Using industrial data for better sustainability in production facilities.

Using industrial data for better sustainability

Managers working in production facilities face a range of challenges relating to output, quality, and costs on a daily basis. So, sometimes the subject of sustainability may not be top of their agenda. However, talk to them about industrial data and you might get their attention.

Using industrial data for better sustainability

When it comes to industrial data, there are a number of “quick wins” that companies can achieve for better sustainability in production facilities. And in turn these are areas where companies can see immediate benefits in terms of energy efficiency, waste reduction, and other sustainability metrics.  In this article, Robin Buxton, Business Relations Director at Evestico, will explore some of these quick wins in more detail.

Energy Monitoring and Management

One of the most straightforward ways to improve sustainability in production facilities is through energy monitoring and management. By collecting data from energy meters and other sensors, companies can identify areas where energy is being wasted and take corrective action. This could include identifying equipment that is operating inefficiently or implementing energy-saving measures such as LED lighting and HVAC upgrades.

Water Monitoring and Management

Similarly, water monitoring and management can be a quick win for companies looking to improve sustainability. By collecting data on water usage and identifying areas where water is being wasted, companies can take steps to reduce consumption and improve efficiency. This could include implementing low-flow fixtures, monitoring leaks, and identifying equipment that uses water inefficiently.

Waste Reduction

Another area where companies can achieve quick wins is in waste reduction. By collecting data on waste generation and disposal, companies can identify areas where waste can be reduced or eliminated. This could include implementing recycling programs, reducing packaging waste, or optimising production processes to minimise waste generation.

Supply Chain Optimisation

In addition to improving efficiency within their own operations, companies can also achieve sustainability wins by optimising their supply chains. By collecting data on suppliers and transportation methods, companies can identify opportunities to reduce emissions and improve efficiency. For example, this could include sourcing raw materials from local suppliers to reduce transportation emissions or using more sustainable shipping methods.

Asset Management

Effective asset management can also be a quick win for companies looking to improve sustainability. By collecting data on the performance of equipment and machinery, companies can identify areas where maintenance or replacement is needed. This can help reduce energy consumption, prevent equipment breakdowns, and extend the life of assets.

Employee Engagement

Finally, employee engagement can be a critical factor in achieving sustainability wins. By collecting data on employee behaviours and attitudes towards sustainability, companies can identify areas where training and education are needed. This can help build a culture of sustainability within the organisation, where employees are motivated to take actions that reduce energy consumption, minimise waste, and improve efficiency.

In conclusion, there are several “quick wins” that companies can achieve in terms of using industrial data for better sustainability in production facilities. By focusing on areas such as energy and water management, waste reduction, supply chain optimisation, asset management, and employee engagement, companies can make significant progress towards their sustainability goals. The key is to identify areas where data can be collected and analysed to drive meaningful change, and to implement changes quickly to achieve immediate benefits. By doing so, companies can not only reduce their environmental impact but also improve their bottom line and build a more sustainable business model.

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