FEATURE Sustainable Manufacturing
Reducing spares and materials waste for greater sustainability
Alexander Hill, Chief Global Strategist and Co-Founder at Senseye, examines how manufacturers can improve sustainability by reducing spares and materials waste by implementing predictive maintenance technology
E
nergy-intensive industries such as manufacturing have a leading role to play in combating climate change worldwide. The
manufacturing industry is responsible for a high proportion of global greenhouse gas emissions. In the US, it accounts for almost a quarter (23%) of direct carbon emissions, whereas in Europe, industrial processes and industrial energy use account for 21% (880m tonnes) of carbon dioxide emissions. Industry 4.0 and its underpinning technologies can help, by providing manufacturers with more accurate data and insights on their machines and processes, better than ever before.
Waste in manufacturing A substantial cause of waste in manufacturing is processes that drift out of control, not only wasting raw materials, but also reducing the opportunity to produce and sell complete end products. Batch testing, for example, often results in unnecessary waste due to delays in fault identifi cation. If a fault is detected during batch sampling, the whole batch will need to be examined, to determine when production started to shift outside parameters. Any products manufactured after that point are likely to fall outside quality specifi cations and will therefore need to be scrapped. “The drive towards zero-waste manufacturing is being led by high- volume, low-margin processes that are highly optimised. These tend to be continuous operations in plants that have lots of management information to help reduce unnecessary waste,” said Jim Davison, Regional Director at Make UK, an organisation that represents local manufacturers. “Zero waste may ultimately be unachievable, because there will always be faults or issues that cause things to go wrong; but it is certainly possible to minimise waste to the lowest level for the product being manufactured.” Waste is also created by the early
replacement of perfectly-healthy machinery or components. Traditional maintenance practices involve
34 June 2022 | Automation
preventative replacement of parts, to mitigate the risk of failure. This is often justifi ed by the believing that over maintenance is cheaper than failure. However, the consequence is that components are frequently replaced before the end of their useful life.
Replacing components involves shutting down machines, disrupting production, and exposing engineers to potential risks. The discarded component usually ends up being recycled or, worse, in landfi ll, which is a waste not only of materials, but also of the carbon involved in its production, storage and transportation. The carbon footprint of the spares’ supply chain can often be overlooked.
Reducing the need for spares and their more eff ective management plays a substantial part in enabling companies to achieve their sustainability goals.
Predictive maintenance With predictive maintenance, the benefi ts go even further. The ability to capture early-stage faults enables simple repairs or component replacement, thereby avoiding secondary damage that can result in scrapping costly assets. Being able to replace a $50 bearing and avoid the failure of a $50,000 gearbox not only makes good fi nancial sense but eliminates large amounts of waste in saving the gearbox and not needing to expedite a replacement. The majority of the carbon footprint in the management of spares
comes from the supply chain, something that’s compounded when parts need to be put on special delivery.
Data-driven operational and maintenance activities minimise waste, reduce health and safety risks, and extend component life. The more eff ectively manufacturers maintain and operate their machines and facilities, the greater the carbon emission reductions and associated sustainability benefi ts. By way of illustration, the predictive maintenance capabilities enabled by Industry 4.0 and implemented by Senseye clients have demonstrated its ability to deliver:
• 55% increase in maintenance staff productivity; • 50% increase in asset lifespan; • 40% reduction in maintenance costs; • 40% reduction in inventory and waste. There’s also a report we’ve prepared on the challenges of improving sustainability in manufacturing, the opportunities available and the bridge built by Industry 4.0 between machine health and sustainability. In it we explore the ways real-time data supports business outcomes, leveraging AI-powered industrial analytics to drive the following key sustainability areas with direct reductions in a company’s carbon footprint.
CONTACT:
Senseye
www.ssenseye.io
automationmagazine.co.uk
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54
