sliding shoe sortation

Top 7 Considerations for Sliding Shoe Sortation

The modern sliding shoe sorter was patented in 1966 and has since become a staple in the industry. Before 1966, a few attempts were made to devise an item sortation system that would afford retail stores the ability to sort automatically. But the sortation mechanisms detailed in the older patents are positively unwieldy.

The 1966 invention of the shoe sorter greatly reduced both mechanical complexity and cost by implementing the divert switch, shoes, and slats. These types of optimizations are usually signs that an invention will go on to disrupt an industry. The 1966 rendition of the shoe sorter went on to do just that! And its design has remained incredibly stable for nearly 60 years. Even with a stable design, there still has been much for engineers to work on in the shoe sorter application. Below are the design criteria around which the original 1966 sorter was originally conceived and examples of ways in which engineers continue to optimize their shoe sorters today.

Sliding Shoe Sortation Considerations

1. Throughput

Belt speed is the first and most obvious parameter to optimize around. Ideally, we want those packages to sail! A faster belt speed equals more packages per unit time and higher throughput. However, this can be a problem for lighter packages as they can, quite literally, take flight. A sorter can also achieve higher throughput by minimizing the gaps between packages. This is done by minimizing pin pitch.  This, too, can pose challenges as now the system might miss diverting a package.  It’s important to note that we’re not maximizing belt speed or minimizing package gap; but instead, we’re maximizing throughput – and accuracy.

Today conveyor speeds are typically capped at around 700fpm. Why? The primary driver is the speed of the divert switch. The divert switch is usually a rotary solenoid that needs to actuate around sub 20ms (or sub 10ms in the 800fpm world). It also needs to return at a comparable speed. But, when the switch flag turns that quickly, it encounters problems controlling the momentum. It’s no problem to actuate the solenoid more quickly, just apply more power. But, when it slams into the stop on the other end, it will obey the laws of physics and undergo elastic collision with its stop and bounce back. This potentially causes mis-sorting on the next package or shortens the life of the switch. Actuation/return speed is the primary parameter controlling both pin pitch and belt speed. Therefore, to optimize throughput at 800fpm, the switch must reliably flip between every other pin at 3” spacing.

2. Energy

A solenoid can switch/spin as fast as you want, just boost the power. But, as we all know, that power comes at a price. First, there’s the thermal debt paid to move all things. More power means more heat. An outlet is needed for that heat or a means to apply power more accurately.  Second, more energy means higher infrastructure costs. Poly-phase 480V isn’t cheap. Moreover, the MH&S industry is shifting to 24V DC as a standard, largely to minimize infrastructure costs and improve safety. The way to control these factors is through the precise and controlled application of power by using PWM.

3. Reliability

As everyone in the sortation industry knows, downtime is costly.  As important as maximizing throughput to optimize value per unit time is, minimizing downtime is also of paramount importance. This is usually done by inventorying spare parts and designing sliding shoe sortation devices that can be rapidly repaired. The switches, shoes, conveyor slats, and more need to be enabled for quick replacement.

While quick repairs reduce downtime, they do not predict it.  With the growth of IoT, critical components can now indicate changes in the system and send an alert that it will fail before it actually fails. This increases reliability by eliminating random failures and enabling predictive maintenance.

4. Life

While predictive maintenance solves random failures in switches and sensors, it is still important to consider the rated life of a piece of hardware. The maximum life of the unit is a key point of differentiation, but for the person installing the unit in a system, it’s more important to know with 95% confidence that any particular unit will fail after a known number of cycles. Life is more than the maximum life of a unit.  It is also the predictable failure modes at well-established points in a component’s life cycle.

5. Repeatability

“All things fall apart,” seems to be a theme for the last two bullets. Repeatability is no different. Pneumatics, known for high irregularity and low repeatability, are impacted by environmental variables more than electronics. Combine that with the natural wear and tear that all things undergo, and it’s a recipe for low repeatability. It is difficult to control the set of input parameters well enough to repeatably cause an identical output. This is a barrier for the industry as it moves to higher throughputs. The solution has come in the form of devices that guarantee high repeatability by dynamically adjusting input parameters to generate identical outputs. This is much easier to accomplish with electrons than with compressed air.

6. Safety

Maintenance protocols require lock-out tag-out (LOTO) procedures. The simpler your system is to isolate from power sources, the easier it is to do LOTO on, and the faster it is to maintain. Pneumatics are troublesome here again, as LOTO procedures sometimes require that all sources of stored energy (steam, hydraulics, etc) be drained, adding time and cost to the process.

7. System Complexity

Reducing system complexity is a bit of a chicken-egg problem. It often requires complicated reasoning or control to reduce overall system complexity, but there are a few surefire places to start. For instance, anywhere there is a sensor and an actuator, the sensor can be removed, and the actuator can do both jobs. Complicated PLC control can be moved to decentralized onboard control. Both approaches prefer a distributed or decentralized control scheme. Preferring a centralized patron/client approach to a distributed ecosystem allows for simple control schemes to handle complicated behavior more efficiently.

The Takeaway

While the general mechanism of the shoe sorter has remained relatively unchanged over the past 60+ years, the problem of article sortation has continued to accumulate complexities in the forms of increasing throughputs, safety regulations, greater expectations for product life, higher requirements for accuracy, and everything in between. Innovation in the shoe sorter industry will look, as it did in the 60s, like a reduction in complexity or a reduction in cost. Industry 4.0, IoT, and better (often more decentralized) control schemes will look like increasing complexity. But this is not necessarily the case…

Imagine a warehouse with no operators where every component communicates with and adapts to the behaviors of its neighbors. While it may look more complex at the component level, the system level complexity is far reduced, at least as far as the human charged with overseeing the warehouse. In fact, that complexity could be reduced to such a degree that warehousing becomes automatic. This is the not-so-distant future. Partner with your suppliers to see how they can aid you in making this a reality.

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