How The smart supply Chain Was Broken & AI Is Fixing It!

The shortage of labor and materials caused by the pandemic and other circumstances is forcing companies to rethink logistics.
The difficulties experienced by the global supply chain affect homes and businesses around the world, with empty shelves, record price increases, congested ports and sick truckers causing interruptions at every link in the chain.
Never before has the supply of products or services faced so many variables. The scarcity of raw materials in some cases is close to historical levels. Manufactured products are left in warehouses, cargo ships and warehouses due to a shortage of containers and of workers and truckers to help get them to their final destination. At the same time, the pockets and salaries of consumers are affected by the increase in prices.
The $9 trillion global logistics industry is reacting with investments in automation and the use of AI and big data to gain more insight from the supply chain itself. This makes startups in the sector experience good times
The need for solutions has made for good times for startups in the supply chain sector, which in the first 3 months of 2021 alone raised $24.3 billion in venture funding, 58% more than the total for the entire year 2020, according to analytics company PitchBook Data Inc.
Invest in AI
Within this scenario, companies see technology and accelerated computing as key to finding solutions and strengthening their position. At Manifest 2022 , a logistics and supply chain conference recently held in Las Vegas, USA, the industry discussed how to streamline supply chains and create cost efficiencies using AI and machine learning. Challenges raised included labor shortages, improving throughput at distribution centers and optimizing deliveries.
In this context, many companies are considering the power of NVIDIA AI to create new solutions in stores, warehouses and routes. An example of this is Kinetic Vision, which has developed machine vision applications on the NVIDIA AI platform that add intelligence to automated warehouse systems.
Companies like Kinetic Vision and SF Technology use video data from cameras to optimize every step of the package lifecycle, speeding throughput by up to 20% and reducing conveyor downtime, which can cost money. to retailers between $3,000 and $5,000 per minute.
Autonomous robot companies like Gideon, 6 River Systems, and Symbotic are also using NVIDIA’s AI platform to improve distribution center performance with their autonomous guided vehicles that efficiently transport material within the warehouse or distribution center.
And with NVIDIA Fleet Command, which securely deploys, manages and scales AI applications through the cloud on a distributed edge infrastructure, these solutions can be securely deployed and managed remotely and at scale across hundreds of distribution centers.
Digital twins and simulation
Improving store and distribution center layouts has also become the key to achieving cost efficiency. NVIDIA Omniverse, a 3D design collaboration and virtual world simulation platform, enables you to virtually design and simulate distribution centers with full fidelity. Users can improve workflows and performance with physically accurate and photorealistic virtual environments.
Retailers could, for example, build a solution on the Omniverse platform to design, test, and simulate material flow and employee processes in digital twins of their distribution centers, and then bring those optimizations into the real world.
Digital human simulations could test new workflows for ergonomics and employee productivity. And the robots are trained and driven with the NVIDIA Isaac robotics platform, creating the most efficient layout and workflows.
Kinetic Vision is using NVIDIA Omniverse to deliver simulation and digital twin technology to optimize retail and consumer product factories and distribution centers.
Artificial intelligence as a differentiating element
Although manufacturers, supply chain operators and retailers have their own approaches to solving the challenges, they are leaning on AI as a key differentiator.
According to consulting firm McKinsey, the successful implementation of supply chain management with AI has enabled early adopters to improve logistics costs by 15%, inventory levels by 35%, and service levels by 65%. %, compared to slower competitors.
Some experts estimate that the global supply chain will not return to normal until at least 2023, so companies are taking the measures that contribute the most to their businesses.