AI and IoT-driven smart supply chains

AI and IoT-driven smart supply chains, 해시게임 In the digital age,

the level of intelligence in the supply chain determines the production efficiency and personalized service level of an enterprise.

해시게임

The Internet of Things, robotics, and artificial intelligence are rapidly driving the digitization and intelligence of supply chains.

The integration of big data analysis and sensor data, through the digitization of everything and the interconnection of everything,

It provides support for lean production management, improving the overall collaboration efficiency of the industry, and digital innovation capabilities in the global market.

Digital Supply Chain Value

Supply chain digitization improves the quality and efficiency of enterprise operations, reduces production costs, and increases the flexibility of capital flow by improving enterprise agility.

Drive business operations and successfully transform and upgrade.

Intelligence and digitalization enhance supply chain management and supply chain service capabilities.

Supply chain managers can leverage available data/information to enhance end-to-end customer engagement,

Improve the interaction of all aspects of production and service.

Digital technology provides information transparency for supply chain managers and can build demand-aware capabilities based on demand,

Predict future changes and trends in all aspects of production or service, and improve forecast quality and operational efficiency.

For example, supply chain terminal tracking systems can send detailed updates about orders at any time.

The application of a digital intelligent

supply chain to realize automation greatly reduces the production cost of enterprises.

According to the forecast*, by applying advanced methods to calculate and optimize the strategy,

With intelligent planning of routes and optimized transport dynamics, transport and warehousing costs can be reduced by up to 30%.

At the same time, with the support of advanced digital systems, 80% to 90% of tasks and work plans can be automated*.

Compared with manual operations, the automated supply chain decision-making process based on real-time updated solutions,

Information is more accurate and timely,

and the system can detect abnormal conditions that require immediate intervention.

Automated operations simplify the work of supply chain professionals, allowing them to focus on more valuable tasks.

For example, digital solutions can be configured to automatically process real-time information, automate preparation and workflow management,

This eliminates the manual work of collecting, cleaning, and entering data.

The application of digital and intelligent supply chains

by enterprises can ease the pressure on capital flow.

A considerable part of the capital flow pressure on production and commercial enterprises comes from inventories.

Implement a new production planning algorithm that refines changes in demand and supply during production and manufacturing to minimize inventory.

In addition, the uncertainty in the process is greatly reduced due to the greatly improved forecasting accuracy of demand/supply,

Considerations for safety stock have been reduced or eliminated accordingly,

making zero-stock planning an operational option.

Applying intelligent supply chain management, the overall inventory will be reduced by 75%, which greatly relieves the pressure on the capital flow of enterprises.

Digital Supply Chain Features

The global economy is undergoing transformation and upgrading, and the waves of the Internet, the Internet of Things, artificial intelligence, machine learning, and cloud computing are sweeping the world.

The modern business environment faced by enterprise innovation puts forward higher requirements for refined and lean management.

In the traditional supply chain,

digital waste/data waste hinders the potential of intelligent supply chain applications.

Digital supply chains use IoT and other advanced technologies to automatically collect and process information,

Use artificial intelligence and big data algorithms to enhance valuable data,

Reduce the generation of digital waste and automatically support decision-making and other activities.

The ever-expanding digital technology and artificial intelligence, the Internet of Things, and big data realize cloud-based intelligent supply chain services,

Provide more and more digital solutions to meet supply chain management needs.

Machine learning systems can advise supply chain managers on how to handle specific situations,

Such as changing material plans and schedules based on new customer orders, or fully automating decision-making.

Automated decision-making systems can be adjusted across functions to improve efficiency.

Powerful and user-friendly analysis tools can compile large amounts of unstructured data and extract useful insights from it.

AI applications can automatically track performance issues,

find root causes, and then recommend corrective actions to managers.

Another benefit of cloud-based digital technologies is that they are easier to set up and use than before, and offer more personalized products and services.

For example, cloud-based products can be piloted at any time and then rapidly scaled across organizations.

Many new technologies can be connected to ERP systems using standard application programming interfaces (APIs) for easy integration with existing systems or software packages.

AWS Service Portfolio and Value for Supply Chain

For smart supply chains, AWS IoT products for industrial, consumer, and business solutions span the cloud,

Build supply chain solutions for virtually any IoT use case across a wide range of devices.

Based on AWS IoT and AI integration capabilities, supply chain equipment is smarter.

In addition, using AWS device software, supply chain managers can securely connect devices and collect data even without a network.

Perform intelligent operations locally through big data analytics and artificial intelligence algorithms.

Georgia-Pacific optimizes manufacturing and supply chain processes

Use Amazon Kinesis to stream real-time data from manufacturing equipment to a central Amazon S3-based data lake, but

It enables the acquisition and analysis of structured and unstructured data at scale.

At the same time, using an AWS-based advanced analytics solution,

the factory’s critical manufacturing processes were optimized, increasing profits by millions.

For example, for a production line,

AWS data analytics technology predicts the quality of the paper stock roll,

Eliminating 40% of paper roll tearing can increase profits by millions of dollars on a single production line.

By optimizing the cutting process, the waste associated with the production process has been reduced by 30%.

Using artificial intelligence for forecasting, equipment failures can now be predicted 60-90 days in advance,

This means that equipment downtime can be planned, improving asset utilization and paper mill safety,

And help factories avoid lost revenue from unplanned production shutdowns.

Data is transformed in a structured way using Amazon EMR via Amazon Redshift.

Analysts use Amazon Athena to query raw data on top of Amazon Simple Storage Service (S3),

This includes information on pulping mechanisms, paper machines, however, converting lines, vibration trends, yields, and paper quality.

Also uses AWS SageMaker to build, train, and deploy ML models at scale.

Using ML models built on raw production data,

Amazon SageMaker provides machine operators with real-time feedback on machine speed and other adjustable variables,

Enables less experienced operators to detect potential quality issues earlier.

It plans to interconnect its production equipment in 122 manufacturing plants around the world through the industrial cloud,

however, to store, collect on-device operational data, and analyze it to optimize production.

The industrial platform plans to add data from around 1,500 suppliers to the connected portfolio as well.

The combination of data from all plants will provide new energy for process optimization.

These measures include more efficient control of material flow,

Early detection and elimination of supply bottlenecks and production process interruptions,

Optimizing the operation of machines and equipment in factories,

Establish production planning and inventory management,

Reduce equipment waste in the production process,

Monitor the movement of car parts throughout the supply chain,

Track the movement of goods inside and outside the factory,

vehicle location services,

Analyze efficiency across systems and more.

Selected a portfolio of AWS services, including Internet of Things (IoT), Amazon Simple Storage Service (S3) enterprise-grade data lakes,

AWS’s connected devices and Amazon SageMaker artificial intelligence SDK,

however, have machine learning analytics and computing services, intelligent robotics, and data analysis functions, etc.

These services have been developed for production environments and can be extended to the automotive industry on other specific requirements.

Also, part of the program will be built on AWS Outposts.

The platform standardizes and simplifies data exchange between systems and factories.

Through the development of the Industrial Cloud, all 122 automotive production plants will be standardized and networked,

Laying the groundwork for the seamless digitization of its production and logistics.

The collaboration with AWS will have a profound impact on the productivity and quality of the global supply chain.

Using the Internet of Things, machine learning, and cloud computing, the goal of the car is to increase the productivity of the factory,

Long-term integration of supply chains in the industrial cloud.

With the expansion of the production scale,

however, the original IT architecture began to encounter bottlenecks and could not meet the needs of rapid business development.

Product development, marketing, consumer communication,

and marketing channel management put forward higher requirements for large-scale data analysis and processing.

Choose the AWS cloud platform for overall big data strategic planning.

The current dealer supply chain, consumer services, and e-commerce platforms are all built on AWS.

AWS cloud platform provides rich functions to support the construction of a big data lake,

Including Amazon S3, Amazon EMR, Amazon RDS, Amazon DynamoDB, Amazon Redshift, etc.,

These functions cover data storage, security protection, analysis, processing, and other aspects.

New digital technologies are enabling companies to completely change the way their supply chains operate.

Use the automation brought by the supply chain to improve rigid efficiency, intelligently meet differentiated and personalized needs,

Bringing new levels of speed, efficiency, and flexibility to the supply chain.

AWS’ global cloud platform integrates global supply chain resources and users.

Taking information flow as the center, it drives the operation of logistics and capital flow.

Using the global service network of AWS, the digital intelligent supply chain is fully interconnected,

In terms of technology, we strive to promote companies to go overseas,

and in terms of business models, we help companies expand into new markets and explore value points.