AI Articles and Analysis in Heavy industry

Asset and wealth management firms are exploring potential AI solutions for improving their investment decisions, and making use of their troves of historical data. In fact, according to our AI Opportunity Landscape research into the banking industry specifically, approximately 13.5% of the AI vendors in banking offer solutions for wealth and asset management.

Garment and textile manufacturing have historically been labor-intensive industries, as seen in how many of world’s largest fashion, clothing and apparel brands seem to have a significant portion of their products manufactured in Asian countries such as China, India, Bangladesh, Vietnam, etc.

Supply chain management (SCM) is critical in almost every industry today - but it hasn't received as much focus from AI startups and vendor companies compared to healthcare, finance, and retail. Businesses are showing increased interest in AI applications, from its benefits to fully leveraging the vast amounts of data collected by industrial logistics, warehousing and transportation systems.

Over the past decade, the industrial sector has seen major advancements in automation and robotics applications. Automation in both continuous process and discrete manufacturing, as well as the use of robots for repetitive tasks are both relatively standard in most large manufacturing operations (this is especially true in industries like automotive and electronics).

This article is based on a presentation originally given by Daniel Faggella, CEO & Founder at Emerj (formerly TechEmergence) to a group of real estate executives at a Grupo4s "Future of Real Estate" event in San Francisco, in March of 2018.

Episode summary: In the last two or three years we at Emerj have witnessed a definite uptick in AI applications like predictive maintenance and heavy industry. Many exciting business intelligence and sensor data applications are making their way into “stodgy” industries like transportation, oil and gas, and telecom - where machine vision has countless applications.

Relative to banking, finance or healthcare, construction is still a small market for artificial intelligence and emerging applications are focused on finding patterns in large datasets which would either be too difficult for humans to process or would take them too long. Over the course of this article, we aim to answer the following questions:

Episode summary: In the heavy industry sector, the cost of unpredicted repairs or machine failures can be very expensive. For example: A cargo train with an engine failure in will incur costs from its own repairs, from the transit required to reach the broken down engine, and with holding up other trains and cargo in the process.