P&G enlists IoT, predictive analytics to perfect Pampers diapers

“These industrial microcontrollers run at super high speed and are very finicky,” Kietermeyer says. “Getting them to run very precisely to manufacture the perfect diaper every time takes a lot of effort and inspection and there’s not a highly expert person available 24 by 7 to watch the line. Even if there were, they would need break time. So that’s where the project idea came from.”

The power of predictive analytics

Here, predictive analytics are key. P&G’s manufacturing specs are continually tested against the incoming data in a rules-based manner via Microsoft’s edge analytics engine, which helps spot necessary corrections several hours in advance. “If the data is trending in a bad way, you can see in six to eight hours if it would fail [in manufacturing],” Kietermeyer says. “We can predict it in time to stop, and do the maintenance before it actually goes outside the spec.”

Proctor & Gamble, which as one of the world’s largest consumer product companies generates more than $75 billion annually, emphasizes how important this use of data collection and predictive analytics has been to the company’s bottom line.

“Business demand for baby care products is extremely high, and the production lines needed to create these products are asset-intensive,” the company reports. “P&G’s ability to keep the lines running has a significant business impact, including supporting our ability to maintain and increase production capacity, reduce unplanned downtime, and reduce the amount of scrap generated during production.”

Hot Melt Optimization comes on the heels of broader commitments P&G has undertaken to its evolve its manufacturing business using digital technologies and AI.

One analyst who follows the use of digital technologies in manufacturing notes that it is critical for vendors to know their processes inside and out to benefit from advanced manufacturing technology.

“Digital transformation uses advanced sensing, data analytics, and the latest in artificial intelligence to gather insight into production processes,” says Carlos Gonzalez, research manager of IoT Ecosystem & Trends at IDC. “The drive of digital commerce is driving organizations to be flexible and produce goods efficiently and quickly. To do so, organizations must deeply understand their industrial processes. IoT platforms and advanced data gathering are necessary to ensure successful and resilient industrial operations.”