Artificial Intelligence (AI) in Logistics
Improve Logistics Processes with the Help of AI Technologies and Increase Competitiveness
Artificial Intelligence (AI): Exploiting Potential along the Supply Chain
Globalization, digitization, and the increasing complexity of value chains bring special challenges and opportunities for logistics. One way to successfully address these is to use machine learning technologies: With the right tools, you can improve selected logistics processes and increase your competitiveness.
Machine Learning (ML) is a sub-discipline of Artificial Intelligence that uses databases to derive decision recommendations. Coupled with our extensive experience in supply chain management and logistics, we can provide you with the best possible support in optimizing and developing your logistics processes. For example, when it comes to release multiple orders from a customer for the warehouse optimally. This takes into account the promised delivery dates for the customer as well as the utilization of the warehouse and the provision of the goods for transport.
Artificial Intelligence (AI): Use Cases in Logistics
Generative AI with platbricks®: Chat with Your Data, Dynamic Dashboards & Documents
With platbricks® Generative AI, specialist departments access operational logistics data directly using natural language - from simple key figures to complex analyses. "Chat with Your Data" creates ad-hoc visualizations, saves queries as dynamic dashboards, and automatically generates documents (e.g., delivery bills). A glossary clarifies your company's terms, a role-based authorization concept safeguards sensitive data, and a long-term memory continually enhances responses.
Advantages:
- Faster decisions: KPI queries and analyses via text input.
- More self-service: create dashboards without a BI ticket.
- Standardized language: Glossary for consistent results.
- Secure use: role & rights model protects data.
- Reusability: Save queries/documents as templates.
Virtual assistants & agents: Your logistics co-pilot
Next step after self-service analytics: virtual assistants in platbricks® that proactively monitor KPIs, recognize events, and initiate tasks, including recommendations for action. Roles and rights control what assistants can see and do. This creates a "logistics co-pilot" that relieves teams and shortens response times.
Advantages:
- Proactive control: Assistants monitor KPIs/events.
- Less response time: automatic alerts in the event of bottlenecks.
- Focus on the essentials: Routine checks run in the background.
- Governance by design: rights/rules per role.
- Scalability: Add additional use cases.
Supply Chain Control Tower with GenAI & platbricks®
The Control Tower bundles real-time data from the warehouse, transport, and partner network. GenAI prioritizes deviations, explains causes, and suggests options. In platbricks®, measures are initiated directly from the control center. This responds to trends such as end-to-end visibility, accelerating decisions from monitoring to action.
Advantages:
- End-to-end transparency: real-time data from all areas.
- Prioritized deviations: AI explains causes and options.
- Fast implementation: workflows directly from the control center.
- Modular Rollout: from Pilot to Global Scaling.
- Higher service quality: lower expedite costs.
Warehouse Robotics & Automation: manufacturer-independent integration
Whether using AMR/AGV or AutoStore, platbricks integrates robotics into order and resource control independently of the manufacturer. The control station orchestrates both manual and automated processes, as well as IoT signals, and edge connections. Result: high-throughput, flexible Storage processes.
Advantages:
- Higher throughput: AMR/AGV orchestrated with manual processes.
- Flexibility: Manufacturer-independent integration.
- Reduced travel times: Slotting/heatmaps optimize routes.
- More stable quality: standardized interfaces.
- Better economy: higher productivity per area.
IoT- & Location-based Logistics: Example "platbricks® Container management meets IoT"
With "platbricks® container management meets IoT", the entire life cycle of reusable containers - from delivery to collection, processing, and disposal - is fully mapped and tracked in real-time. Thanks to IoT sensor technology and partner solutions, such as those from Bornemann and Flowcate, the booking and location of containers are entirely automated, eliminating the need for manual scanning or booking. The solution provides a precise location overview that is accurate to within one meter, enabling end-to-end transparency across both internal and external sites. The open architecture, based on industry standards (e.g., Omlox), ensures maximum flexibility and easy integration into existing systems.
Advantages:
- 100% automated bookings - no more manual scanning or booking
- End-to-end transparency across all locations and containers in real time
- Plan, control, and react in real time based on current data
- Quick and easy commissioning thanks to minimal hardware requirements
- Open, scalable architecture based on industry standards
Artificial Intelligence (AI): Use Cases in Logistics
Optimizing Cut-off Time with Machine Learning
Your customers regularly order goods from you. Your warehouse prepares the delivery in a timely manner. Before the delivery is made, the same customer places a new order with you. You would like to combine different orders from the customer that are shipped at one delivery time. This way you can save packaging material, volume and transportation costs.
To overcome this challenge, we have developed a machine learning system: The neural network is fed with the key data of the orders from your system and is thus able to estimate whether a customer has already completed his orders for the current period or not.
Advantages:
- You can predict the ordering behavior of customers
- You can estimate when customers have fully completed their orders
- You can optimize the delivery of multiple orders to one customer
- You save packaging material, volume and transportation costs
AI-based Path Optimization
Short walking times increase productivity in order picking. Using AI-based algorithms, we have developed a solution approach for the best possible item positioning and allocation to suitable fixed locations. The following steps are run through: Feeding the AI with pick data, manual selection of special cases if necessary, forecast generation for picks, sequence generation, allocation to storage bin, selection of stock transfer suggestions and forwarding to the WMS. The microservice is available as a Microsoft web service based on Azure and can be easily integrated using standard interfaces (REST API).
Benefits:
- You keep the time from order entry to shipment as short as possible
- You process more orders due to shorter throughput times and can thus achieve more turnover
- You optimize item density and order bundling
- You solve the "Traveling Salesman Problem" by determining the shortest route length based on mathematical calculation of possible walking distances
Master Data Error Detection in Logistics with AI
Master data, such as item description, dimensions, or weight, play an important role in planning processes, e.g., storage location determination, package predetermination, or freight space planning. Each master data record is analyzed for possible anomalies in our solution, such as material or customer master errors. Probabilities and score values are calculated as a measure of the anomaly. In an integrated workflow, a notification is made in the warehouse management system when anomalies are detected. The service is offered as a web service in Microsoft Azure and can be called via Rest API. There is a standard connection to our cloud logistics platform platbricks.
Benefits:
- The AI-based checking service does not include static rule sets
- The algorithm learns with every true/false process
- By scoring the data quality, the master data can be permanently monitored
- Distributed master data maintenance can be monitored automatically
Efficient Warehouse Management with Chatbots
An automated form of communication via chatbots offers the possibility of providing relevant information in real-time, for example, on the order status in the warehouse, the transport status, the degree of utilization in the warehouse, or the warehouse availability for customer service. Users address their concerns to the connected system via chatbots by simply sending messages - as if they were addressing a "real" person. In this way, communication between the user and the system (e.g., the warehouse management system) is completely revolutionized. In this way, chatbots can also be a valuable aid in logistics.
Benefits:
- Short implementation and learning time
- Flexible retrieval of information via mobile devices
- High scalability and connection of various data sources through the cloud
- High level of security through role and authorization structures
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Inventory Forecast
Companies are always looking to minimize inventory costs while providing their customers with what they need on time — our solution: implementing intelligent inventory forecasting technology that enables lean and responsive inventory management. Using artificial intelligence, warehouses will be able to predict item sales and expected demand, ensuring that available inventory meets customer needs. Inventory-influencing parameters are constantly evaluated and analyzed. Dependencies are identified from historical and current data and adapted for future forecasts.
Advantages:
- Optimal inventory situation
- Sales volume forecasts enable demand-driven personnel planning
- Fewer out-of-stock situations and thus higher customer satisfaction
- Quick and easy integration into existing ERP processes thanks to standard connectors for SAP and Microsoft
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Article Classification
Using an AI-based article classification, articles are sorted into predefined classes. The automated classification eliminates the need for time-consuming manual data sifting. Based on adjustable criteria, such as the article's short text, the article's number, the article hierarchy, and/or the geometric properties, the AI identifies and groups the articles. With the help of the pattern recognition used, significantly more data can be included in the assignment than would be possible by manual means.
Advantages:
- Fully and semi-automated correction of master data errors
- Automatic derivation of storage and removal control indicators
- Automatic storage location assignment for new items
- Improved master data quality and thus greater process reliability
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Predictive Maintenance
By evaluating and analyzing existing machine and plant data, and utilizing complex mathematical algorithms and machine learning methodologies, failures and malfunctions in industrial plants can be predicted and proactively avoided. Through the use of sensors, data is continuously collected and analyzed by algorithms. For example, speeds, noises, or temperatures of motors can be recorded, and unusual vibrations or imbalances can be detected at an early stage.
Advantages:
- Demand-oriented planning of technicians
- Better planning basis for the procurement of spare parts
- Reduction in downtime
- Fast return on investment
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Smart Nameplate Recognition
Nameplates reflect the essential information for identifying a machine or motor vehicle. However, reading the nameplates can quickly become time-consuming in larger industrial plants or factories. Our solution utilizes intelligent image recognition mechanisms to quickly and easily read data from nameplates without requiring human intervention. Via an image capture of a nameplate by an installed camera or a drone and an image recognition service, the nameplate data can be read, stored, and managed.
Advantages:
- Increased process efficiency
- No typing errors
- Automatic retrieval of relevant maintenance orders
- Real-time data collection and availability
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Product Recognition
In the case of returns, original item numbers or other required information are often missing. Direct assignment of the item is then not possible, and you have to carry out identification manually. Our service assigns an item to be returned using a probability indicator. The product is recognized and identified via a video recording. Thanks to neural networks, this is possible even when the lighting conditions, angles, and backgrounds differ from those in the image of the item. An analysis of material or other additional features, such as weight, is also possible.
Advantages:
- Faster and better processing of returns
- Automatic item suggestions simplify the process
- Integrated video/photo documentation of the process as proof for customers
- Self-learning system that is constantly evolving and learning from user feedback
Our Services For Your Success
We offer more than service-level agreements or licenses as an international IT specialist. We manage our clients ' entire long-term business development. The task requires comprehensive SCM expertise, flexibility, innovation, and an entrepreneurial approach to thinking and acting. We serve as our clients ' strategic and technology partner, IT implementation and process optimization specialist, education and change manager, and service partner for hosting and applications.
As a long-standing SAP Gold Partner, our expertise includes consulting services and implementations of SAP solutions, such as SAP S/4HANA, SAP EWM, or SAP TM. On the other hand, we also successfully close digitization gaps in logistics with our specially developed cloud platform, platbricks® - as supplements to our SAP solutions or as a stand-alone logistics solution. This enables us to individually adapt the optimization options along the supply chain to our customers' requirements, needs, and initial situations.
In addition to efficiency, sustainability, and future-proofing, we also stand for innovation in the Digital Transformation of the supply chain. With mobile logistics apps, chatbots, or AI and analytics, we show companies what today's modern and efficient logistics look like and which trends of tomorrow they should already focus on now.
For its competence in Artificial Intelligence, Arvato Systems has received several awards in the current study "PAC Innovation Radar - AI-related Services in Germany 2020" by the market analysis and consulting company PAC.
In the "Logistics/SCM" area, our AI-related services were ranked "Best in Class".
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