February 2020 | Commentary | IT Matters: Logistics & Supply Chain Technology

AI Powers Sustainable Manufacturing

Tags: Manufacturing, Technology , Sustainability

One of the greatest potential benefits of artificial intelligence (AI) is helping the world become more sustainable. This includes addressing the three P's of sustainability—people, planet, and profit—in manufacturing.

Morgan Zimmermann, CEO, Netvibes-Exalead, Dassault Systemes, 855-696-1125

Today's millennial workforce is committed to long-term policies that will provide a more stable environment. Industrial actors that don't align on sustainability goals have, or will have, difficulty finding a future workforce and customers eager to invest in products and services that don't represent their values. Companies are increasingly evaluated less on their profit and loss statements and more on their engagement with the three P's of sustainability.

AI strengthens the following three main "pillars" aligned with the three P's metric to enable companies to meet sustainability targets:

1. Workforce of the future (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 spark innovation and help build a more sustainable future.

AI helps make best practices hidden in documents actionable. Any employee can leverage them to make a greater impact on the enterprise. Thanks to AI, that knowledge can be delivered faster—at unimaginable scale and at the right time—by using augmented/virtual reality, collaborative platforms, and 3D, making training more intuitive. Thus, the workforce can make better-informed decisions. The symbiotic relationship between AI and people makes them both smarter.

2. Global operations optimization (planet). By adopting lean practices throughout the product life cycle, companies can minimize their global environmental footprint. This goes further than solving problems on the shop floor. It's about evaluating and streamlining all operations in a continuous feedback loop.

Eliminating waste is a core concern of manufacturing. Getting rid of anything that doesn't add value in critical areas, like moving a product unnecessarily, requires AI technology that can self-learn from constantly evolving targets (sales, inventories, resources, capacity). AI can anticipate the most beneficial tradeoffs to limit waste.

3. Value network orchestration (profit). Collaborative digital platforms that leverage AI are creating sustainability throughout the value network while enabling the delivery of unique experiences to market. Companies gain visibility into resources and processes and how they're interconnected. Manufacturers can coordinate all stakeholders more efficiently and agilely.

Testing ideas, products, and the experiences they provide in the virtual world before actually producing them in the real world can lead to inventing new usages and the products supporting them.

AI sifts through data at lightning speed, evaluating millions of potential scenarios to find the right information. Firms can capture, standardize, and analyze data to evaluate a business activity's environmental and social impacts and communicate takeaways for informed decision-making.

the Real World: Efficient and balanced

Only virtual worlds provide the right observation and decision-making deck for manufacturing. By speeding access to virtual worlds, AI technology is making the real world more efficient.

AI not only delivers new insights and knowledge; it also allows industry to capture and understand experience and reuse it to contribute to a more balanced and sustainable life.






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