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
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.
- 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 transport 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).
- 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.
- 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.
- 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
Companies are always looking to minimize inventory costs while providing what their customers need in a timely manner — 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.
- Optimal inventory situation
- Forecasting of sales quantities enables needs-based personnel planning
- Fewer out-of-stock situations and thus higher customer satisfaction
- Fast and easy integration into existing ERP processes thanks to standard connectors for SAP and Microsoft
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 short text, the article 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.
- Fully and semi-automated correction of master data errors
- Automatic derivation of storage and retrieval tax codes
- Automatic storage bin assignment for new articles
- Improved master data quality and thus higher process reliability
By evaluating and analyzing existing machine and plant data and using complex mathematical algorithms and machine learning methodologies, failures and malfunctions of industrial plants can be predicted and proactively avoided. Through the use of sensors, data is permanently collected, which is analyzed and evaluated 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.
- Demand-oriented planning of mechanics
- Better planning basis for the procurement of spare parts
- Reduction of downtimes
- Fast Return on Investment
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: using intelligent image recognition mechanisms to quickly and easily read data from nameplates without 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.
- Increase process efficiency
- No typing errors
- Automatic retrieval of relevant maintenance orders
- Real-time data acquisition and availability
Product Recognition for Returns
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 if the lighting conditions, angles, and backgrounds differ from the image of the item. An analysis of material or other additional features such as weight is also possible.
- Faster and better processing of returns
- Automatic article suggestions facilitate the process
- Integrated video/photo documentation of the process as proof for customers
- Self-learning system that constantly evolves and learns with user feedback
Warehouse Resources Forecast
- To optimize inventory management as well as warehouse staff planning
Enhancement of the Logistics Release Case or Purchasing Planning
- To respond dynamically to load peaks (seasons, events, holidays, etc.)
- In order to bring in advance goods whose ordering probability is high closer to the customer's place of delivery
Integration of External Data
- e.g. preparation of weather-dependent deliveries based on historical data and current weather forecasts
Forecast of Complementary Goods
- For placement in the warehouse and, if necessary, order proposals for customers
Our Services For Your Success
As an international IT specialist, we offer more than Service Level Agreements or licenses. 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 the requirements, needs, and initial situations of our customers.
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 & analytics, we show companies what today's modern and efficient logistics look like and which trends of tomorrow they should already be focusing 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".