CXO INSIGHT
How can these disruptions be addressed ?
Digitalisation and diversification are key aspects of supply chain resiliency . Digitalisation enables opportunities for remote access ( through secure cloud platforms ), the accelerated deployment of Digital Twins , Industrial Internet of Things ( IIoT ) and Augmented Reality ( AR ). All these innovations sit at the heart of AVEVA ’ s business strategy .
Our work during the pandemic with the pharmaceutical industry is representative . As travel was not an option , one of the world ’ s largest producers of vaccines , Pfizer , asked us to help it to secure full oversight of the production processes for all its manufacturing sites . With our market-leading enterprise data solution , AVEVA PI System , the company was able to collect , enrich and analyse production data from 29 global sites to accelerate delivery of life-saving vaccines . With AVEVA PI System , Pfizer scientists from different locations were able to work from a single source of truth to identify issues , look for innovative solutions and maximise outcomes .
Diversification is also important as dependency on a single supplier can be risky , given their exposure to risks such as natural disasters and financial issues . By diversifying suppliers geographically and across industries , businesses can spread the risk across different sources and create a more robust and resilient supply chain . Another way is prioritising risk assessment and planning . By conducting a thorough assessment of risks , businesses can identify potential vulnerabilities and work on contingency plans on how to adapt and respond to disruptions . It is all about building resilience into your supply chain .
How is AI transforming decision-making processes ? this will initially be under human supervision , followed by a move to full autonomous . Of course , this is one of countless examples as AI continues to play a more and more critical role across all industries .
What does the future look like for AVEVA ?
AVEVA is optimally placed to drive innovation and value . We ’ ve brought together market-leading software portfolios , acquired California-based industrial data infrastructure company , OSlsoft , and merged with the global giant , Schneider Electric , which specialises in digital automation and energy management . Our customers can now benefit from precise insights derived from different data sources – from cloud software to hardware and use these insights to make informed decisions , to design and build and optimise their operations .
This collaboration brings added value such as enhanced quality and traceability across supply chains . Arguably , the industrial sector will capitalise on the increased data insights and functionality that cloud-based solutions provide , benefitting from a reduction in energy and carbon intensity , as well as an acceleration in customer journeys of efficiency and sustainability .
Moreover , our engineering solutions provide the foundation of a Digital Twin . Giving owner operators intuitive access at any stage in their assets life cycle to all the engineering data from the design stage in a transparent , automatic , visualised , in-context way through a single platform . For example , AVEVA ’ s Unified Engineering in the cloud helps Aker Carbon Capture create efficient and replicable designs for carbon capture units , and AVEVA ’ s cloud-based software allows teams to collaborate across time zones , resulting in an increase in operational efficiency and time to market by over 50 %.
We anticipate significant disruption across all industries that will continue to evolve over time . Generative AI has been around for decades , but the big recent change is the creation of massive LLMs , such as GPT , PaLM , LLaMa , etc . That ’ s the big difference . But that alone won ’ t change industries in a major way . You also need to be able to blend that ‘ brain ’ ( where it knows nothing beyond the date it was trained ) with up-to-date industrial data through additional AI to make sense of it all in context . This is the game-changer and will add massive value to almost all industries . However , this is NOT ChatGPT . This is the LLM ‘ brain ’ being combined with both industrial data and fit-for-purpose AI ( such as a neural net ) in order to provide game-changing value that can be tailored to the industrial world . This will play a significant role in helping move AI from task-based to objective-driven .
Around 90 % of leading companies in 12 industrial sectors from food and manufacturing to power , energy , infrastructure , marine and EPCs , rely on our solutions to help them deliver life ’ s essentials : safe , reliable energy , food , infrastructure , transportation and more . Our forward-looking goal is to support our customers in their endeavours to become cleaner , more efficient and ultimately more profitable . x
Ultimately , we see this technology driving industry toward improved industrial efficiency and sustainability . For example , AI could be given an objective to minimise a plant ’ s greenhouse gas emissions using any available means that are legal , ethical and safe . AI would take it from there by identifying underperforming assets , prescribing and co-ordinating maintenance and then improving the operational control of the assets . This would optimise fuel utilisation and , thus , minimise carbon and other harmful byproducts that are released into the atmosphere . All of
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