Automated Guided Vehicles move material from one place to the other. What sounds simple is actually quite complicated: The more vehicles are on the move on the store floor, the greater the challenges become. A smart control system is needed.
Nowadays, every order is a custom order. For example, in e-commerce: Every shopping cart is unique and may contain a wide variety of products that must first be transported from large warehouses into their packaging. A vacuum bag, textbook and new sweatpants must all be packaged and shipped as rapidly as possible.
Efficient intralogistics management is extremely important: after all, when customers order products, they want to receive them as quickly as possible. No online shop can survive now with sluggish order handling that takes a matter of days – the competition is simply too tough. Other providers can offer next-day delivery, and they strengthen customer loyalty by doing so.
The configuration and assembly of a new car is also highly complex. The vehicles coming off the conveyor belt these days are not just dull standard models, but unique items with selected special equipment. These developments might make individualists happy, but they pose particular challenges for manufacturers and their intralogistics systems: ultimately, assembling a customer’s dream car requires many individual parts to be in the right place at the right time. If they don’t arrive at the assembly line on time, this could result in expensive delays.
In production halls and warehouses, Automated Guided Vehicles (AGV) move the required materials from one place to another. Incoming goods are first brought to the warehouse and stored there. In the next step, the parts must be transported for final assembly, interim storage or shipment handling.
AGVs and AMRs (Autonomous Robots) take care of these various transport tasks and operate autonomously. Precisely in this context, processes must be carefully planned, efficiently optimized and finally carried out. The method required here is holistic optimization – not just step-by-step planning. The desired goal is to achieve ideal utilization of resources and maximum delivery performance. The key is on-time delivery of all required parts and materials.
Bottlenecks, accidents or technical breakdowns interrupt the process and rapidly thwart even the most cautious of plans. What is therefore required above all is flexibility and a rapid response. Human beings can only manage this to a limited extent – the complexity and volume of data involved in sensible planning is simply too large. Top-down planning that is only adjusted once or infrequently will not be sufficient, since modern shop floors are highly dynamic.
Nonstop Optimization in Real Time
A modern solution requires continuous optimization in real time: A control software must react to events without any delay and reschedule rapidly, again and again. What if a vehicle suddenly breaks down? Then a replacement has to jump in and take over the task. This is exactly where SYNA.OS LOGISTICS comes in: The AI based software makes new plans 250,000 times a second and continuously looks for the optimal solution to prevent a breakdown from causing serious delays. Algorithms distribute tasks, define routes and continuously review whether routes have to be rescheduled.
This kind of process optimization quickly achieves a high degree of complexity because countless dependencies and interconnections must be considered during planning. Every disturbance can trigger a sequential build-up similar to the famous butterfly effect: The smallest flap of a wing could trigger a tornado somewhere on the other side of the world.
Any modification or delay in intralogistics, no matter how small, can cause unforeseeable problems. As a result, control software has to continuously review the situation and react to events. This is exactly the job of modern algorithms, which process data in real time without interruptions and optimize processes based on the data. The more information, the better. In this case, complexity is a definite advantage!
Other circumstances and conditions exist which must also be considered during planning, for example different order characteristics: Which type of container is used? Which AGV characteristics are involved? Traffic management including route optimization also plays a crucial role. Ideally, AGVs always take the optimal route (which does not necessarily have to be the shortest). The decisive factor is the holistic interplay of elements and overall optimization.
Energy management, i.e. the power supply for the vehicles, also plays an important role. As long as they are filling up with electricity at the charging station, they are not available for orders. Proper energy management means that orders are completed on time and the entire fleet is kept in good shape.
The control process also considers various map data, for example the layout and design of the warehouses and production halls. Data such as speed limits, one-way streets, temporary closures due to construction work and the like are also included. Massive volumes of data might be incorporated into the optimization process, resulting in highly complex processes.
Despite the progress of digitalization and automation, fully autonomous fleets are rare to see. In reality, manual actors are also moving around the same halls, for example human employees who transport goods on a forklift. This mixture of manually operated vehicles and fully automated transport systems leads to an unpredictably dynamic and convoluted process. This poses a further challenge for the control process.
There are also certain data exchange issues to overcome: Each AGV and AMR manufacturer has come up with its own solutions for communicating with the vehicles and has developed proprietary software. However, this heterogeneity in communication has major disadvantages because it prevents unified control. It is also impossible to operate mixed fleets with AGVs from different manufacturers.
As a result, users are subject to what is known as vendor lock-in: Once they decide on an AGV brand, they are stuck with that one manufacturer and dependent on them for the long term. The situation becomes frustrating if a competitor has a much better and more affordable solution in their portfolio, but it is not able to work together with the existing vehicles in the fleet. What’s more, not every manufacturer offers AGVs and AMRs with all capacities for transport and maneuvering. This restricts the possible applications available for customers. However, there is already a solution for these problems: the VDA 5050 interface.
Read more about the new standard and its benefits in our blog entry VDA 5050: Industry Standard with a Big Vision.