How Industry 4.0 and smart maintenance can save the world’s largest metals and mining organizations up to $25 billion a year

A new report shows that the world’s largest metals and mining firms are moving beyond trials and introducing Industry 4.0 technologies such as smart predictive maintenance and AI at scale

 Southampton, UK, 17th May 2022: A new report from Senseye, the machine health management company, reveals that at least a third of the world's largest metals and mining companies are now introducing smart predictive maintenance capabilities and AI-decisioning systems across their businesses.

Senseye’s research indicates that 16 of the world’s 50 largest metals and mining companies, and six of the top 10, have started deploying Industry 4.0-enabled predictive maintenance technologies to multiple production environments to support more efficient and sustainable operations.

An even greater number of organizations are rolling out AI-driven decision systems. Almost half (23) of the top 50 companies are now introducing AI to support decision-making in multiple business areas. All but ten of the world’s 50 largest metals and mining companies have tested AI decision capabilities or smart predictive maintenance technologies in at least one business area.

Senseye found that the top 50 metals and mining firms spent $62.5 billion on plant and equipment maintenance last year, with these costs typically representing up to three percent of revenues. Senseye's analysis indicates an opportunity for these companies to save up to $25 billion a year through maintenance efficiencies enabled by Industry 4.0.

 Screenshot 2022-05-16 at 14.55.42

Alexander Hill, Chief Global Strategist at Senseye, comments: “There's been a seismic shift in the digital landscape at the world's largest metals and mining companies. AI and predictive maintenance are now mainstream, with those that collect asset data now using it to drive more effective and efficient operations at scale. The savings that Industry 4.0 offers metals and mining companies are eye-watering.”

Brad Owen, Senior Asset Health Management Specialist at Cameco, comments: “Machine maintenance represents up to 30 percent of our operating cost. Smart predictive maintenance approaches enabled by Industry 4.0 provide the foresight to deal with issues more effectively and a big opportunity to improve efficiency.”

Gísli Gylfason, Leading Reliability Engineer at Alcoa, comments: "Improving the maintenance management process is helping us to avoid downtime and delivering efficiencies across the business. Automated solutions help us track growing volumes of data and focus our attention with increasing accuracy."

To download a copy of Senseye’s Connecting Asset Data at Scale report, please click on the image below. 

 Blog 1

ENDS

For more information please contact:

Niall Sullivan, VP Marketing, Senseye – niall.sullivan@senseye.io 

About Senseye™

Senseye, headquartered in the UK with regional offices in Germany, France, USA, and Japan is the leading global industrial software company for Machine Health Management. Senseye helps global Fortune 500 organizations to save millions of dollars in unplanned downtime and maintenance efficiencies every week in key industries such as Automotive, Manufacturing, Heavy Industry and FMCG. www.senseye.io