BySort: Fabricating efficiency and material handling automation

Blog Eliminating Fabricating Bottlenecks with Material Handling Automation

One way to increase efficiency in laser cutting systems is to eliminate bottlenecks by incorporating material handling automation.

Laser cutting systems without material handling automation display the most variability in their production time during the loading and unloading process.

If you analyze the waiting or idle times data from the laser cutting machine, the waiting times are notoriously evident. This is due to either a lack of raw materials having been supplied to the machine or a lack of unloading cut parts before the laser cutting machine has finished processing the previously cut sheet. Avoiding material bottlenecks at this point in the fabricating process is critical to maintaining efficient downstream operations and reducing overall process times.

Automating to supply raw materials

As the cutting programs are released to the laser cutting machine for processing, how does your system react to this request? Does someone now retrieve the raw material from a material storage area using a forklift and bring it to the machine? How much time is accumulated performing this action for each and every material changeover?

If you are in a high-mix environment with many daily changeovers, this is a critical bottleneck. With an automated material storage system, multiple materials types and thicknesses can be supplied across multiple machines. With an automated material storage system, as programs are released to the laser cutting machine, the communications to the material storage system are achieved automatically. Once the first order of raw material is delivered to the laser cutter, the subsequent material order can already be delivered during the processing of the last sheet of the first order. This way, the raw material is moving to the machine while the machine is still processing.

Automating the material loading process

Once the laser cutting machine is presented with the raw material stack, the next step is to automate the raw material loading. If automated, the loading of the material becomes part of the automatic sequencing tied to the machine’s request for material. No more waiting from sheet to sheet and from order to order. Sheets are loaded onto the secondary shuttle table while the laser cutter is cutting on the primary table. But there is yet another important sequence that must occur in between the raw materials being loaded. If the cut material is not unloaded in a timely manner then waiting times will accumulate.

Automating the material unloading and parts sorting process

Automating the material unloading process is extremely critical as the other processes of loading and cutting are dependently tied to this very important sequence. A bottleneck is created without the unloading taking place in a timely manner. At this point, there are two ways to address the unload automation process. One method is to unload the entire cut sheet with parts using an unload fork system. Another, and more efficient method, is to already have the parts unloaded and stacked using an automated sorting system for the parts and a fork system to remove the material skeleton when completed. The automated parts sorting system sorts parts from the cut sheet material based on the order it belongs to. It also organizes ‘like’ parts in a neat stack for the next fabricating process. This greatly reduces process times in sorting the parts manually from the cut sheet and reduces errors in stacking similar part revisions.

Reducing bottlenecks in the fabricating value chain

Reducing material handling bottlenecks by incorporating material automation and part sorting greatly increases downstream efficiencies and overall throughput. In this blog, we have identified the most common areas for process variability and bottlenecks in the initial fabricating value chain due to unplanned waiting times. If these variabilities exist, they are probably not being accurately accounted for in job quotes; are affecting efficiency, throughput, and profit, and more than likely affecting your promised customer delivery dates.