Case Study: Blade Runners

By The Business Analyst Team


Insights into a helicopter production issue lead to a big award and even bigger cost savings.

Aerospace Manufacturing / Quality Improvement

Profile: The largest global helicopter manufacturer in terms of both revenue and deliveries.


The Challenge:

A key blade production department began experiencing sporadic occurances of waves and ripples on the spars of helicopter blades resulting in large costs due to scrap and rework. The three components of this specific spar - called the upper, middle and lower core - are manufactured separately and forged together through an advanced welding process called prepolymerization.

This business, having invested heavily in Six Sigma training, conducted several sessions of Practical Problem Solving (PPS), yet failed to uncover answers. The production director decided more data was necessary and led an effort to collect multiple sources of existing data while working with production line workers to track new data. The primary focus was on tracking the viscosity of the resin used and the resulting hardness of the spars.


The Solution:

Once the data was collected, the team had values for a large number of parameters. Still, it was difficult for the blade department to fully understand the relevance of the parameters on the outcome of production. Once the data was loaded into MondoBrain, the team was able to manipulate the data to observe the spar reactions at different combinations and ranges of parameters.

The team already had a working theory that by changing the polymerization temperature to INCREASE the hardness of the intermediate core, they could make a difference in reducing defects. What MondoBrain’s intelligent dashboards showed however, was that it was also necessary to REDUCE the hardness of the upper and lower cores in order to maximize default reduction. The findings were presented to the lead engineer who took time with the team to confirm their interpretation of the data findings. Changes in the production process are never made lightly and require extensive review. Yet, after only a week the team came to a consensus and engineering gave the green light to implement the new parameters. MondoBrain enabled the team to combine the power of artificial intelligence with their collective, human expertise to uncover and refine the solution to the problem.


The Results:

Experiments were conducted in two phases to obtain a temperature at which no wave appeared on the spar after polymerization. The team started producing spars at this new temperature. According to the production director, after the first 10 or 20 spars were produced without defect, it - in theory - the positive results could have been ascribed to a string of good luck. However, by the time the team had produced another 30 or 40 stars without issues, everyone knew the dramatic improvement was due to the adjusted temperature settings discovered via MondoBrain analysis. By the time the team had produced 100 new spars without ripples or scrap, the team was recognized internally with the aerospace company’s highest award for quality innovation. In a global internal newsletter highlighting the team achievement, it was noted that the savings associated with the solution were considerable as the alternative - essentially a trial and error approach - would have required tremendous time and resources as each defective spar cost the company a significant amount of dollars.