Ensuring optimal quality of products during transportation and delivery
Depending upon the types of goods they produce, manufacturers have to ensure that they arrive in good condition. According to the Food and Agricultural Organizations of the United Nations, approximately 40% of food is lost on average in post-harvest and processing stages, in developing countries. This obviously impacts the food manufacturing, processing and transportation companies. Moreover, most industrial manufacturers are sensitive to increases in any transportation cost.
Quality management of products through the transit is crucial. Manufacturers can predict the quality of their products under given transit conditions, hence giving them the opportunity to improve refrigeration (for perishable products) or optimize routes (for raw materials and finished goods). AI based transportation optimization leverages route information, weather data, fuel cost and other such factors to arrive at the best possible route as well as to predict the quality of goods at the destination.
The mission at H2O.ai is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. Leading industrial brands like Stanley Black and Decker have partnered with H2O.ai to deliver the next generation of industrial manufacturing solutions powered by H2O Driverless AI. H2O Driverless AI is an award-winning platform for automatic machine learning that empowers data science teams to scale machine learning efforts by dramatically increasing the speed to develop highly accurate predictive models. Driverless AI includes innovative features of particular interest to manufacturers including machine learning interpretability (MLI), custom recipes, reason codes for individual predictions, and automatic time series modeling.
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I am very excited to use the H2O Driverless AI because prior to it, we used to spend weeks hyperparameter tuning etc., but with Driverless AI, one experiment takes just a few hours.”
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