How to go beyond educated guessing…

“If at first you don’t succeed, try, try again.”

Systematic process improvement, as described in several previous posts (Adjusting complex process variables: Drawbead shapes, Virtual Tryout or Process Engineering?,What is passing?, In the rearview mirror, Infinitely adjustable presses, when should we stop adjusting?), is a method of using multiple iterations of simulated forming processes where the design inputs are varied intentionally over a range of potential settings. The intent of this method is to systematically identify what values for the input settings address any forming issues that may arise for given combinations of tool, process, or production settings.

Some of you might wonder if such a process can work in practice. We had the opportunity recently to run a trial of this method, where we asked groups of process engineering professionals to attempt to manually interpret a simulated stamping process, with significant forming issues for visible splitting, challenges with wrinkles, and draw-in beyond acceptable limits. Each engineer was given the chance to define for themselves, based on their experience, the next process combination with which to attempt to address the forming issues.

Sample process simulation result as starting point of issue resolution attempts

Sample process simulation result as starting point of issue resolution attempts

They could choose to edit or define new settings for blank size and shape, drawbead restraints, binder pad pressure, tooling radii, and addendum wall angles. As one might imagine, given rooms full of engineers,  a seemingly infinite number of combinations could be rapidly defined. To find out which combination might yield the best result would require the participants in this study to run and evaluate the results before they could come to any conclusions.

This exercise was repeated in 10 locations with different participants. In all, there were over 340 discrete simulations created by the 137 participants, for an average of 2.5 iterations per participant. When all of these simulations were evaluated, it was found that only seven of the 340 simulations resulted in a resolution of all forming issues – and a “working process.”

Forty-three of the 340 discrete simulations resulted in some level of meaningful improvements to the issues. These near misses could eventually have been combined to further refine any of the forming issues, but that would still require time and effort by the engineers to critically evaluate each combination of their inputs into a new iteration – essentially seeding seeding a new “educated guess” and simulating a 341st iteration to find if all the forming issues had been addressed.

As an alternative to creating another batch of guesses to run, the workshop participants were asked to collect the ranges of the forming parameters that they used in order to define a matrix of upper and lower bounds for the defined forming parameters.

Sample matrix of parameter ranges set up by ten participants in 10 workshops

Sample matrix of parameter ranges set up by ten participants in 10 workshops

This matrix of ranges was then used to define a single input set for an AutoForm-Sigma Systematic Process Improvement (SPI) analysis. When defining an SPI run, users can determine for each process parameter a minimum and maximum value; the software automatically combines the ranges of input parameters into a set of simulation “realizations,” each representing a different combination of inputs.

In this way, the entire range of possible sensible process parameters as defined by the user — and all resulting outcomes — can be analyzed at once. In the end, at each workshop location a single AutoForm-Sigma run was performed based on the combined ranges defined by the participants. In eight of the ten workshops, the SPI method achieved precisely what the participants sought – namely a clear definition of which process parameter values addressed all the forming issues.

At two of the workshops, the Sigma set ranges were proven not to address all the issues. It might be tempting to think that this demonstrates a weakness in the approach. But consider the following: At those two locations, it was shown that the solution does not live within the ranges that the users had defined themselves — in other words, it was shown that NO solution existed within the parameters that they thought should work. How many more manual simulation setups and runs would it have taken to come to the same conclusion? To know that a solution does NOT exist (within the range of parameters deemed reasonable) is possibly even more valuable than being told what the solution is.


Technical Seminars 2016 reached 229 participants in China

AutoForm Technical Seminars 2016 were held in the major automotive hubs of China in Shanghai, Guangzhou, Changchun and Beijing in November. The aim was to link expertise from AutoForm with expertise from the Chinese market. An impressive number of 229 participants from automotive OEMs, manufacturing companies, components and parts suppliers together with related college teachers attended the events this year to engage in discussions and gave highly positive feedback.


Dr. Bart Carleer was introducing AutoFormplus R7 highlights

Dr. Bart Carleer, AutoForm Technical Director, gave his lecture on “The next level of process simulation”; the motto of AutoFormplus R7.


Participants got absorbed in the lecture

He talked about significant highlights of the latest released AutoFormplus R7 software including Progressive Die Application, material modeling and springback compensation. He also gave a brief introduction of our new family member –TriboForm, a company offering software solutions for the simulation of friction, lubrication and wear, through a more realistic consideration of tribological effects, a new level of simulation accuracy can be achieved.




Seminars in Shanghai, Guangzhou, Changchun and Beijing

Some of the winners with smile

Some of the lucky winners with a big smile

In addition to the giveaways we prepared for every customer, customized Swiss Army knives and watches with AutoForm logo were given to our lucky draw winners to express our gratitude for their trust and support.

All customers learnt some new functions and highlights of AutoFormplus R7, exchanged software operation experience with our technical experts, and established business contacts and relationships via the events.

We do hope and believe it was worthwhile for every customer to participate in the events, if you were not able to attend this time, no need to worry, let’s meet in 2017!

What is passing?

After the recent posts on failure prediction based on FLCs, several inquiries arrived through the blog and social media, regarding interpretation of other outputs for predicting failure modes. Commenters wanted to know the values, for various result variables, that might define the upper and/or lower limits, and how one interprets results to determine part/process feasibility. This brought to mind the fact that stamping engineers spend a major portion of every week analyzing the results from the simulation that they run and looking for any failures.

By plotting the strains measured on a current panel against the FLC we can predict relative formability of that part or process

By plotting the strains against the FLC we can predict relative formability

This often means switching between several result variables and reviewing result color scales plots looking for values that exceed the limit for each variable. Precisely what values constitute failure, is something that we can leave for a later (and possibly contentious) post. What does bear mentioning, right now, is how we can streamline this activity of applying specified limits for key result variables. Continue reading

Adjusting complex process variables: Drawbead shapes

In Finite Element Analysis, it is common to treat the metal restraint due to draw beads as numerical factors applied along a curve or set of curves. The use of these factors makes defining boundary conditions simple and computationally effective.

  • Need to increase material flow? Decrease the restraint factor
  • Want to tighten up the material flow? Increase the restraint factor

The application of a line bead restraint offers efficiency as it eliminates or at least greatly reduces the computational costs associated with running 3-D geometrical beads and eliminates the need to make any CAD adjustments if additional iterations are necessary to arrive at a safe result.

Adjusting the forming of  a part may require editing of countless bead shapes

Adjusting the forming of a part may require editing of countless bead shapes

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Hemming feasibility

The Auto/Steel Partnerships finding on hemming High Strength Steel

The Auto/Steel Partnerships finding on hemming High Strength Steel

We had the honor to be selected as the computer simulation partner for a recent Auto/Steel Partnership (A/SP) study that considered the feasibility of using higher strength and advanced high-strength steels to achieve weight reductions of hemmed closure panels: project #AS-8004. One of the A/SP mandates is to research, develop, and promote steel applications to achieve the fuel economy goals of the North American Auto industry, rather than the use of materials like aluminum or carbon fiber.

  Outer material Inner material
Supplier A BH-280 0.55mm−       Bake hardenable grade 280 DC04 0.7 mm
Supplier B BH-440 0.55mm−       Bake hardenable grade 440  DC04 0.7 mm
Supplier C DP-490 0.50mm−       Dual-phase grade 490  DC04 0.7mm

While advanced high-strength steels, or AHSS, are used extensively in the body-in-white, applications for the exterior “Class-A” panels have been limited to mild steel and some dent-resistant classes of material (~210 MPa yield strength). For this project, the steel-making partners provided three developmental materials of higher yield strengths to see if parts produced from these grades could, in fact, achieve panels of acceptable quality.

A/SP project geometry was created to emulate problematic geometry from real closure panels

A/SP project geometry was created to emulate problematic geometry from real closure panels

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Generic CAD or Dedicated Surfacing tools for Die Face design

Fifteen years ago, AutoForm introduced a novel idea to the sheet metal stamping industry: AutoForm-DieDesigner, a sheet metal simulation integrated-draw die-face development product. With this product, we upended a long-standing process engineering paradigm, where draw die-face concepts had to be meticulously surfaced in CAD prior to import and meshing for FEA analysis—a time-consuming and arguably sub-optimal process.   For the first time, die-face development within the formability engineering environment allowed for rapid iteration and improvement cycles, reducing the time spent to develop tooling concepts while improving sheet metal quality and feasibility.

This paradigm shift created an entirely new work flow for stamping process method planning in which the engineering of the die face—die tip, binder curvature, addendum geometry—and process settings like draw bead configuration, blank shape, and binder force could truly be simultaneously engineered and validated. Starting with part data only, an addendum for draw and line die concepts are created, for immediate process validation and improvement when necessary. Rapidly iterating between die face creation and evaluation of the process engineering concepts, represented a significant improvement in engineering practices, enabling stamping process engineers to design optimized stamping processes. This shift—from a process using FEA simulation as a CAD design validation tool to one where simulation is used to drive die-face engineering—created a new challenge as well: “How do we efficiently transfer the feasible die-face concepts  into fully faced CAD objects?”

Rapid DieFace development during process engineering necessitates recreation of CAD/CAM ready surfaces

Rapid DieFace development during process engineering necessitates recreation of CAD/CAM ready surfaces

With AutoForm-ProcessDesignerforCatia, our customers—like Fontana Pietro, whose success story we shared in an earlier post—rapidly recreate machinable surfaces based on their AutoForm-DieDesigner concepts.  AutoForm-ProcessDesignerforCatia brings a new approach for rapid die face creation to the CATIA Environment, creating repeatable and reliable machine-ready die faces that translate directly to and from AF-ProcessExplorer for final validation and compensation.

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Die Cost Estimation Accuracy: Apples to Apples

A colleague shared this story with me:

At a demo of AutoForm-CostEstimatorplus, he performed a live tool cost estimate using two similar parts planned for production with similar processes at the same plant. The cost estimate for the first part was roughly 900k€ (900,000 euro). The prospective customer was impressed by the speed of the result, but pointed out that the actual cost of the tool was 600k€. My colleague pointed out that cost results are based on a estimation standard that might not reflect the local charge rates for labor and resources. He then showed the prospect the resource estimations—hours of engineering, machining time, construction effort, tryout time, mass of cast materials and estimated cost of purchased components. Given that additional information, the prospect agreed that the resource estimate was reasonable and once appropriate charges for resources were factored in the cost would be accurate.

Tool cost estimates should reflect the process plan, the manufacturing resource requirements of tools supporting the plan, and cost of the resources

Tool cost estimates should reflect process plan, manufacturing resource requirements, and cost of resources

My colleague then repeated the demo for the “sibling” component, arriving at a cost of roughly 900k€. The parts were very similar in size and design complexity and followed a similar stamping process. Naturally, it fits that the resource requirements should be the same. But when presented with these results, the prospect frowned and said that this second component cost 1.2 million €. Their explanation: The second component was for the luxury line, while the first one was for the economy model.

Two versions of the same part for two different vehicle lines, with a total cost of 1.8 million €. Would the two stamping processes really require so great a difference in tool manufacturing resources, or is the difference a post justification for the luxury model? Were the number quoted price or actual costs? Did this organization compare their price expectations to their true costs? Were costs reported to fulfill expectations?

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Material Matters: Knowing your limit

The Formability of sheet metals

Previous posts Materials Matters- “The known unknowns”  and “Material plasticity visualized” covered the general aspects, common terminology, and formulation of the plastic properties in sheet metal forming problems. Accurate definition of flow curves, kinematic hardening and yield locus helps us to simulate the plastic flow of sheet metals during forming operation. Computer simulation uses those definitions to predict at each location in the sheet how the metal will deform and how strong the material is at each point after the deformation. Reliable prediction of the strains and resultant stresses in sheet metal allows us to simulate the springback with high accuracy. However, computing plastic deformation is not enough alone to predict the formability of a stamped component.

In the context of metal forming, formability can be defined in general sense as:

Capability of a material to be formed without failure

Failure can show itself as necking, splits, or wrinkles. A widely used method for failure prediction in industrial applications was proposed by Keeler (1965) and Goodwin (1968), namely the forming limit curve (FLC). The method has found a broad application because it is empirical, intuitive, and easy to understand and apply.

The concept is very simple: take the sheet metal you wish to characterize, deform it until necking, record the maximum achievable strains before necking and use these values as to define deformation limits.  Applying the limits to numerical simulation should predict if the deformation is safe or not.


Circle grid data collection for FLC determination

Circle grid data collection for FLC determination

Marciniak test circle grid

Marciniak test with optical strain measurement pattern applied


FLC determination

Experimental determination of these limits is performed by using different specimen geometries in order to obtain different deformation states. The specimens are usually stretched over spherical or cylindrical punches (Nakajima or Marciniak Tests). Traditionally, circle grid analysis was performed by technicians to samples artfully collected prior to the onset of failure, and then charted manually.

Major (ma) and Minor (ma) strains (e) can be measured using deformed circle grids

Major (ma) and Minor (ma) strains (e) can be measured using deformed circle grids

However, more recently optical strain measurement systems are utilized to capture the deformation history of the entire sheet surface. By this way the time point of localized necking and the corresponding strains can be identified with high accuracy. Obtained strain values from different specimen geometries are plotted in principal strain space as shown in the below figures.

Construction of forming limit curve (FLC)

Construction of forming limit curve (FLC)

Strain-space is defined with the vertical axis charing the major strain (ema , first principal strain) and the horizontal axis is the minor strain (emi , second principal strain). The third strain component, thickness strain, does not needed to be plotted. Due to volume constancy in metal plasticity, the third component is dependent on the plotted principal strains.

A forming limit curve (FLC) is constructed by fitting a curve to the obtained coordinates (ema, emi) in strain-space.  The FLC is specific for the grade of material tested, with same mechanical properties, at the same thickness. In time, if enough samples are taken, it is sometimes possible to apply a consistent curve shape for a range of materials and predict the forming limit of similar materials at different thicknesses. Such was the conclusion of Keeler-Goodwin et al with the publishing of their FLD0  (orFLC0), for mild steels. With the FLC0 formulation, given thickness and material n-value the location of a common shape FLC could be determined. However, for other materials a predictive shape and location of the FLC is not as widely accepted, requiring new empirical tests for each new material thickness and/or type.

Using FLCs

Later in the simulations the Forming Limit Curve defines the onset of necking. In post-processing of the finite element simulations, the strain state of each element is checked relative to the curve. If the strain state lies well below the curve, the elements are predicted to be safe. Points that lie below but are near the curve are considered to be marginally safe. A strain state over the line predicts a potential split. According to the position of the elements on the forming limit diagram other cases like thickening, excessive thinning or insufficient stretching can be defined.

By plotting the strains measured on a current panel against the FLC we can predict relative formability of that part or process

By plotting the strains measured on a current panel against the FLC we can predict relative formability of that part or process

Strictly speaking, FLCs are valid for forming operations with linear strain paths. FLC determination is performed using specimen geometries and deformations with linear strain paths. If strain paths change, e.g. the part is stretched then compressed then stretched again, the standard FLC may not reliably predict failure. This is a major concern for engineering forming operations; it is possible that with appropriate knowledge an FLC can be modified to include non-linear strain path effects.

The concept of FLC does not have information about shear deformation or failure, thickness effects, or edge quality of the sheets. For the cases like, shear fracture of AHSS, bending over sharp radii and edge crack sensitivity of laser cut sheets alternative fracture criteria can be utilized. These criteria complement the information in FLCs with maximum available shear strains or edge strains.

Future trends:

Given the limitations of FLCs further academic research is ongoing and focuses currently on following points

  • Time dependent evaluation of the FLD-test results in order to identify the onset of necking more accurately
  • Strain path dependent FLCs including anisotropy effects
  • Stress based FLCs
  • Determination of temperature dependent FLCs for hot forming applications
  • Continuum damage mechanics
  • Fracture prediction based on crystal plasticity and surface texture
  • Computation and prediction of FLCs based on constitutive equations


Springback Compensation in Hydroformed closed section parts

For the continued growth of tube-hydroforming, better methods for creating and validating springback compensation are essential. Upcoming vehicle programs forecast increasing use of Advanced High-Strength Steel along with more tube-hydroformed parts.  The release of AutoForm-HydroDesigner2016 represents the first commercial solution specifically for compensating closed-section geometries processed using tube-hydroforming processes—NC tube bending, preform, and hydroforming.

hydro-compensation-process First, it is necessary to recognize springback at the various stages of the process, from tube to finished product.  Initial planning typically begins with a pre-bent tube, which is loaded into the hydroforming die. AutoForm-HydroDesigner2016 automatically finds the centerline of the closed-section part and the tube fill addendum, and then proposes a bend schedule based on user inputs such as size(s) bending disk(s), number of bends allowed, and original tube diameter.

initial tube bending is based on centerline of the net shape part, but springback after bending can translate the tube away from planned centerline

initial tube bending is based on centerline of the net shape part, but springback after bending can translate the tube away from planned centerline

After bending, springback shifts the tube centerline away from the intended net shape of the part, possibly even preventing the loading of deformed tube into the following operations.  Manually defining the centerline of a part without compensation is already difficult; applying springback compensation to the centerline is not any easier. Using software to correct the centerline to account for springback builds a new bending schedule that addresses springback effects.

Springback compensation builds a new bending schedule to compensate for the springback observed; after springback the compensated part is closer to the net shape intent

Springback compensation builds a new bending schedule to compensate for the springback observed; after springback the compensated part is closer to the net shape intent

With the tube starting the hydroforming process closer to the planned net shape of the part, any further springback-induced translation of the tube, twist, or crowning specific to hydroforming deformation can be addressed. Without compensation software, engineers and toolmakers would have to make educated guesses of how to adjust the tooling geometry to correct for the springback. In CAD, new tooling geometry would need to be built or existing data morphed. New geometry would then either be cut as prototype/proof tooling or further evaluated using finite element analysis (FEA) software.

FIgure 2

Case Study: DP1000 Roof Rail, Ford Lincoln MKZ 2016

Figure 12: 2016 Lincoln MKZ and BIW of similar platform showing position of the roof rail (source: Great Design in Steel 2015)

2016 Lincoln MKZ and view of  similar vehicle showing position of the roof rail (source: Great Design in Steel 2015)

Schuler Group recently put this approach into practice with the engineering of the roof rail for the 2016 model year Lincoln MKZ. What follows are the results of the engineering study.

Forming process and part geometry of the Lincoln MKZ 2016 roof rail

Forming process and part geometry of the Lincoln MKZ 2016 roof rail

The selected material (Dual Phase 1000) is difficult to form with a conventional (high-pressure) hydroforming process; instead, a pressure-sequence hydroforming process is selected. The process starts with seven bending steps and a preforming operation, followed by hydroforming. At the beginning of hydroforming, lower pressures are applied during closing of the tools. After closing the dies, pressure increases for a final expansion/calibration of the part shape.

Springback results considering all forming operations

Springback results considering all forming operations

 Springback after bending to planned net shape (grey), tube after springback (red) will not fit the tool (yellow)

Springback after bending to planned net shape (grey), tube after springback (red) will not fit the tool (yellow)

Initially, springback after the bending operation is analyzed the predicted springback at the tube ends is large: 59.5 mm and 88.2 mm.  Comparing the tube after springback to the lower die, it is noted that the bent tube will not fit into the lower die without compensation. The tube would be damaged during closing of dies. Therefore the bending operation has to be compensated.

Thickness: 2.0 mm +/-0.1 mm
Outer diameter: 60.325 mm +/- 0.25 mm
Yield: 800 N/mm2 +/- 80 N/mm2
Tensile: 1080 N/mm2 +/- 80 N/mm2
Analysis of springback variation during bending

Analysis of springback variation during bending

Before compensating, the production process variation was analyzed. Robustness analysis showed a significant variation of the springback results of about 7.5 mm at the tube ends. At the left tube end where a nominal springback deviation of 59.5 mm was predicted, production deviations could range from 55.75 to 63.25 mm. Springback results proved sensitive to changes in the yield strength. If the incoming stock yield strength is higher than nominal, springback increases. If the yield strength is lower than nominal, springback decreases.

Since yield strength is prone to variation and the springback variation is not too high in the bending operation, compensation has been engineered for typical material properties, and the remaining potential shape variation has been addressed by engineering-appropriate lead-in surfaces of the forming operation.

Springback compensation of the bending operation

Springback compensation of the bending operation

The centerline has been compensated and a new bending schedule developed. Validation of the bending springback shows that the tube will align better after springback. Now we can continue analyzing the remaining springback effect caused by the following preforming and hydroforming operation.

 Springback results after hydroforming with compensated bending operation

Springback results after hydroforming with compensation applied to  bending operation only

Springback results found that the magnitude of springback was significantly reduced by the compensation of the bending operation. Previous results of 12.8 mm and 13.9 mm at the tube ends had improved to 3.2 mm and 3.7 mm, respectively.

However, springback results were still a little too high to meet the targeted tolerances of the part. With other areas of the tube out of tolerance, compensation had to be applied to the operations after tube bending. The tool surfaces needed adjustment to compensate any twisting, translation, and crowning effects.


Springback results after fully compensated process


AutoForm-HydroDesigner2016 was used to compensate the hydroforming tools automatically, based on the simulated springback results. The shapes of the preforming tools were also adjusted to fit to the compensated hydroforming die surfaces.

The resulting deviation of the part compared to the target geometry is now completely inside of the required tolerances, nearly net 0.0 with a few areas up to 0.35 mm. Only at the tube ends do we still find values of 1.4 mm and 0.8 mm. These areas are deemed not critical, as they are part of the tube addenda and therefore outside of part geometry.

Variation of the dimensional deviation of the formed part from the target geometry

Variation of the dimensional deviation of the formed part from the target geometry

A final robustness analysis, considering the unintended scattering of process parameters and material characteristics, indicates dimensional variation within the part is less than 0.35 mm. In combination with nominal springback deviation (all below 0.35 mm), it means that even with production noise the part will repeatably be within tolerance. The process layout and the compensated tool surfaces could be released with confidence.

The new methodology for springback compensation of hydroformed parts enables analysis of springback issues and definition of compensation strategies. This systematic approach helps identify root causes of springback and allows for designing and testing countermeasures for springback in each forming operation, before the final CAD tool design has been released. This approach significantly reduces the time-consuming CAD-based compensation, and reduces the tryout time, by eliminating deviations that otherwise prevent tool loading. The time saved in engineering and tryout results in lower costs and an earlier time-to-market for the final products.

Title Date City/Country Location Presentation
New Developments in
May 10, 2016 Fellbach,
Schwabenlandhalle Paper and Booth
New Developments in
Sheet Metal Forming
May 10 – 11, 2016 Fellbach,
Schwabenlandhalle Paper and Booth

Stamping System: Press speed and lubrication challenges

Lately, one of the most frequently asked questions in metal forming simulation has been “Can your software model the effects of a servo press?” The answer to this question has been YES and NO. It’s YES because, with most metal forming simulation software programs, we have the capability to define ram speeds and therefore can model the potential of the die to close the die at variable speeds, much like the servo press. It’s NO because in many cases, the ram speed would seem to not influence the simulation of the material deformation, especially when using hardening criteria with no strain rate sensitivity and a single friction coefficient value.

Measuring the effect of cycle time and ram speed on sheet metal deformation is more complex than simply telling the simulation that the tools are closing faster. The effects of speed on the mechanics of the press and die tooling, alignment, friction behavior, lube temperature, and force distribution are largely overlooked in the way that many analysts set up their stamping models. Today, simulations can be augmented by introducing the strain rate sensitivity for a material, easily input in many cases and commonly available. But not until the more influential interactions at the tool-lube-sheet interface can be modeled well will the potential of modelling ram speed be more fully realized.

The role of lubrication in the stamping system

In our previous post on the stamping system, several environmental variables within production sheet metal stamping are mentioned. In that post we listed variables such as blank surface, blank coating, tool surface, tool coating, and blank/die lubrication. These variables are often grouped together into one variable when conducting an engineering analysis as the friction coefficient.

The blank lubrication, die substrtate and coating, and blank material and coating are key friction drivers of the stamping system

The blank lubrication, die substrtate and coating, and blank material and coating are key friction drivers

Blank/Coil Production Line Die
Coating (if any) Lubrication (if any) Die surface and coating
Mill oil (friction coefficient) Lube (friction coefficient) Tool and surface condition
Grain and rolling direction Lube thickness and distribution Temperature
Substrate metallurgy Ram speed (cycle time)

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