Category: Manufacturing

In the manufacturing world, valuable insights from service reports often remain underutilized in document storage systems. This post explores how Amazon Web Services (AWS) customers can build a solution that automates the digitisation and extraction of crucial information from many reports using generative AI.

In this post, we share how Apollo Tyres used generative AI with Amazon Bedrock to harness the insights from their machine data in a natural language interaction mode to gain a comprehensive view of its manufacturing processes, enabling data-driven decision-making and optimizing operational efficiency.

This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Blake Santschi, Business Intelligence Manager, from Schneider Electric. Additional Schneider Electric experts include Jesse Miller, Somik Chowdhury, Shaswat Babhulgaonkar, David Watkins, Mark Carlson and Barbara Sleczkowski.  Customer Relationship Management (CRM) systems are used by companies to […]

A successful deployment of a machine learning (ML) model in a production environment heavily relies on an end-to-end ML pipeline. Although developing such a pipeline can be challenging, it becomes even more complex when dealing with an edge ML use case. Machine learning at the edge is a concept that brings the capability of running […]

In Part 1 of this series, we drafted an architecture for an end-to-end MLOps pipeline for a visual quality inspection use case at the edge. It is architected to automate the entire machine learning (ML) process, from data labeling to model training and deployment at the edge. The focus on managed and serverless services reduces […]

This is Part 3 of our series where we design and implement an MLOps pipeline for visual quality inspection at the edge. In this post, we focus on how to automate the edge deployment part of the end-to-end MLOps pipeline. We show you how to use AWS IoT Greengrass to manage model inference at the […]

Companies use time series forecasting to make core planning decisions that help them navigate through uncertain futures. This post is meant to address supply chain stakeholders, who share a common need of determining how many finished goods are needed over a mixed variety of planning time horizons. In addition to planning how many units of […]

This is a guest post co-written with Moulham Zahabi from Matarat. Probably everyone has checked their baggage when flying, and waited anxiously for their bags to appear at the carousel. Successful and timely delivery of your bags depends on a massive infrastructure called the baggage handling system (BHS). This infrastructure is one of the key […]

Predictive maintenance is a data-driven maintenance strategy for monitoring industrial assets in order to detect anomalies in equipment operations and health that could lead to equipment failures. Through proactive monitoring of an asset’s condition, maintenance personnel can be alerted before issues occur, thereby avoiding costly unplanned downtime, which in turn leads to an increase in […]

In 2019, Amazon co-founded the climate pledge. The pledge’s goal is to achieve net zero carbon by 2040. This is 10 years earlier than the Paris agreement outlines. Companies who sign up are committed to regular reporting, carbon elimination, and credible offsets. At the time of this writing, 377 companies have signed the climate pledge, […]