How the SYNAOS IMP saves 30 percent vehicles

Fewer transport vehicles and still the entire order pool processed on time? This is possible - with the SYNAOS Intralogistics Management Platform (IMP). Through AI-based Decision Automation and Process Optimization, orders are distributed more sensibly. This saves expensive hardware and reduces delays.

A car consists of several thousand individual parts. If the exterior mirror does not arrive at the production line in time, there is a risk of production demolition — the production lines are at a standstill and there are expensive waiting times. It is therefore all the more important that the necessary parts arrive at the right place reliably, punctually and efficiently. Mobile robots, i.e. AGVs (Automated Guided Vehicles) or AMRs (Autonomous Mobile Robots), are increasingly responsible for transport within the factory. Will these be combined with the SYNAOS IMP software solution controlled, up to 30 percent of these vehicles can be saved and delays significantly reduced. How is that possible?

HOLISTIC APPROACH: ALWAYS KEEPING AN EYE ON EVERYTHING

A simple sample customer clearly shows how the savings are achieved. SYNAOS simulated several scenarios for this: In the first scenario, SYNAOS IMP optimizes the distribution of tasks to a total of 59 driverless vehicles. The adaptive algorithm does not follow a fixed plan, but takes complex dependencies, travel times and the entire task pool into account. As a result, it is not necessarily the fastest vehicle that receives the first order, but the best one in terms of overall optimum. Its travel time may be longer, but it still requires less time overall: The AI-based algorithm follows a holistic approach and predictively analyses global interaction. On the whole, orders and vehicles are combined in the best possible way.

RESPOND FLEXIBLY TO FAULTS

The result: delays are reduced and there are fewer delays and problems. The software continuously and in real time checks whether acute changes are necessary. For example, if a vehicle suddenly fails, the adaptive algorithm immediately calculates alternative solutions and, in the worst case, prevents production from being shut down. Comprehensive monitoring also makes it possible to flexibly move orders in between. The vehicles are always optimally utilized.

FEWER VEHICLES, FEWER DELAYS

In the second simulation scenario, tasks were distributed step by step — this is still the standard in many logistics centers and factories. The rigid rules dictate that an order always goes to the best vehicle. Without the smart software from SYNAOS, there are delays over the course of a simulated eight-hour shift, which accumulate towards the end of the shift:

To reduce delays to the level of scenario 1 without abandoning gradual scheduling, 76 vehicles would be required instead of 59. Conversely, this means: By using the SYNAOS IMP and its sophisticated algorithm, 17 vehicles can be saved — i.e. just under 30 percent!

CONCLUSION: SMART SOFTWARE SAVES RESOURCES

The powerful SYNAOS software ecosystem distributes tasks according to smart and flexible rules. All relevant information flows into machine occupancy planning in real time. The SYNAOS IMP therefore immediately recognizes delays and compensates for them through lightning-fast rescheduling. The algorithm calculates 250,000 combinations per second and thus always finds the best solution to control vehicles as efficiently as possible.

Our complex simulations have shown that AI-based holistic fleet optimization requires fewer vehicles than is the case with a classic planning approach. A good 30 percent of vehicles can be saved by intelligent control. (The practice-oriented simulations represent production in the automotive sector. The energy management of the vehicles was not taken into account.) Another advantage: If there are fewer vehicles on the road, the traffic network is significantly reduced and obstructions occur less frequently. The exterior mirror reaches the production line on time and can be installed without delay.

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