May 16, 2020

Industry 4.0 and the rise of the ‘smart factory’

Smart Manufacturing
Dr Simon Kampa, CEO of Senseye
4 min
smart factory
Smart factories are fast becoming mainstream in manufacturing, offering a new level of efficiency and productivity to those that invest in them. Industr...

Smart factories are fast becoming mainstream in manufacturing, offering a new level of efficiency and productivity to those that invest in them. Industry 4.0, combined with increasingly sophisticated software and analytics, is playing a huge role in driving this movement.

Factories are no longer simply a mass of machinery operating as a series of siloed production lines. Instead, manufacturing executives and engineers manage interconnected networks of moving parts, something more akin to a living organism, that can be trained and fine-tuned to optimise performance.

New technologies such as big data, prognostics, machine learning and the cloud have changed the game when it comes to factory efficiency and maintenance. They are enabling manufacturers to proactively manage and improve the performance of these environments, with relatively low levels of investment.

The opportunities on offer from this new era of responsive, interconnected machinery are enormous. We are seeing higher levels of communication, transparency and yield. Engineers can now precisely predict and manage machine failures at the touch of a button. And through initiatives such as servitisation, the nature of relationships between equipment suppliers and manufacturers are being redefined before our eyes.

The accessibility of predictive maintenance

Our interest in Industry 4.0 is squarely in the area of condition monitoring and predictive maintenance. Although these are by no means new concepts, in the past they have been a reality for the few and a dream for the majority of manufacturers around the world. The cost and sheer complexity of gathering and analysing sufficient data to drive tangible results has limited the use of these proven tools largely to the defence and aerospace sectors.

The introduction of Industry 4.0, where production assets are connected and able to communicate through the Industrial Internet of Things (IIoT), combined with machine learning and advanced analytics from the likes of Senseye, has opened up the world of predictive maintenance to a much broader range of industries and use cases.

Previously, gathering the data required to inform conditioning monitoring activities was a laborious manual process requiring specialist expertise. The growing use of smart sensors and self-aware machines that record their own vital statistics and relay them for analysis over the IIoT, allows this vital data to be pulled from potentially thousands of machines at relatively low cost.

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Much like the gathering of machine data, the filtering and analysis required to translate it into actionable insight has also been an extensive manual endeavour that involved teams of data scientists. We are now seeing the emergence of intelligent machine learning algorithms that automate this activity too.

Smart algorithms crunch through all of the available data, comparing vital readings into machine vibration, pressure, temperature, torque and electrical current against known faults to spot emerging problems and identify if and when a machine will fail in the future.

This prognostic approach allows engineers to undertake precisely the right maintenance activities during periods of planned downtime and fix problems before they can affect production.

The benefits of predictive maintenance

Recent developments in condition monitoring and predictive maintenance, made possible through Industry 4.0, are significantly improving the performance of industrial machinery, and also making the task of operating and maintaining it easier and far more efficient.

Unplanned downtime is one of the biggest costs for any manufacturing environment. In the automotive sector, for instance, every minute that critical machinery carries a cost amounting to tens of thousands of pounds.

Being able to predict if and when a machine will fail in the future allows engineers to make repairs weeks or even months before a predicted failure might affect production. Senseye customers are typically able to halve their levels of machine downtime by using this automated approach, while also saving 40% on their maintenance costs too.

Although we are still in the early days of Industry 4.0, it is clear that enabling machines to gather data and connect with services like Senseye is already driving significant improvements in machine effectiveness and efficiency. The longer-term potential of Industry 4.0 has yet to be realised, but it is clear that its impact will be truly transformative

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May 12, 2021

Ultium Cells LLC/Li-Cycle: Sustainable Battery Manufacturing

2 min
Ultium Cells LLC and Li-Cycle join forces to expand recycling in North America, recycling up to 100% of the scrap materials in battery cell manufacturing

Ultium Cells LLC - a joint venture between General Motors and LG Energy Solutions - has announced its latest collaboration with Li-Cycle. Joining forces the two have set ambitions to expand recycling in North America, recycling up to 100% of the scrap materials in battery cell manufacturing


What is Ultium Cells LLC?

Announcing their partnership in December 2019, General Motors (GM) and LG Energy Solutions established Ultium Cells LLC with a mission to “ensure excellence of Battery Cell Manufacturing through implementation of best practices from each company to contribute [to the] expansion of a Zero Emission propulsion on a global scale.”

Who is Li-Cycle?

Founded in 2016, Li-Cycle leverages innovative solutions to address emerging and urgent challenges around the world.

As the use of Lithium-ion rechargeable batteries in automotive, industrial energy storage, and consumer electronic applications rises, Li-Cycle believes that “the world needs improved technology and supply chain innovations to better recycle these batteries, while also meeting the rapidly growing demand for critical and scarce battery-grade materials.”

Why are Ultium Cells LLC and Li-Cycle join forces?

By joining forces to expand the recycling of scrap materials in battery cell manufacturing in North America, the new recycling process will allow Ultium Cells LLC to recycle cobalt, nickel, lithium, graphite, copper, manganese and aluminum.

“95% of these materials can be used in the production of new batteries or for adjacent industries,” says GM, who explains that the new hydrometallurgical process emits 30% less greenhouse gases (GHGs) than traditional processes, minimising the environmental impact. Use of this process will begin later in the year (2021).

"Our combined efforts with Ultium Cells will be instrumental in redirecting battery manufacturing scrap from landfills and returning a substantial amount of valuable battery-grade materials back into the battery supply chain. This partnership is a critical step forward in advancing our proven lithium-ion resource recovery technology as a more sustainable alternative to mining, " said Ajay Kochhar, President, CEO and co-founder of Li-Cycle.

"GM's zero-waste initiative aims to divert more than 90% of its manufacturing waste from landfills and incineration globally by 2025. Now, we're going to work closely with Ultium Cells and Li-Cycle to help the industry get even better use out of the materials,” added Ken Morris, Vice President of Electric and Autonomous Vehicles, GM.

Since 2013, GM has recycled or reused 100% of the battery packs it has received from customers, with most current GM EVs repaired with refurbished packs.

"We strive to make more with less waste and energy expended. This is a crucial step in improving the sustainability of our components and manufacturing processes,” concluded Thomas Gallagher, Chief Operating Officer, Ultium Cells LLC.

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