Future Vision: Achieving next-level supply chain management with AI
Ensuring a smooth flow from producer to consumer is no easy feat and can incorporate pass over of many hands and incorporating road, rail, sea, air, sea ports and intermodal ports. From food and consumable consumer-driven goods to materials, equipment and supplies, ensuring an efficient and effective supply chain is critical to supporting future economic growth, encouraging investment, building more sustainable communities and preparing for future global, national and regional challenges.
With such a huge challenge at hand, many logistics and supply chain companies are implementing AI and Machine Learning technology to achieve next-level performance in supply chain management.
According to McKinsey, successfully implementing AI-enabled supply chain management has enabled early adopters to improve logistics costs by 15%, inventory levels by 35% and service levels by 65%, compared with slower moving competitors. Given the significant value of these improvements, many solutions have emerged.
Here are 7 ways AI and Machine Learning are transforming the supply chain.
AI and machine learning offer many opportunities to automate import and export and allow for safer processes.
License plate recognition allows for more efficient management of truck yards. Automatically capture data such as parking count, occupancy, vehicle entry and exit time, and duration of parking.
When integrated with weighbridges, employ safer practices during loading and unloading of cargo, as smart cameras can match license plates with the overall weight carried by the vehicle, notifying workers of loading limits.
When utilized in ports, plate detection can assist port authorities to capture information of shipping containers that enters their premises. Data such as container numbers and license plate of the vehicle carrying the container are crucial to this process. Inaccurate data capturing due to human error can lead to delivery delays and costly expenses for shipment providers.
Industries that need to adhere to regulatory compliance, such as freight, can benefit from computer vision technology. Through using object detection, AI can notify authorities if it detects any non-compliance to the container’s attributes; such as heavy exterior damage and leaks, proper sealing practices, hazardous or dangerous material stickers, or tags. Computer vision can reduce human error and help to ensure compliance needs are met.
At a consumer-focused level, AI can be implemented to enable businesses to identify the depth and type of damage of a product and take further action to reduce damage, long before it reaches the customers’ hands, improving overall levels of satisfaction.
Viana™ a meldCX product, utilizes Vision AI and Machine Learning to detect inconsistencies and notify when detected, allowing human power to be focused in higher order areas of business.
Predictive maintenance is predicting potential machine failures in the factory by analyzing real-time data collected from IoT sensors in machines. Machine learning-powered analytics tools enhance predictive analytics and identify patterns in sensor data so that technicians can take action before the failure occurs.
Through predictive maintenance, companies are able to ensure that their machinery is always in tip top shape regardless of conditions such as harsh weather, and reduce chances of downtime all while reducing lifetime repair costs to expensive machinery.
Delivering goods from A to B the most efficient way can be vastly improved with AI technology. Route optimization uses shortest path algorithms to identify the most efficient route for delivery trucks.
Having real-time insights of their vehicle fleet enables businesses to improve operational efficiency while increasing overall profitability. Utilizing route optimization technology could allow businesses real-time insights into:
- Updates of delivery times, allowing automated updates to customers as well as back-end teams to inform of delays
- Alerts when and if drivers diverge from their routes
- Dynamic routing based on traffic and weather conditions
- Easy tracking and reporting of deliveries
Autonomous Vehicles, Machinery and Robots
Self driving vehicles, drones, robots and autonomous machinery are all utilized from all touch points of the supply chain in order to maximize efforts throughout the supply chain and allow more human effort to be spent on delivering great customer service.
With technology and humans working in unison, businesses are able to reduce error rates, automate repetitive tasks and create safer, more effective working environments.
eCommerce giant Amazon, has over 200,000 robots working in their warehouses. In 26 of Amazon’s fulfillment centers, robots assist humans with picking, sorting, transporting and stowing packages to allow customers to receive their packages on time.
Utilizing real-time data, AI and ML technology can enable organizations to make great strides in their forecasting efforts. AI-powered demand forecasting methods reduce error rate significantly compared to traditional forecasting methods such as ARIMA, AutoRegressive Integrated Moving Average, and exponential smoothing methods.
With improved accuracy in demand prediction, manufacturers and suppliers can better optimize the number of vehicles to warehouses to reduce operational costs and improve manpower planning, warehouses and retailers can reduce holding costs and customers are less likely to experience stockouts that reduce overall customer satisfaction.
As AI becomes increasingly more intelligent, predictive technology could take supply chain players into the territory of anticipatory delivery models, supplying the consumer goods before they even realize what is needed.
Cognitive Workflow Automation
With dozens of handover points and new paperwork piling up at each step of the way, global freight forwarding is akin to a relay race. Logistics specialists and customs agents must decipher information contained in millions of papers in non-standard formats, ranging from bills of lading to customs declarations, along the way.
Cognitive workflow automation can streamline the complex back-office work that drives global trade. Intelligent optical character recognition (OCR) programs that read both printed and handwritten text paired with workflow automation software can streamline these activities, freeing logistics professionals from simple and more repetitive tasks and allowing them more time to focus on customer service and experience.
Concept SALi by meldCX optimizes the shipping process for Australia Post through OCR technology powered by Machine Learning and Vision AI. The self-service kiosk allows customers to lodge their own parcels and in return helps to automate workflows through verifying the package size, weight, sender's identity, handwritten information and shipping cost -- elevating the complexity from shipping a package for customers and employees.
Viana™ a meldCX product, works at the edge and allows companies to gather real time insights and operational data, all while keeping completely anonymous so no identifiable information is captured.
Ready to see how AI can transform your supply chain? Book a demo with our Vision AI expert today!
This article is an installment of our Future Vision series, where we tackle insights on Vision AI disruption across industries.