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* By Alejandro Chocolat
Artificial Intelligence (AI) is not a trick or trick. It is not just used to generate new music playlists or chatbots that, ultimately, cannot answer your questions at customer service. In according to PwC, the global economy could receive a potential contribution of US$ 15.7 trillion thanks to Artificial Intelligence by 2030.
Today, this technology is helping the world to become more sustainable and helping companies of all sizes to stay ahead of the competition. This includes addressing the three sustainability “P” s: People, Planet and Profit (profit).
The three “P” s about P&L (Profit & Loss)
With climate change in mind, the new generation is motivated to commit to long-term policies that will provide a more stable environment and a more balanced and enjoyable life. Industrial actors who are not aligned with these sustainability goals have or will have difficulties finding a future workforce and customers eager to invest in products and services that do not represent their values. Companies are being increasingly evaluated for their involvement with the three sustainability P's inseparable and less for their financial results.
The model of the three "P" s is beginning to have a massive influence in the industrial world. The United Nations is defending its 17 Sustainable Development Goals, while companies of all sizes and in all domains, not only with small niches, are adopting long-term policies. Large multinationals, such as global investment manager BlackRo ck, Inc., based in the USA, are offering sustainable investment solutions. Consumer goods market leaders such as Adidas, Danone, Gucci and L´Oréal recognize that strong sustainability initiatives are good business.
AI will get us there more quickly. Global initiatives like “AI for Good Global Summit”Of the United Nations and the”Google.org Impact Challengand ”, Google’s annual event, with US$ 25 million investment funds for AI, are helping to fuel that role. On the manufacturing side, AI strengthens the three main "pillars" in line with the metrics of the three "P" s to enable companies to meet sustainability goals: workforce of the future, global optimization of operations and network orchestration of value.
Future workforce (People)
Creating the workforce of the future involves capturing and transferring knowledge and know-how from today's employees and empowering people with technology to create experiences that encourage innovation and can help build a more sustainable future.
Digital technology makes it easier to share information faster around the world. Companies must adopt this change in skills to adapt to new technologies and, thus, increase the autonomy of their workforce. This can be achieved through multidisciplinary approaches to lifelong learning and training, combining the classroom and the laboratory.
Artificial Intelligence helps make best practices hidden in documents accessible. Any employee can take advantage of them to have a greater impact on the company. Thanks to AI, this knowledge can be delivered more quickly, on an unimaginable scale and at the right time, through the use of augmented / virtual reality, collaborative and 3D platforms, making training more intuitive. So, the workforce can make decisions by being better informed. The symbiotic relationship between AI and people makes them both smarter.
Global Operations Optimization (Planet)
By adopting lean practices throughout the product's life cycle, companies can minimize their global environmental footprint. This goes far beyond troubleshooting on the shop floor. It is about evaluating and optimizing all operations, from product design to manufacturing engineering, optimization of the supply chain and production in a continuous feedback cycle.
Eliminating waste is the central concern of manufacturing. Getting rid of anything that does not add value in critical areas, such as moving a product unnecessarily, excess inventory, errors or scrap, requires AI technology that can self-learn with constantly evolving goals (sales, inventory, resources, capacity, etc.). ). Artificial Intelligence can also anticipate the most beneficial trade-offs to limit waste.
Another example of proof of value is in reducing energy consumption. There is a lot of enthusiasm surrounding the deployment of smart grids that connect producers and consumers, maximizing storage and energy supply at the right time. Artificial Intelligence predicts peak consumption and helps in real-time optimization of operations settings.
Value Network Orchestration (Profit)
Current supply chains are being replaced by global value chains - industrial partners joining forces to redefine their contribution to achieving common delivery goals. Collaborative digital platforms that leverage Artificial Intelligence are creating sustainability across the value network, while allowing the delivery of unique experiences to the market. Companies gain visibility into resources and processes and how they are interconnected. Manufacturers can coordinate all stakeholders more efficiently and quickly. Testing ideas, products and experiences that they provide in the virtual world before actually producing them in the real world can lead to the invention of new uses and products that support them.
Artificial Intelligence selects data at the speed of light, evaluating millions of potential scenarios to find the right information. Companies can capture, standardize and analyze information to assess the environmental and social impacts of a business activity and communicate these results for information-based decision making. People can propose and test the best scenarios, simulating results through a Virtual Twin experience to identify the right opportunities and apply what they learn where it makes sense. They can reduce waste and increase efficiency - from product design to packaging, supply of raw materials to disposal and recovery of materials. For example, two companies could share resources, such as spare parts, logistics or even inventory. Artificial Intelligence helps them to optimize the ability to become a self-adaptive and more productive production line.
Making the real world efficient
Artificial Intelligence is a catalyst for change. The most challenging problem is deciding how to observe and live in the world; what is the framework to be used to connect and contextualize exponential amounts of data? Only virtual worlds provide the right platform for observation and decision making for manufacturing. By accelerating access to virtual worlds, Artificial Intelligence technology is making the real world more efficient. It not only provides new insights and insights; it allows the industry to capture and understand the experience and reuse it to contribute to a more balanced and enjoyable life.
* Alejandro Chocolat, Managing Director of Dassault Systèmes for Brazil and Latin America
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
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