FLP6000EOS Energy Optimizing Software
for the Positioning Solution System

MODULAR ENERGY OPTIMIZING SOFTWARE SIGNIFICANTLY REDUCES OPERATING COSTS

Industrial conveyor systems, such as stacker cranes, hoists, overhead cranes, shuttles or elevators, incur operating costs on a regular basis. To keep those expenses at a minimum and to enable plant operators to leverage the benefits of potential savings, PSI Technics developed the FLP6000EOS Energy Optimizing Software for the Positioning Solution System.

FLP6000EOS was specifically developed for systems with multiple axes and is available as an optional add-on for the Positioning Solution System.

The Positioning Solution System provides time-optimized controls that enable logistic facilities to operate at maximum capacity. The modular FLP6000EOS add-on enables you to precisely reduce operating expenses to achieve optimum positioning performance. Increased operating expenses incur due to high energy costs - the savings potential with FLP6000EOS software is substantial.

The energy consumption of a conventional motor drive (IEC energy class EFF2) is approximately proportional to the maximum travel speed (vmax), which in turn determines the energy required for acceleration. Even when using a brake feedback loop, this proportional interdependence will be reduced, but in principle still persists. Energy consumption increases accordingly, depending on vmax. This is where the intelligent FLP6000EOS Energy Optimizing Software comes into play. It determines, on a case-by-case basis, whether maximum velocity is required to achieve optimum performance. If maximum velocity is not required, it automatically adjusts the speed - significantly reducing facility wear.

FLP6000EOS Advantages:

Reduces the amperage by up to 30%
Optimized energy consumption
Saves energy by reducing braking and acceleration ramps
Reduces mechanical wear and power consumption
Extends the facility's life-span
Easy to operate; no programming skills required
No additional setup software required

Examples for Increased Motion Path Efficiency

Example 1: Axis Speed Optimization

A stacker crane with 2 axes used to be positioned conventionally by two separately controlled drives (e.g. with the Trimble ICS5000). Positioning took place using predefined static speed values. Now, PSI Technics' FLP6000EOS automatically controls multiple axes in dynamic mode and adjusts the vehicle's speed to the match the actual positioning time. The FLP6000EOS precisely determines the positioning time based on the automatically calculated motion path.

Diagram 1: Positioning a vehicle with two axes
The system receives a travel command (X 20 m, Y 10 m). With a conventional travel profile (green line), both axes are positioned at the target location with maximum speed. The vehicle's y axis has a shorter travel distance and reaches the target position faster. Maximum velocity, however, won’t render any benefits, since the x axis has to travel a longer way and is going to reach the target destination later.

Using the optimized travel profile (blue line), the speed of the vehicle's y axis is adjusted to match the speed of the x axis. This way, both axes reach the target position at the same time.

Diagram 2: Conventional travel profile v(t) for both axes
Both axes travel at maximum speed, but due to the different travel distances, they reach the destination at different times.

Diagram 3: Optimized travel profile v(t) for both axes
After the FLP6000EOS calculates and optimizes the travel profile, the y axis' final speed can be reduced. The speed remains significantly below vmax and the y and x axes arrive at the target position simultaneously.

Example 2: Optimization of Throughput Time

Necessity, not maximum velocity, is the decisive factor for determining positioning speed. Positioning time is determined by the throughput time of the entire warehouse. Against this backdrop, maximum velocity can amount to costly "luxury", when the warehouse throughput time is subject to its own cycles and can’t benefit from this "head start". A more moderate approach still ensures an adequate velocity and is considerably more efficient from a savings point of view.

By analyzing either the already traveled distances or by calculating the average warehouse throughput time supplied by the warehouse process computer, the FLP6000EOS software achieves maximum efficiency. Users can enter an expected capacity utilization in the FLP6000EOS software. The software then uses this value as a basis for matching the travel speed to the actual warehouse throughput conditions.

CONCLUSION

The modular FLP6000EOS add-on considerably increases positioning efficiency, saves energy and reduces maintenance costs to increase the life-span of industrial facilities and ensure a fast return on investment.