Manufacturers should not only strive for better sustainability for the future of the planet, but for the future of their facilities too. 

The PricewaterhouseCoopers (PwC) 2021 Global Investor Survey revealed that reducing scope one and two emissions — direct emissions from owned or controlled sources and indirect emissions from purchased electricity generation — is the top priority for 65% of investors. But how can leveraging the industrial edge make it happen?

Edge-enabled efficiency in manufacturing

Edge analytics allows businesses to process data close to its source. After collecting data from various machines on the factory floor, manufacturers can employ edge analytics tools to process it. They can adopt smart filtering to remove any irrelevant, invalid or ‘dirty’ data and only send relevant data to other systems or storage.

Once machine data has been obtained, filtered and standardised, manufacturers are left with deep insights into their machines’ performance, making it easier to identify key contributors to emissions or a particular resource drain. Industry accounts for 39% of the world’s final energy use according to the IEA. But making small improvements to each individual machine’s performance can result in incremental energy savings that build to a big impact.

Manufacturers can streamline machine to machine (M2M) communication by using the data from one machine to gain an actionable insight into its performance and generate an output that determines the configuration of the next machine.

Identifying energy inefficiencies in real time presents manufacturers with an opportunity to act fast. For example, edge analytics can be used to monitor the speed at which a machine is running or the quantity of a material it dispenses. In response to the data collected, each machine’s configuration can be modified immediately according to a predetermined algorithm for streamlined operations. By optimising several individual machine processes that are significant energy consumers to make them more efficient, edge analytics controls - and reduces - a facility’s overall energy consumption.

Cutting down on defects will enhance a manufacturers sustainability goals 

Industrial waste is another huge element of manufacturing’s sustainability problem. The World Bank has estimated that globally, industrial waste generation is almost 18 times more than municipal solid waste - and the two greatest contributors to industrial waste generation? Overproduction and defective output.

If a machine begins to malfunction, its output will be affected, meaning all of the defective parts it produces will ultimately end up as industrial waste. By analysing machine data immediately and continuously, manufacturers can identify performance anomalies before they become a problem. Once an anomaly has been identified, it can trigger a warning to inform machine operators that direct action must be taken. Production can be temporarily paused, the machine repaired, and output remains as intended.

The Crosser Flow Studio is an edge analytics platform that provides manufacturers with actionable insights into their machines for less emissions, energy use and waste. Designed to fight complexity with simplicity, Crosser’s solution unlocks the value of edge analytics for every manufacturer, no matter its size or digital abilities. Thanks to its low code nature, end users with no coding knowledge can design, deploy and manage data flows with ease.

If manufacturing is to reach net zero and align its activities with international climate goals, it must act now. Forrester has predicted sustainability-related services powered by edge will grow in 2022, but with Crosser’s platform, they are already here. With the urgency of the crisis clear, there’s no time to waste in adopting ESG goals. Embracing the edge is crucial to making it happen.