Mars is collaborating with Accenture to digitize its operations using artificial intelligence (AI), cloud, edge technology and digital twins. 

The companies have been working in partnership since 2020, trialing digital twin solutions for Mars’ manufacturing operations. The tech will allow Mars to simulate and test planned changes before committing resources to them. 

The project seeks to target the company’s overall emissions, as well as water use and cost of operations, with digital twin tech hoped to enable predictive maintenance and pre-empt other potential problems to minimize cost (and resource) waste. 

“The problems we’re solving aren’t new,” said Simon Osborne, a managing director at Accenture. “What’s new is how we use advanced technologies to get real-time data into operators’ hands and apply AI to help them make decisions before problems occur.”

“While many companies are beginning to experiment with digital twins, what sets this project apart is the speed and scaling of the technology across Mars’ operations globally,” he added.

Under the new partnership, a cloud platform for manufacturing application, data and AI is set to be established over the next two years, used as a foundation for Mars’ “Factory of the Future.” Using robotics, AI and automation, the platform will be designed to streamline operations to address sustainability goals such as reducing waste and greenhouse gas emissions. 

“Our collaboration with Accenture … enables us to scale digital twin technology to reach this goal,” said William Beery, vice president at Mars. “Delivering not just significant cost savings and sustainability, but preparing our manufacturing operations for the future of work.” 

With businesses facing rising labor costs and production capacity still reeling from the impacts of the pandemic, harnessing digital tools is a popular solution to help drive down costs and ensure operations are safe, efficient and sustainable.

One example of the use of this technology is the companies’ successful trial harnessing digital twins to tackle overfilled packages – a common industry problem. In the trial, sensor data from manufacturing machinery was put into a predictive analytics model, allowing operators to monitor packages in real time and adjust processes to avoid this issue.