Wed. Dec 1st, 2021


Covid-19 Has illuminated the spotlight on many networks around the world Internet International air travel. But the supply chains that cross the world — the ships and trucks and trains that connect factories to ports and warehouses that bring us almost everything from where it is produced to where it is used thousands of miles away অনেক are much more than ever. 6 are facing more investigations

“It’s fair to say that no matter what you’re selling, you’ve got a problem right now,” said Jason Boyce, founder and CEO of Avenue7Media, a consulting firm that advises on top Amazon sellers. Boyce says he has clients who would earn millions of dollars a year if they could stay in stock. “We talk to clients every day where they are just crying,” he says. “For months, they haven’t been fully in stock for 30 consecutive days.”

Digital twins try to resolve breakdowns in the supply chain by predicting before they happen and then using AI to figure out a solution. The name captures the basic idea of ​​simulating a complex system on a computer, creating a kind of twin that reflects real-world objects থেকে from ports to goods — and is a part of the processes that make them. Simulations have been a part of decision making in the industry for years, helping people explore different product designs or stream warehouse layouts. But the availability of large amounts of real-time data and computing power means that more complex processes can be simulated for the first time, including the chaos of global supply chains that often rely on numerous vendors and transportation networks.

Such technology has given Amazon, which already has the advantage of controlling its own trucks and warehouses, an added edge over the years. Now others are taking it too. Google is creating supply-chain digital twins that carmaker Renault has announced it will start using in September. International shipping giants such as FedEx and DHL are developing their own simulation software. And AI companies like Pathmind are creating the right tools for anyone to pay for them. Yet not everyone will benefit. Indeed, powerful new technologies could widen the growing digital divide in the world economy.

Stormy weather

It is easy to blame the epidemic for the current supply-chain problems. Factory closed and Labor shortage At the same time the production and delivery hub has been rocked by a leap in online shopping and comfort shopping has rocketed the demand for home delivery.

But in truth, the epidemic has only made a worse situation worse. D’Maris Kaufman, an economist at University College London, said: “Here the global powers are driving it, all in all a perfect storm.”

Overcoming these storms requires sinking trillions of dollars into global infrastructure, expanding ports and delivery fleets, and investing in better management, better working environments, and better trade agreements. “Technology is not going to solve this problem. It will not allow ships to carry more containers, ”said David Simchi-Levy, who heads the data science lab at the Massachusetts Institute of Technology and has helped build digital twins for several large companies. But AI can help companies in its worst weather. “Digital twins let us identify problems before they happen,” he says.

According to Hans Thalbauer, managing director of Google’s supply chain and logistics team, the biggest problem for businesses is not being able to predict events up to the chain. “It doesn’t matter which company you’re talking to,” he said. “Everyone in the supply-chain world will tell you they don’t have the visibility to make a decision.”

It’s supply-chain visibility that allows Amazon, for example, to predict when an item will appear on your doorstep. For every item that Amazon itself delivers এবং and that includes millions of items delivered by third-party vendors like Boyce and its clients দেয় it gives an accurate estimate of when it will arrive. It may not seem like much, Boyce says, but if Amazon makes these predictions wrong, it will start to lose customers বিশেষ especially during the holiday season, when people are buying last-minute gifts and trusting Amazon to deliver them. “It takes huge computing power to show that simple short delivery day,” he says. “But people are afraid of hell when they don’t get their things on time.”

According to Deliver, a U.S. company that handles delivery logistics for multiple e-commerce firms, including Amazon, Walmart, eBay and Shopify, estimates delivery times increase sales by seven to 10 days by 40%; The one-day estimated delivery time increases sales by 70%.

No wonder others want a crystal ball of their own. At the right time the supply chain is almost dead. The disruptions of the past two years have sunk many businesses that have been driven by hyper-efficiency. Warehouse space is expensive, and paying for inventory storage that you may not need for a week may seem unreasonable at times. But when next week’s stock doesn’t show up, you have nothing to sell.

“Before the epidemic, most companies focused on reducing costs,” said Simchi-Levy. Now they are willing to pay for resilience, but focusing on resilience alone is also a mistake: you need to find the right balance between the two. This is the real power of simulation. “We see a growing number of companies starting to stress-test their supply chains using digital twins,” he says.

What if?

By exploring different potential situations, companies can find a balance between efficiency and resilience that works best for them. Add Deep Reinforcement Learning, which allows an AI to learn what to do in different situations through trial and error, and digital twins become machines for exploring key-if questions. What if there is a drought in Taiwan and water shortages stop microchip production? A digital twin can predict the risk of this phenomenon, find out what impact it will have on your supply chain, and – using reinforcement learning – can suggest what steps should be taken to minimize the damage.

If you are a car manufacturer in the Midwest of the United States, a digital twin may advise you to purchase additional components from a West Coast distributor that still has a surplus. But multiple situations thread together and things soon become massively complicated. For example, according to Simchi-Levy, Ford maintains more than 50 plants worldwide, using 35 billion parts to produce 6 million cars and trucks each year. About 1,400 suppliers are scattered across the 4,400 manufacturing sites with which it communicates directly and a pile of suppliers and suppliers of up to 10 levels deep between the raw materials of Ford and its vehicles. Any one of these links can be broken and a good stress test should investigate each of them.



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