Illovo Sugar Africa – a discrete manufacturer of sugar, headquartered in South Africa – produces a wide range of products from industrial sugars to prepacked sugar for direct consumption in domestic markets. Form Fill and Seal (FFS) Machines fill consumer stock units, and operational productivity hinges on minimizing the downtime of these machines as well as the risk of recalls from variability in product packaging. Unfortunately, FFS Machines have typically had a high probability of downtime and variability. With very little reliable, repeatable data at Illovo’s fingertips, there was no way to target and improve overall equipment effectiveness (OEE).
Year: 2018
Manufacturing companies are always seeking to improve efficiency, keep their assets operating and reducing energy consumption. These objectives have been around since the beginning of the industrial revolution. Many look to implement modern Smart Manufacturing techniques and sensing technologies, which make use of real-time data.In this webinar you will learn:What is Smart Manufacturing?And haven't we been doing this already?What capabilities are needed to manage the vast amounts of sensor data to enable operational insight, business value and predictive outcomes?How can a manufacturer leverage an ecosystem of advanced analytics solutions to help them solve those tough manufacturing problems?Are there examples and lessons learned that can provide some insight along with a community of practitioners you can learn from? ...
Year: 2018
Watch this webinar to see our latest release of PI Integrator for Business Analytics to learn more about its capabilities and how it enables advanced analytics by serving data to different destinations.
Year: 2018
Résumé et conclusion ...
Year: 2018
Les Big Data, Data Lakes, le Machine Learning et l'intelligence artificielle ouvrent la voie à de nouvelles perspectives et réponses aux rendements. Mais la première réussite n'est parfois due qu'à une amélioration mineure des données dont vous disposez déjà. Découvrez comment vous pouvez diviser des problèmes de Big Data apparemment complexes en une séquence d'étapes gérable grâce au PI System. Même avant la fin d'un modèle statistique complet, vos spécialistes des opérations peuvent généralement relever les modèles d'anomalie avec quelques événements seulement, capturés sous la forme de cadres d'événement PI System et affichés dans un rapport. Lorsque vous êtes prêt à transmettre les données à des outils de Machine Learning (ML) avancés, le PI Integrator peut démarrer votre processus de science des données avec des données propres, prêtes à l'emploi et fiables.
Year: 2018