FreeMove in a Collaborative Palletizing Case Study—Part 3

By Alberto Moel, Vice President Strategy and Partnerships, Veo Robotics

Welcome, dear reader, to our third (and last!) blog post in this series on the benefits of the Veo FreeMoveTM system in a collaborative palletizing application.

In collaboration with Advanced Robotics for Manufacturing, we have developed detailed models of four different palletizing solutions: a fully manual palletizer, a fully robotic one, an approach using Power and Force Limited (PFL) robots, and one using the Veo FreeMoveTM system. For a comparison of the capital expenditures and commissioning metrics of the different palletizing solutions, see Part 1 of our case study. For a discussion around fault recovery and associated cost-savings and throughput, see Part 2. Once you’re all caught up, you’ll understand that the Veo FreeMoveTM palletizing solution far outperforms the other options, reducing costs of all kinds while improving productivity.

In this final part of the case study, we’ll dig a bit deeper into how the Veo FreeMoveTM solution’s quicker and lower cost design, development, and implementation has benefits when it comes to reconfiguring (i.e., recommissioning) the palletizing workcell.

Recommissioning, you say? What does that mean?

The analyses presented in Parts 1 and 2 assume that we’re palletizing the same products throughout the life of the palletizer (which we peg at 10 years). In other words, our models palletize the same size and number of packages in the same geometric configuration over and over, with no variation whatsoever.

But this is unrealistic. Shorter product cycles and increasing SKU proliferation (a topic for a future blog post) mean that the products coming off the end of the line are likely to change on a fairly frequent basis. So though we might start out with pallets that fit 48 cases each containing four bottles of liquid detergent, in a few months, we might need to accommodate a completely different product, say, powder detergent containers that come six to a case. And if the cases are a different shape or size, or if we need to use a larger or smaller pallet, what then?

The lifetime of a particular palletizing application may change across the lifetime of the palletizing workcell, which we still assume is 10 years. This means that, every once in a while (maybe a few times a year), the palletizer is stopped and recommissioned for a different application. Recommissioning involves some non-recurring engineering expenses and downtime, which have an impact on the palletizer economics. The extent of that impact depends on the following:

  • How often the palletizer needs to be reconfigured and recommissioned. Never? Once every two years? Once every two months?
  • How long the shutdown and reconfiguration process takes. What kinds of new fixtures and programming are required? Will it take a day or two, or is the palletizer out of commission for a longer period of time, like a month?
  • How much it costs to recommission the palletizer. What non-recurring engineering expenses are needed to upgrade and reconfigure the workcell? What are the new fixturing and programming costs?

So, number of recommissionings per year, downtime caused by recommissionings, and non-recurring engineering expenses per recommissioning are key factors that will inform our choice of palletizing solution.

This is a complicated model and we could quickly fall off the conveyor, so let’s make some simplifying assumptions that will allow us to more or less quantify the value of speed and lower costs in reconfiguration:

  • Our analysis must help us decide between the fully automated, fully manual, and Veo FreeMoveTM palletizer solutions. The PFL solution just doesn’t stack up (revisit Parts 1 and 2 of the case study for context), so we’ll leave it out.
  • All of the original capital investment in robots, fixtures, and safety systems can be fully utilized in the recommissioned workcell. In other words, we’re reusing everything that has already been deployed and that has not maxed-out its useful life of 10 years.
  • The non-recurring engineering expense (NRE) for the reconfiguration is amortized over the life of the reconfigured workcell and affects per-pallet costs. For example, if the palletizer gets reconfigured twice a year, those additional costs are amortized over six months. For our purposes, we will assume that it costs $35,000 to reconfigure the fully automated palletizer, and $10,000 to reconfigure the Veo FreeMoveTM palletizer, as one would expect due to the flexibility embedded in the Veo solution. These numbers are illustrative estimates based on the time and complexity to reconfigure and recommission the solutions.
  • The time it takes to complete the recommissioning is also dependent upon each solution’s inherent flexibility. The fully automated solution must be reprogrammed to handle a new series of tasks, and may have to be fitted with additional fixturing, which may take over three weeks (let’s estimate 24 days). The Veo solution, on the other hand, uses a combination of human workers and robots and requires less new fixturing and reprogramming. If we assume the human workers are able to adapt to the procedural changes on the fly, we only have to account for some reprogramming of the palletizing robot arm, which could take a few days (let’s say five). Using this same logic, we can assume that the manual palletizer can be reconfigured instantly and costlessly.
  • The throughput of the reconfigured palletizer, measured by number of pallets per year and cycle time, remains constant. In other words, although the amount, shape, and size of the boxes to be palletized may change, the time it takes to build a pallet is the same before and after reconfiguration.
  • All the robotic palletizer solutions are able to work faultlessly across the cycle. Though it requires a stretch of the imagination, this assumption allows us to isolate the economic value of recommissioning from the benefits of flexible fault recovery. The fault recovery analysis featured in Part 2 is additive to the value calculations presented here.
Figure 1. Operating statistics for faultless palletizer operation.

Figure 1. Operating statistics for faultless palletizer operation.

Enough preambling, let’s get to some numbers. Figure 1 shows some baseline statistics for the three palletizer solutions under the assumptions above. If the palletizers never fail, using the Veo system provides cost savings over alternatives, while maintaining the highest performance, reducing the per-pallet cost to $0.65, and meeting the high throughput of the fully automated solution.

What happens to these operating statistics as the palletizing workcell gets reconfigured and recommissioned? We would expect the total cost per pallet to rise, and the total number of pallets per year to decrease.

Let’s start by analyzing the workcell throughput (in pallets per year) as a function of the number of recommissionings per year and length of downtime. Assuming the Veo solution can be reconfigured in five days and the fully automated solution in 24 days, we can see that the time savings of the Veo solution allow the workcell to maintain pallet throughput even as it gets reconfigured more frequently. The throughput of the fully automated solution takes a steep dive as reconfigurations increase, which translates to big losses in productivity.

Figure 2. Pallet throughput as a function of recommissionings per year.

Figure 2. Pallet throughput as a function of recommissionings per year.

Figure 3. Pallet throughput as a function of days downtime.

Figure 3. Pallet throughput as a function of days downtime.

Obviously, the longer the downtime the lower the pallet throughput, and the more changes per year the stronger the impact of that downtime. If we are updating the palletizer six or more times a year and each update takes a few weeks to reconfigure, at some point we are producing so few pallets per year that it becomes more economical to switch over to the fully manual solution, which has no downtime. Because of the flexibility of the Veo system, the Veo FreeMoveTM-enabled palletizer has a much shorter recommissioning downtime and as the number of changes per year increases, its value becomes more and more apparent.

Figure 4. Cost per pallet as a function of NRE and days downtime.

Figure 4. Cost per pallet as a function of NRE and days downtime.

Let’s introduce one more variable into the model, the cost of recommissioning, estimated as a non-recurring engineering expense. We should expect higher costs, more downtime, and more frequent updates to the workcell to impact per-pallet economics. The modeling possibilities are, of course, infinite, but let’s focus on a typical example—recommissioning once a quarter. Figure 4 shows the cost per pallet for a palletizer that is reconfigured and recommissioned four times a year. While the Veo solution’s $10,000 NRE per quarter increases per-pallet costs from $0.65 to $1.10, the fully automated palletizer with $35,000 NRE per quarter suffers a much more pronounced rise in costs, from $0.81 to $2.38.

Although we have made some assumptions about the Veo solution having shorter downtime, it is illustrative to see the impact of increasing downtime on the cost per pallet. As the days of downtime increase, the fully automated palletizer looks less and less attractive. If the recommissioning time is sufficiently high (about three weeks in the model shown in Figure 4), we’re better off using the manual palletizer, with its terrible throughput (but high flexibility). The Veo FreeMoveTM palletizer remains economic even if downtime is material.

So, what do we take away from this analysis? The inherent flexibility of the Veo palletizer workcell has economic value. The use of a flexible system such as Veo FreeMoveTM extends the economic range of automation, capturing the benefits of faster cycle time and throughput while reducing the impact of the cost of automation. All things considered, in a real palletizing workcell where the application is likely to change periodically in response to consumer demands, the Veo FreeMoveTM solution takes the cake.