Transform your engineering firm with these 5 emerging technologies
There’s a skills crisis looming that is not a product of poor training, but rather a symptom of the relentless march of technological innovation.
Half of the business leaders who responded to the 2019 PWC Fourth Industrial Revolution survey expressed a concern about future job losses – with 55 percent of respondents saying that the biggest impact of this skills shortage on business is the “inability to innovate effectively.”
The impact of technological advancement is shortening the shelf-life of existing employee skills. While this reality can be disturbing, the emerging technologies driving these skills shortage are exciting and demand that engineering firms adopt a new mindset to embrace these changes.
These technologies also have the power to transform the current workplace into the digital offices of tomorrow that encourage levels of collaboration that we have never experienced before. This approach can also unlock new workstyles that can solve the biggest problems we face today.
These five emerging technologies are particularly beneficial in the engineering space:
- Digital twins
Virtual models can be used to adapt or construct buildings and even whole urban infrastructures and cities to arrive at unique solutions. Digital twins are an important tool to reshape our urban spaces to drive down carbon emissions, while boosting economic efficiency.
Ernst and Young also reported digital twins can reduce carbon emissions in urban areas by between 50 to 100 percent, reduce operating costs for building asset owners by 35 percent and boost productivity by 20 percent.
Six steps to create a digital twin:
- Equip your project/asset with IoT sensors to measure inputs and outputs
- Connect the IoT sensors to a digital platform
- Organise the collected data and prepare data sets for analysis
- Visualise the data with iterative models
- Transfer to a 3D model or overview dashboard to inform decision making
- Implement this data-guided decision in the physical world
- Edge computing
Processing data close to the source and only sending the results to the cloud cuts down on storage costs and speeds up processes. Centralised cloud computing has yielded amazing products, including unlimited data storage and connected apps, but the security risks and a reliance on data connectivity has limited its use in high-security environments.
Edge computing provides shorter response times, lower bandwidth costs, and more robust data safety and privacy protection than cloud computing.
What is edge computing? It moves compute power to the edge of where your local network meets the internet. This infrastructure is more robust and reliable and keeps data costs low by only utilising the connection when offloading the processed data to external storage.
Networking speed is also improved through local and peer-to-peer communication, which is a central component of the Internet of Things. In the future all the machine-to-machine communication that underpins autonomous driving will demonstrate the full potential of edge computing.
Cryptographic distributed ledgers create a digital log with a permanent record and can track assets. With blockchain contracts are embedded in digital code and stored in transparent, shared databases, where they are protected from deletion, tampering, and revision.
With an internal blockchain every agreement, every process, every task, and every payment would have a digital record and signature that could be identified, validated, stored, and shared. Individuals, organisations, machines, and algorithms can freely transact and interact with one another with little friction.
Three important advantages of an internal blockchain:
- Confidentiality can be incorporated in a private blockchain by encrypting the data on a chain.
- Multichain tokenisation allows you to anchor the value of a transaction and you can link multiple chains
- Private blockchain can provide authenticated and notarised messaging services.
- Artificial Intelligence
AI can process large data sets in a short time and, through machine learning techniques, automate certain processes. The complementary nature of on-device machine learning and edge computing means that future IoT systems can operate semi-autonomously within defined parameters, freeing up human capital and compute power for other tasks.
Applying AI to design can also speed up that phase of the work without resorting to copying and pasting templates. AI can dynamically place standard objects/features and suggest alterations in response to data from a digital twin.
- Augmented Reality
The ability to overlay additional data or information on top of the real world will help visualise data in new and innovative ways. Technically digital twins can be described as augmented reality because the models you can design are tied to a real-world object.
The metaverse may be the hot topic now but, outside of communications and entertainment applications, the concept of VR in the engineering workspace is not ideal. AR on the other hand combines all the strengths of VR, but doesn’t require you to depart from the meat space.
Ensure your firm is equipped to support innovation projects
While your firm is enhancing its solutions and gearing towards future-focused engineering solutions, it needs in-house software, including for project management, that supports this kind of innovation and forward thinking.
This workbook contains questions and prompts to help you brainstorm how you can use emerging tech to transform your processes.
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