Latest news: AI in the packaging industry

US Steel is set to use Google Cloud’s generative AI technology with the aim of driving efficiencies and improving employee experiences in the largest iron ore mine in North America. 

The first gen AI-driven application that US Steel will launch is called MineMind which targets equipment maintenance by providing solutions for mechanical problems. 

Underpinned by Google Cloud’s AI technology like Document AI and Vertex AI, MineMind is expected to improve the maintenance team’s experience by providing information more easily and save costs from more efficient use of technicians’ time and better maintained trucks. 

When fully operational, MineMind will reportedly allow a US Steel technician to reduce the amount of time to complete a work order by an estimated 20%. 

The initial phase of the launch will begin in September and will impact more than 60 haul trucks at US Steel’s Minnesota Ore Operations facilities, Minntac and Keetac. 

US Steel president and CEO David Burritt commented: “We’ve meaningfully accelerated digitisation through our work with Google Cloud. Faster repair times and less down time are only some of the many benefits we expect with generative AI.” 

Google Cloud vice president for North America Michael Clark added: “Our work with US Steel on generative AI technology has the potential to not only transform manufacturing but adjacent industries – from trends and logistics, to supply chain, sustainability, process automation, and more.” 

The two companies will seek to continue to expand the relationship to solve high-impact areas across the US Steel value chain. 

The cumulative revenue generation opportunities for generative AI providers such as Google Cloud is estimated to be US$65.04bn between 2022 to 2027. 

A Norwegian study has found potential use for artificial intelligence (AI) in tracing the origins of waste and providing feedback to apparel brands. 

Avfall Norge, a Norwegian organisation representing more than 200 waste management and recycling companies, ran the study in summer 2023 with 71 students as part of its REdu-program. 

The students analysed 3,024 items of textile waste from various municipalities in Norway over two weeks. They were able to identify clothing from 708 different brands using a Targeted Producer Responsibility picking analysis using AI and machine learning (ML). 

The research comes shortly after the UK Fashion and Textiles Association announced a £4m ($5.06m) project to develop and pilot an automated sorting and pre-processing plant for waste textiles. 

For 84.78% of the items analysed using the AI tool, the brand of the garment was easily identifiable. The researchers say this information can help create feedback loops with brands, which they say may help to “nudge producers towards sustainable production”. 

As well as the brand of each item, the analysis also provided information about the composition of its fibres, garment age, the country of production and its potential for reuse. The AI and ML tools made use of product labels, tracking each brands’ labelling system. 

The researchers believe that their AI and ML method can be used to provide more accurate data about the lifecycle of apparel, allowing for fashion brands to be held more accountable for the end-of-life of their products. 

The report says: “We observed fast fashion’s strong influence, with many items being in mint condition, despite being discarded. Alarmingly, some even had their price tags intact.” 

While sorting items, the researchers also found that many items had been discarded despite only having minor damages. The report argues this highlights the need for consumer education on garment care and advice on easy repairs. 

The researchers say the data gathered using their new method and AI can be used to automate the sorting and recycling apparel waste process. The report adds: “Such insights can lay the groundwork for transformative strategies and policies that address waste at its source and curtail fast fashion’s unchecked growth.” 

Last month (July) the EU Commission proposed rules that would make fashion brands and retailers responsible for the full lifecycle of textile products and would require them to financially support the sustainable management of textile waste across the EU.