At P&G we are obsessed with understanding, exploring, and fixing the problems consumers face in their daily lives. Connecting business strategy with technology opportunities across all dimensions of our business – digitizing the business – is one way we are doing this.
A great example of this is the new multi-year co-innovation agreement that P&G and Microsoft recently entered into. The collaboration will leverage the Microsoft Cloud, expand P&G’s digital manufacturing platform and leverage the Industrial Internet of Things (IIoT) to bring products to consumers faster, increase customer satisfaction, and improve productivity to reduce costs.
Under the new collaboration, P&G will use Microsoft’s Azure suite to digitize and integrate data from more than 100 manufacturing sites around the world and enhance its AI, machine learning, and Edge computing services for real-time visibility.
“Through our work with Microsoft, we intend to make manufacturing smarter by enabling scalable predictive quality, predictive maintenance, controlled release, touchless operations, and manufacturing sustainability optimization – something that has not been done at this scale in the manufacturing space to date,” said P&G CIO Vittorio Cretella.
Using the new IIoT platform, P&G will be able to collect data from sensors on the manufacturing line and use technologies like advanced algorithms, machine learning, and predictive analytics so we can improve manufacturing efficiencies.
P&G is already innovating and using Azure IoT Hub and IoT Edge to help our employees analyze insights with greater speed and efficiency. Pilot projects are already underway in baby care and paper products in Egypt, India, Japan, and the United States.
For example, in baby care, we’re improving the manufacturing process of Pampers. The production of diapers involves assembling many layers of material at high speed, with great precision, to ensure optimal absorbency, superior leak protection, and outstanding comfort. The new IIoT platform uses machine telemetry and high-speed analytics to continuously monitor production lines to provide early detection and prevention of potential issues in the material flow. This improves cycle time, reduces rework losses, and ensures quality, while simultaneously improving operator productivity.
These projects will help us improve our manufacturing process, reduce manufacturing downtime, minimize scrap, and lower maintenance expenses by automatically detecting and resolving the largest causes of line stops and rework using machine learning.
We’re leveraging data on a scale that has never been done before, and creating capabilities that haven’t previously existed, to enhance the predictive quality of manufacturing equipment and manage supply chain efficiency. These advancements constructively disrupt the norms of manufacturing to transform how we operate and to help us deliver the highest quality, with the greatest consistency, for our consumers.