Industrial products and projects are rarely contained to one machine. Economic development has continued to push the division of labor to maximize efficiency, while effects of globalization have geographically spread the production processes of goods and services. Production lines have expanded into production webs, with a vast array of variables that can influence the procedure and the final product.
These intricacies have complicated the analysis of product life cycles, causing issue with the urgent need for greener practices. Making truly sustainable choices requires divulging the often hidden carbon footprint behind goods and services, taking into account the waste produced by every contributing factor. This attention to detail has led the level of scrutiny to become much higher. When sourcing, production, packaging and shipping can all happen in different locations, we have a serious problem in understanding the sustainability of a product.
Some companies are offering some solutions, such as one for online retail, where you have the option to offset the footprint of your purchase by adding a small fee at the end. Your money then goes towards organizations that work to reverse the effects of your purchase. But calculating such a figure is, unsurprisingly, a difficult endeavor. It requires analysis of huge amounts of data from disconnected sources, and finding greener alternatives would require applying this same analysis to the multitude of other possibilities.
With the general sentiment on rampant consumption changing, there lies an excellent opportunity for the recovery out of the current recession to be more sustainable. It would be a smarter recovery, where ultimately greater control over our methods of production could cull any unnecessary energy usage.
To complete this task, we need sophisticated infrastructure that can connect and analyze the data, culminating in simulations that represent entire processes of products. Digital Twin has capitalized on this by offering new technologies that can simulate all the intricacies of these complex workflows and offer a greater level of control.
What is Digital Twin?
The benefits of digitally modeling physical entities are well known. Computer Aided Design (CAD), for example, changed the creative process of architecture and engineering permanently when it first emerged. It allowed preliminary tests and checks to be carried out at a much lower cost than actually prototyping the products. The latest iterations can even integrate virtual and augmented reality technologies, allowing designers to immersively experience their creations. In one sense, Digital Twin has been around for a while as it is essentially a blanket term for a digital representation of a physical object or process. In their latest iterations however, they can provide insights into the modern realities of production and processes.
In order to give a better understanding of this, consider first, digital twin being split into two key but still interconnected branches: informing and actioning. For informing, we see the importance of IoT devices in their role in data capture that has accelerated our ability to analyse our industrial processes. This data is then collated and displayed through dashboards interfaces that ultimately provide a platform for simulations that can be run to investigate inefficiencies or other potential outcomes of this data. This acts as a bridge to the actioning side, in conjunction with AI and machine learning that prescribe adjustments to contribute to the digital representations. With these often being spatial, AR and VR technologies can help better visualise them to best plan the changes that occur. These changes are then enabled by relaying the decisions to the physical counterparts, where robotics and machine to machine integration has allowed us to manage our physical capital with new levels of control.
As you can see, creating digital twins means orchestrating this symphony of different technologies and data. It is a mammoth computational and logistical task, but its ramifications allows us to navigate the complexities of our modern workloads.
How Digital Twin can provide greener insight
One of the key opportunities lies in the optimisation of processes for managing waste and energy consumption. Consider an example in manufacturing, where the varying sources of materials could now be determined based on the carbon footprint produced in acquiring them. Choosing more local would for example, reduce the carbon produced in transportation. Similarly, it could give the freedom to choose alternatives that contain less harmful substances. Plastic pollutants, for example, have been a key focus in this area, but gaining an understanding of specifically where the waste occurs is difficult when there is such widespread usage. Digitalisation is helping combat problems like these in a number of ways. For example, BASF, the largest chemical producer in the world, is using digital tracer technology in its reciChain programme that is aiming to increase plastic circularity by analysing the movement of plastics used in its production.
Furthermore, digital twins of the processes themselves would allow for tweaking of variables using real time data. Edge technologies and the Internet of Things being integrated into large simulations has accelerated this, as local processing is overcoming latency issues that have held back real-time adjustments. This could mean reducing the energy usage during down times, or adjusting power output in order strike a greater balance between costs and production. It can also help avoid disasters, such as a high level of pressure causing an explosion that could do anything from ruining a batch to destroying machines. Mitigating risk in this way also has its green benefits, where less wasted batches of a product helps conserve energy and avoiding any disasters can reduce potential fallout damage to the environment.
Digital twins of cities in the form of smart cities have already seen a great level of traction, particularly regarding environmental welfare. Monitoring pollution in areas using sensors, measuring traffic levels and tracking energy usage in buildings are all methods that have been taken to inform planning and procedure. In a number of cities across the world, they have improved the environment for people living there.
Essentially, more control and connected knowledge is at the very heart of Digital Twin and it just so happens this is also what is needed to make more sustainable choices. Ultimately, this will be accelerated by serverless platforms that can simulate these processes at massive scale.
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Craig Beddis, Chief Executive Officer and Co-Founder, Hadean