Machine Learning in Logistics and Supply Chain 6 Use Cases Included

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" width="308px" alt="supply chain ai use cases"/>

Further, the company’s robust supply chain utilises proactive and early warning systems to assist them in mitigating the risk and quick query resolution. The company has a massive product portfolio that generates a huge amount of data which needs to be integrated on a central level for predictive analysis and driving operational efficiencies. Machine learning can play an instrumental role in optimising the complexity of production plans. Machine learning models and techniques can be used to train sophisticated algorithms on the already available production data in a way which helps in identification of possible areas of inefficiency and waste. A Statista survey identified visibility as an ongoing challenge that grapples the supply chain businesses.

The first is forecasting, where AI is used to make predictions about downstream demand or upstream shortages. Moreover, algorithms can detect one or more events they recognize as precursory to failure, and then warn assembly line operators before production quality falls short. In the post-pandemic world, enterprises plan to optimize their supply chains and logistics management to overcome disruptions. That’s why early adopters of AI in SCM reported 15% lower logistics costs, 35% higher inventory levels, and 65% higher service levels.

Supply chain analytics and AI in driving relevance, resilience and responsibility

It ensures that the UPS drivers use the most optimized delivery routes in regard to distance, fuel and time. Supply chain has a lot of components right with managing inputs from raw materials, to manufacturing, warehousing, and distribution to customers. The power of forecasting improves when a good feature extraction algorithm like CNN is added on top of it.

As AI technologies continue to advance, they will further redefine supply chain operations. Predictive analytics, machine learning, and automation will play even more significant roles in shaping the supply chain process. Incorporating natural language processing, Walmart systematically parses customer reviews and monitors social media conversations.

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The logistics industry, from how truck drivers are organized to how products are ordered and scheduled, has almost completely adopted AI at various stages of their supply chain. With each new success, more businesses are jumping on board to optimize their business models with the adoption of AI in the supply chain process. Oracle, for example, is utilizing artificial intelligence to create databases that are self-updating and self-managing that their clients can use and take advantage of. Coupa has created an entire business structure around helping businesses manage their own supply chains with the help of AI and other deep learning programs. AI, as a tool for supply chain management, is enabling companies to pivot and navigate the escalating complexity of both global and local supply chains.

• At Attri, we can help you transform your organizational operations with our expertise in AI agent solutions and generative AI.
• The “chat” function of one of these generative AI tools is helping a biotech company ask questions that help it with demand forecasting.
• However, maybe for a very specific supply chain, which has been digitized, the use of deep learning for demand planning can be explored.
• A Bloomberg report suggests that in the past two years, the overall cost in the supply chain has reduced to 12% leading to profits.

Since the supply chain has a lot to do with understanding data, one method might not provide enough information or extract enough patterns to make any decision. A smart warehouse is a fully automated facility where most work is done through autonomous robots or software. In the process, complex tasks are made simple, and operations become more cost-effective. Companies can use a route planner based on genetic algorithms to map out optimal routes for deliveries.

Understanding the Future of AI in supply chain: Best Supply Chain Predictions for 2023 and Beyond

They bring forth the complexities and uncertainties in supply chain management that cannot be extracted, analyzed, and addressed through simple statistical methods such as moving averages or exponential smoothing. AI algorithms are capable of swiftly processing huge amounts of data about suppliers, in particular about their delivery times, pricing, and product quality. An e-commerce and retail giant Alibaba has opted for AI algorithms to find new suppliers for Taobao and Tmail. Even further, machine-powered systems can access suppliers’ risk profiles, assessing all available information. For instance, Intellias has developed a Microsoft uses AI services and data science to automate document reviews and make it easier to search throughout contracts.

However, its potential to reshape industries, from code writing to supply chain transformation, remains promising. If you would adopt Artificial Intelligence in your business, please contact us. USM Business Systems is a pioneering technology partner serving a wide range of industries with AI solutions.

AI in Supply Chain: Top Use Cases of AI in Supply Chain Management

A thriving supply chain business heavily depends on visibility and tracking, and constantly looks for technology that can promise to improve visibility. Many organizations combine various AI-powered solutions into one system to get the most benefits. Leading software solutions offer easy integration with other software and existing systems, so you don’t have to worry about that. Companies that adopt this technology in the earliest stages have a 15% reduction in logistics costs, inventory improvements of about 35%, and a service improvement of 65%.

Organizations often procure an SCM solution from leading vendors (SAP, Oracle among many others) and implement it after implementing an ERP solution. The combination of the technologies already mentioned at the beginning into a unified architecture prepares the basis for several important innovations. The most important characteristics of this approach are, for example, flexibility, speed and efficiency, as work is done in a way that bypasses hierarchies, whereby the hierarchy stands for rigidity and a lack of efficiency. Furthermore, the adaptable network can better adjust to customer wishes, which is best described by the term customization [30]. Greater decentralization strengthens situational awareness, which allows a variety of responses to events, changes and disruptions.

Benefits of Machine Learning in Supply Chain

If you Google AI for supply chain management, you’ll get hundreds of solutions designed to help optimize supply chains and other business processes. Uptake uses AI and machine learning to analyze data for telematics with the goal of predicting failure in order to reduce downtime for a variety of vehicles and machinery, including trucks, cars, railcars, combines and planes. Supply chain and logistics teams then can anticipate issues, lower operational costs and develop more consistent workflows. H2O.ai is simplifying supply chain and manufacturing duties by encouraging businesses to embrace AI. Leaning on AI and a cloud platform, H2O.ai can forecast demands and returns, detect faulty machines and anticipate when maintenance will be needed.

This helps businesses align their strategies across departments, optimize resource allocation, and better respond to changes in demand and market conditions. For instance, Tetra Pack uses AI to develop Tetra Rex packages that have a lower environmental impact than equivalent glass and plastic packaging and are recyclable. AI algorithms also aid with precisely forecasting customer demand, thereby decreasing overstock inventory. For example, Nestlé leverages AI to predict demand for their goods in various countries and decrease the number of overstocked products by 10%.

While developing custom transportation management software, web development vendors are often asked for vehicle condition tracking features. Though not every AI-powered software supports fleet wearout monitoring, the technology has the potential to aid companies with timely equipment updates. But a company doesn’t need a pandemic-sized disruption to knock a normally operating supply chain off kilter if the company lacks access to vital information.

This can direct businesses to create new products or services that respond to trends or customer satisfaction standards. AI-powered technology facilitates the smooth and sustainable flow of goods, components, and materials in a global, data-driven business environment. According to IDC, by 2026, 55% of Forbes Global 2000 OEMs are projected to have revamped their service supply chains with AI.

• The benefit of these power automated quality inspections translates to reduced chances of delivering defective or faulty goods to customers.
• IoT device data is generated from in-transit vehicles to deliver real-time insights on the longevity of the transport vehicles.
• Managing inventory levels is a delicate balance between avoiding stockouts and minimizing holding costs.
• Therefore, the ability to attend to volatile order volumes is a challenge for many companies.
• Generative AI can analyze product dimensions, fragility, and other factors for packaging optimization to suggest the most efficient and environmentally friendly packaging solutions.
• Since there are manual errors in the path of order alignment, it is not possible to place the resources correctly.

AI-driven companies are able to make decisions and adapt to changes faster, improve customer service and satisfaction, and reduce costs. With the advent of AI, the world of business is quickly evolving to adapt and capitalize on the opportunities it offers. AI has enabled organizations to automate their operations, improve performance, reduce costs, and manage risks more effectively. One aspect of business operations that can benefit substantially is AI in supply chain management. AI is a commonplace technology for the supply chain now that enterprises of every scale and size have adopted its extensive applications.

Generative AI can optimize various aspects of the supply chain, such as inventory levels, production schedules, and delivery routes. The models can be trained on historical data to identify patterns and trends that can help optimize the supply chain. Efficient transportation and logistics management are critical components of a well-functioning supply chain. Generative AI can optimize route planning, delivery scheduling, and resource allocation by considering traffic conditions, weather forecasts, vehicle capacities, and customer demands.

Supplier evaluation is modeled as a multi-agent system that simulates buyer and supplier negotiations. This evaluation approach can be applied to attain goals similar to sustainability in the given scenario. The architecture allows you to adjust supplier evaluation parameters based on defined goals and buyer preferences.

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