative approaches may also be considered, such as a machine learning framework for directly predicting the forward dynamics of the progressive die operation or a co-simulation approach in which a robust controller interacts directly with the FE simulation

A survey of the fluorescent lighting industry

Thesis (M.B.A.)--Boston Universit