Picking Solutions: How Complex Must Your System Be?

Bin-picking, random picking, pick and place, pick and drop, palletization, depalletization—these are all part of the same project. You want a fully automated process that grabs the desired sample from one position and moves it somewhere else. Before you choose the right solution for your project, you should think about how the objects are arranged. There are three picking solutions: structured, semi-structured, and random.

As you can imagine, the basic differences between these solutions are in their complexity and their approach. The distribution and arrangement of the samples to be picked will set the requirements for a solution. Let’s have a look at the options:

Structured picking

From a technical point of view, this is the easiest type of picking application. Samples are well organized and very often in a single layer. Arranging the pieces in a highly organized way requires high-level preparation of the samples and more storage space to hold the pieces individually. Because the samples are in a single layer or are layered at a defined height, a traditional 2-dimensional camera is more than sufficient. There are even cases where the vision system isn’t necessary at all and can be replaced by a smart sensor or another type of sensor. Typical robot systems use SCARA or Delta models, which ensure maximum speed and a short cycle time.

Semi-structured picking

Greater flexibility in robotization is necessary since semi-structured bin picking requires some predictability in sample placement. A six-axis robot is used in most cases, and the demands on its grippers are more complex. However, it depends on the gripping requirements of the samples themselves. It is rarely sufficient to use a classic 2D area scan camera, and a 3D camera is required instead. Many picking applications also require a vision inspection step, which burdens the system and slows down the entire cycle time.

Random picking

Samples are randomly loaded in a carrier or pallet. On the one hand, this requires minimal preparation of samples for picking, but on the other hand, it significantly increases the demands on the process that will make a 3D vision system a requirement. You need to consider that there are very often collisions between selected samples. This is a factor not only when looking for the right gripper but also for the approach of the whole picking process.

Compared to structured picking, the cycle time is extended due to scanning evaluation, robot trajectory, and mounting accuracy. Some applications require the deployment of two picking stations to meet the required cycle time. It is often necessary to limit the gripping points used by the robot, which increases the demands on 3D image quality, grippers, and robot track guidance planning and can also require an intermediate step to place the same in the exact position needed for gripping.

In the end, the complexity of the picking solution is set primarily by the way the samples are arranged. The less structured their arrangement, the more complicated the system must be to meet the project’s demands. By considering how samples are organized before they are picked, as well as the picking process, you can design an overall process that meets your requirements the best.

Automation is “Rolling Out” in the Tire Industry

Automation is everywhere in a tire plant – from the old manual plants and mid-hybrid automated plants to the newest plants with the latest automation technology all over the world.

Industry challenges

Some tire industry automation challenges are opportunities for automation suppliers and machine builders. These can vary from retrofitting old machines and designing new machines to including smarter components to bring their production into the IIoT.

Plants want to save CapX dollars on new machines, so they are looking to upgrade old ones. Tire plants are learning from the past. They are limited by their older technology, but it has been hard to upgrade and integrate new technology, so there are long-term needs for adding flexible automation on machines. This requires new processes and recommissioning machines quickly. A good example of this is the addition of a vision system to improve quality inspections.

More automation is also needed due to a lack of skilled labor in the industry combined with the desire for higher throughout. The addition of robots on the line can aid with this. Plants can also simplify their wiring by migrating away from control panel i/o/analog to an IP67 network and IO-Link master and hubs.

The use of IO-Link also allows for more continuous condition monitoring. There is an increased need for quality inspections and process improvements. Plants are collecting more data and learning how to use it and analytics (Industry 4.0, IIoT) to achieve operational excellence. Plants need more technology that supports preventive and predictive failure solutions.

Additionally, there are automation needs on new machinery as tire designs are in an evolutional growth/change period – in the electric vehicle (EV) market, for example, where rapid change is happening across all vehicle manufacturing. Smart tires are being designed using RFID and sensors embedded in the tire ply.

Successfully matching up automation products to meet plant needs first requires understanding the plant’s main processes, each with millions of dollars of automation needs.

How tires are made

    1. Raw materials logistics – raw materials are transported to the mixing and extrusion areas for processing.
    2. Mixing and extrusions – up to 30 ingredients are mixed together for a rubber blend tire.
    3. Tire components – extruded rubber ply is measured and cut to size to meet the needs of the specific tire and then loaded onto reels feeding the tire building machines.
    4. Tire build machines – tires are built in stages from the inside out. They are crated without tread and transferred to the curing press machines.
    5. Tire curing press machines – here, the “green” tires are vulcanized, a chemical process that makes the tire more durable. Tire parts are then compressed together into the final shape and tread pattern.
    6. Inspection and test machines – tires are quality tested and undergo visual, balance, force, and X-ray inspections.
    7. Logistics material handling, conveyor, ASRS, AGV – finished tires are taken to the warehouse for sorting and shipping.

In the past, not many people outside the tire industry understood the complexity and automation needs of these high volume, high quality, highly technical plants. Tires are so valuable to the safety of people using them that manufacturers must be held to the highest standards of quality. Automation and data collection help ensure this.

In the meantime, check out these futuristic tires and imagine all the automation to manufacture them.