With the intelligent application of smart technology, manufacturers can take the steps needed to minimize impact and promote energy efficiency.
Manufacturing is essential for the world we live in, but it is also a major contributor to global emissions – about 24.2% of all GHG (Greenhouse Gas) emissions are from electricity use in manufacturing alone. That’s more than from any other single sector, including transport and agriculture. All this means that manufacturers have a particular responsibility when it comes to minimizing and optimizing their energy use. And as consumers become more and more environmentally aware, and sustainability-conscious, there is a growing commercial imperative for manufacturers to make sure their operations are as green as can be.
Fortunately, they now have greater opportunities to do this than ever before, aided by the exponential rise in digital solutions. Manufacturers can increasingly leverage IoT and data analytics technology to gain an unprecedented, deep, and granular understanding of their energy use patterns – allowing them to optimize their operations.
Furthermore, as the gradual rollout of ultra-fast 5G networks continues, declining latency times will pave the way for ever more sophisticated technologies that can monitor and improve the speed-and-precision oriented environments of factory floors.
Virtual twins and simulation processes can let you understand energy use and model alternative configurations in a safe and cost-effective away.
5G-enabled machine sensors can monitor for and predictive upcoming malfunctions, allowing for repairs to be carried out in a timely manner.
Using 3DEXPERIENCE solutions factory operators can get a comprehensive view of the organization, and effectively co-ordinate energy saving measures
A core challenge for factory operators and manufacturers when it comes to energy conservation is trying to ensure that machines run at maximum efficiency all the time.
For example, when changing the color of a production run, it can take time for inks and paints to be switched over. While this is being done, machinery can remain idle, wasting electricity.
Or take the surface mount technology (SMT) line. Many consumer electronics companies rely on SMT production lines, where components are mounted directly onto circuit boards. However, different assembly processes can take different amounts of time. When considered in the wider context of the production line, these processes inevitably create bottlenecks. The problem with bottlenecks is that they mean that other machines must remain on, but idle. Gathering more data on this activity allows manufacturers to identify which machines are acting as bottlenecks.
Once identified, manufacturers can then make informed decisions and take actions to address idle equipment throughout their production lines. They could reschedule working patterns or reconfigure supply line layouts to reduce friction around product flow.
IoT and data solutions can also help track materials as well as machinery. For example, chip components oxidize in open air, meaning electronics manufacturers have a set time limit to assemble more complex parts before the materials degrade and become unusable.
IoT can help here. Barcodes or RFID tags attached to sensitive materials allow manufacturers to track these components throughout the lifecycle, and keep them within workable margins, lessening waste and the need for rework.
Another area where data and IoT solutions are helping manufacturers improve their energy use footprint is via improved approaches to maintenance. In particular, predictive maintenance works by using IoT sensors to detect irregularities in machine performance that may be markers of a future malfunction.
For example, a sensor fitted inside of an industrial turbine could monitor vibrations produced as the turbine operates. By cross referencing this against historical data, operators can learn to identify particular patterns of vibrations that may signal an imminent breakdown.
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This data then allows operators to take preventative steps to ensure machines are repaired in good time, allowing plants to spend more time working at maximum efficiency. The savings can be dramatic – predictive maintenance on HVAC units can result in energy savings of up to 40%.
Manufacturers frequently rely on downtime to audit and service machines. Therefore, having information on any potential issues with operational machinery also allows manufacturers to schedule blackouts and downtimes accordingly.
Dassault Systèmes’ cloud-based 3DEXPERIENCE® platform can allow factory operators to take all the data produced and turn it into actionable insights. Manufacturers can create testable virtual models based on the data, better understand their energy use landscape, and make informed decisions about what steps they need to take to realize more sustainable, energy-efficient operations.
For example, when it comes to actually building operating processes based on IoT data, 3DEXPERIENCE’s virtual twin and simulation services can help manufacturers model alternative operating processes in a cost-effective, low-risk way
Another way in which the cloud-based platform can complement data-led efficiency drives is through facilitating cross collaboration between teams. Manufacturing operations invariably involve multiple siloed teams. These teams, while not in conversation with each other, may all have insights around how production operations can be optimized, and energy efficiency can be maximized.
Dassault Systèmes’ 3DLEAN platform helps break down these silo walls, giving teams a structured collaborative environment to pool together diverse insights, and develop solutions that can have impacts on a scale that goes beyond any individual function and deliver long term sustainability outcomes across the organization.
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