Fatigue Forecasting: Model-centric material database opens design exploration opportunities in PM

GKN Powder Metallurgy team earns MPIF Outstanding Technical Paper Award for fatigue life forecasting research

The function of components in engines, gear boxes and other systems highly impacted by vibration relies heavily on the performance of their fatigue strength. To design these components, it is critical for designers to understand the options in fatigue life processes and materials offered to select one that is optimal for the application. 

Though the geometry of many of these applications are ideal for powder metallurgy (PM), PM steels have historically been left out in early design discussions as their fatigue life performance was not well known. 

To excel against competing technologies - like casting and forging among others - in notch fatigue and material strength, the GKN Powder Metallurgy team engaged in comprehensive research of fatigue life forecasting models and has developed a first-of-its-kind fatigue parameters database for PM materials. The database includes intensive material data to support customers during design exploration and virtual validation efforts for thorough and accurate PM information.

The award-winning concept

PM steel materials and gray cast iron variants were compared during early testing of the research. Similarities between the material types were intensely analyzed for accuracy.
PM steel materials and gray cast iron variants were compared during early testing of the research. Similarities between the material types were intensely analyzed for accuracy.

GKN’s Dr. Markus Schneider and Dr. Virgil Savu have earned the 2019 Howard I. Sanderow Outstanding Technical Paper Award from the Metal Powder Industry Federation (MPIF) for the research conducted on this competitive material database. First of its kind in the PM industry, the database promotes timely product design exploration through accurate fatigue lifetime predictions. 

Due to its ability to produce near-net shape components, powder metal is often chosen for applications with strict requirements for space, weight and function. These components typically contain notches from the complexity in teeth, drillings and various cross-sections – PM materials offer a performance advantage in this area.  

Up-front discussions on fatigue strength typically underestimated a PM steel against a fully dense wrought steel. However, PM materials testing shows a low notch sensitivity: compared to a fully dense wrought steel with a turned notch from the outside, the PM steel shows little difference while the wrought steel shows a strong drop in fatigue performance.  

Combining low notch sensitivity and an increase in performance with adherence to complex geometries, PM materials capabilities are now accurately represented in a digital database to showcase the PM industry as a stronger candidate in design discussions.  

As a result of years of testing, the digital database now entails accurate fatigue-life parameters for a vast range of PM materials. GKN Powder Metallurgy continues to expand the database by testing additional PM material grades and offering robust global support to customers.

Opening early discussions for PM

Model-based decision making will lead future developments for the automotive industry. Customers will rely more heavily on accurate material databases for design requirements.
Model-based decision making will lead future developments for the automotive industry. Customers will rely more heavily on accurate material databases for design requirements.

OEMs now place a strong focus on reducing production launch timelines and expanding the design exploration space, and we see engineers assigning an emphasis on design and modeling to aid in this time sensitivity. Engineers require accurate, in-depth material properties to avoid costly and incorrect design outcomes.

Casting and forging material databases have been well-developed for years and are already readily available to OEMs in early design explorations. For PM to remain a competitive technology, when OEMS place a significance on modeling knowledge, an increase in accurate data is a necessity.  

A comprehensive material and processing data package brings PM technology into discussions at an earlier stage through design concept. The data accuracy, a significant improvement from standard material generalizations that downgraded specific material performance, positions PM materials to win business that was previously lost to insufficient, inaccurate data.  

While the database improves probability of sourcing a PM component, the benefits carry on through the entire production process. The fatigue-life research allows our teams to improve component designs from the concept phase. Before a material is inputted into the global database, extensive forecasting and testing is completed to guarantee the upmost accuracy.  

With a global team heading the research for GKN, fatigue-life testing will continue to expand material selection and grow PM’s competitive advantage against forging and casting materials. The accurate correlation between predicted fatigue life and observed fatigue life reiterates this database’s ability to generate beneficial material data for forecasting potential opportunities.   

Tested materials in the database

The following materials have been fully tested and are now included in the digital database. All hardened, sinter-hardened and case-hardened materials were tempered. 

Press and Sinter materials:  

  • MPIF FL-5108 Modified (Fe-1.8Cr-1Cu-0.2C Case Hardened & Tempered) 
  • MPIF FC-0205 Modified (Fe-3Cu-0.55P-0.55C) 
  • MPIF FD-0405 
  • MPIF FD-0205 
  • DIN Sint D32 (Sinter Hardened & Tempered) 
  • DIN Sint D32 
  • MPIF FL-4005 Modified (Fe-0.5Mo-1.3Mn-0.6C Sinter Hardened & Tempered) 
  • AS4300 (Fe-1Cr-1Ni-0.8Mo-0.6Si-0.6C Sinter Hardened & Tempered) 
  • MPIF FLN4C2-4905
  • MPIF FC-0205 

Metal Injection Molding materials:  

  • MIM 8620 (Case Hardened & Tempered) 
  • MIM 52100 (Hardened & Tempered) 

Additive Manufacturing material:  

  • AM Aluminum AlSi10Mg (Peen/T6/Peen) 

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Markus Schneider
Markus Schneider
Manager Modeling, Simulation and Fatigue