How Collaborative is Your Application? – A General Approach
By Alberto Moel (Vice President Strategy and Partnerships)
Welcome back, dear reader, to one more installment of the Veo Robotics blog. Now that Veo FreeMove® is certified to ISO 13849 PLd Cat 3, our blog is shifting to provide practical tools for customers and systems integrators on how to implement Speed and Separation Monitoring (SSM) under the ISO 10218 and ISO/TS 15066 standards.
In our musings to date, we have given a number of examples of effective human-robot collaboration using Veo FreeMove in palletizing, machine tending, and in-line parts presentation for assembly. We also estimated the value gain against alternatives such as fully-automated or fully-manual workcells, Power and Force Limited (PFL) robots, and workcells being safeguarded by the current “state of the art” methods with light curtains or safety scanners. We have found collaborative applications can improve cycle time, reduce fault recovery times, and permit quicker and more flexible workcell reconfiguration relative to alternatives.
Although we have quantified how “collaborative” a robot can be and whether to use a PFL robot or SSM for our collaborative application, we have not really discussed how “collaborative” an application is (or can be made). In today’s post we step back and consider a general approach that could be helpful when incorporating human-robot collaboration in manufacturing.
Our analysis hinges on the fact that workcell operations have a cycle time and the level of human interaction is dependent on the application, its design, and operation. We conclude that the shorter the cycle time and the more frequent the required human interaction, the more collaborative the application.
Although in principle most human interactions could be “automated away” (reducing the level of collaboration), it may not be economically or technically feasible to do so while retaining manufacturing flexibility. In other words, there is no ROI to the automation effort – it costs too much and takes away the flexibility that humans provide. In that case, retaining human input into the process through human-robot collaboration is very frequently the best approach.
In our next post, we will show how the economic benefits of Veo FreeMove increase with the application’s degree of collaboration; in other words, the more you need humans in your process, the more Veo FreeMove can improve the economics of your application.
The Cycle Time Continuum
First, note that pretty much all manufacturing workcells (collaborative or not) are repetitively performing some discrete manufacturing step (assembly, weld, paint, package, palletize, you name it) on a sequence of workpieces that are “fed” to the workcell, “worked on” by an amount of time (the cycle time[1]), and the process repeated with the next workpiece.[2] Some examples:
A workcell consisting of a robot feeding metal parts to a CNC for deburring. Every deburring step takes, say, 10 seconds and the robot is feeding the parts to be deburred from a bin holding 20 input parts and putting the finished parts on a bin holding 20 output parts. Then, roughly at a cycle time of 200 seconds, there needs to be a Machine Tending operation where a bin with unprocessed parts needs to be brought to the robot and similarly a bin with processed parts needs to be removed from the workcell.
If the CNC step were, instead, a machining step and it took 30 seconds with each part fed individually (with or without a robot), we would need an Operator Load Station to feed parts directly to the machine at a cycle time of 30 seconds.
Or, perhaps a Palletizer (or Depalletizer) where a pallet is assembled (or disassembled) every 4 minutes (240 seconds) and full (or empty) pallets need to be brought in and out of the palletizer.
Or, consider a Parts Presentation application, where the workpiece is “presented” to a human or an automated system for processing: cabling, fastening, quality assurance, parts attachment, etc. This presentation can occur multiple times in the same cycle, as in this video of Veo Robotics CTO Clara Vu performing three assembly and QA steps on an appliance.
All these applications run the gamut of cycle times from a few seconds (for example, single-part machine tending) to minutes, as would be the case of the palletizer or the multi-step processing of a complex workpiece such as a large appliance or an automobile.
The Human Interaction Frequency Metric
The design and operation of the manufacturing application will determine how and how often the human and robot will collaborate. At one extreme, there is no collaboration, and the application runs unattended[3] throughout the operating cycle. In that case, a simple and sturdy cage with a lockout/tagout mechanism is sufficient to isolate humans from the robots (although we note that FreeMove could be useful here, substantially reducing downtime during fault recovery of a fully-automated workcell).
At the next level, it could be that the application requires the simplest form of “collaboration” where the robot and human are in proximity to each other but do not really interact with each other during robot operation. In that case, a PFL robot, a light curtain, or 2D scanner could be sufficient for peak cycle time performance.
The applications discussed above all fall in the “definitely collaborative” category; the only question is how often human interaction occurs. In the case of an operator load station with a human feeding parts one by one to a robot or a machine, the interaction is once per cycle, which can be every few seconds. For a palletizer, it is twice per cycle—once to bring in an empty pallet and once to take out a full pallet. But the cycle is much longer, perhaps in the range of minutes.[4] And in the case of parts presentation, this interaction could be multiple times per cycle. The opposite end of the continuum is also possible where interaction occurs every few cycles, for example in the case of a machine tending application where many output bins can be handled automatically before human intervention is required.
We can take these applications, and others not discussed, and the two metrics—cycle time and human interaction frequency—and plot them on a graph, as in Figure 1.
Figure 1. Classification of collaborative applications
A simple conclusion is that the more human interactions across time, the more “collaborative” the application. This happens as cycle time gets shorter and the interactions per cycle increase. Note that the total cycle time of the process not only includes the time the robot or machine is processing a workpiece, but also the time it takes for the human interaction plus the time it takes to slow down or stop the machine during human interaction.
If we can optimize this interaction time, we would improve the efficiency of human-robot collaboration, lowering production costs and enhancing manufacturing economics. In our next blog post we will quantify how Veo FreeMove can provide this efficiency gain, so stay tuned!
[1] To be clear, we are defining cycle time as the time it takes to complete a single process step, not the time to complete the whole manufacturing process (which is more precisely the inverse of the throughput, or production units per unit time).
[2] Which in principle can be different from the previous workpieces, and the process performed on it also varies. Although in practice these differences are not going to be extreme; a cell welding steel parts is not going to be the same cell fastening plastic parts to each other.
[3] Except possibly for routine maintenance, unexpected repairs, or fault recovery during operation.
[4] In reality, the interaction is likely to be more than twice per cycle as, on occasion, there could be a dropped box or misaligned box that requires human intervention to correct.