AI Articles and Analysis in Heavy industry

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.

Episode summary: In this week’s episode of AI in Industry we speak with Rodney Brooks, Founder and CTO of Rethink Robotics, a collaborative robot manufacturer founded in Boston in 2008. Rodney explores robotic safety regulations and he also paints a picture of what robots might be capable of in the next five years.

According to this report from Deloitte, the global 3D printing industry is expected to reach $5.2 billion in 2020 and the largest opportunities for corporations in near future will be in home improvement and the life sciences sectors. Yet, today there are still several hurdles in the additive manufacturing process that need to be overcome for widespread adoption in the industry.

In a white paper about the digitalization of the chemistry and advanced materials sector published by the World Economic Forum and Accenture, total global chemical sales in 2014 amounted to $3.5 trillion and is expected to rise to $6.9 trillion by 2030.