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standards. They evaluated the process and identified several input variables, which included the temperatures of the sealing system’s front and back heating bands and the speed of the system.
Now the team needed to assess each of these variables and determine how they affected the quality of the pouch seal. Which inputs were most important? And where should the operators set the temperatures and speed of the system to ensure each pouch had a strong seal?
That’s where the statistical method called design of experiments (DOE) comes in. A designed experiment lets you simultaneously change and assess more than one input variable at a time, then uses statistical analysis to get meaningful results about all input variables of interest. You can quickly determine which factors matter, and then adjust the process to get the desired results.
variables and the two-way interactions between them.
The analysis identified front and rear temperatures as significant factors, as well as the two-way interaction between them. Speed was not a significant factor for seal strength, which allowed the team to remove it from the model.
By focusing on the critical factors identified in the designed experiment, the team devised optimal process settings to ensure the new pouches had strong seals. Now they turned to Minitab to demonstrate the effectiveness of process settings with a tool called capability analysis, which demonstrates whether or not a process meets specifications and can produce good parts. They sealed the pouches using the optimal process settings they had identified, keeping in mind that the higher the temperatures, the stronger the seal. They then measured the seal strength of these pouches, and performed a capability analysis to assess the measurements relative to the lower specification limit. Their capability analysis showed that the proposed temperature settings met, and even exceeded, the minimum seal strength requirements.
Results
Fig.3. The team performed process capability analysis in Minitab, which helped them to prove that the proposed temperature settings would allow them to achieve end production goals.
Minitab statistical software can be used to easily create and analyse many kinds of designed experiments. Camacho used it to create a two-level, full factorial designed experiment, which would enable the team to evaluate all of the input
Now that careful data analysis has shown the effectiveness of the sealing system, the facility in Costa Rica can begin using the new plastic pouch. Adopting the new pouch supports Boston Scientific’s broader efforts to streamline packaging across the corporation, and the project played a major role in the company’s combined savings of more than US$770,000 to date. What’s more, the team’s process validation confirms that the changes – and savings – can be sustained. l
For more information ✔ at
www.engineerlive.com/asia
Carly Barry is with Mintab in Pennsylvania, USA.
www.minitab.com
www.engineerlive.com 31
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