Can KPIs help to prove the ROI of your robotic cell? You bet!
Your first robot is an important investment. It can open doors to future automation projects in the business… but only if you can prove that the investment has been worth it. If you cannot prove the robot has recovered its costs, the company's commitment to robotics will evaporate quicker than a water spill on a hot motor.
But, how do you prove that a robot has been a good investment?
We previously explained how to calculate the Return on Investment (ROI) for a planned robot purchase. This calculation is useful at the early stages of robot deployment, but it only provides an estimation. It doesn't prove that this ROI has been achieved.
To achieve a more accurate ROI of the robot you need analytics. This involves using metrics improve the ROI calculation using real operational data. It is a more accurate method but it can also take more time if you don't measure those metrics properly. Dedicated analytics software can speed up the process significantly.
Here's how to decide which analytics data you will need, how to gather the data effectively and how to analyze it to prove the ROI of your robot.
How to Choose Analytics
Not all metrics are born equal. There are hundreds, if not thousands, of metrics you could use to measure the effectiveness of your business and robotic system, but only some of them are actually helpful for calculating ROI. You should use the Key Performance Indicators (KPIs) which are directly linked to the performance of the robot cell.
Interesting vs Useful Metrics
Some metrics seem interesting but, in fact, are useless for measuring robot ROI. Measuring the wrong metric can be more damaging than measuring no metrics at all, because it can give you an inaccurate picture of the performance.
For example, let's say you decide to choose the metric "productivity of each cell" — you compare the robot's productivity with the productivity of each of the other cells to see if it is "keeping up." Although this might seem to be interesting information, it's likely to be useless because different cells will have inherently different productivity levels. In this case, it would be much more useful to compare the robot productivity with the previous manual productivity before you automated the cell.
But, how do you choose the most useful metrics?
Picking the Right KPIs
Many of the KPIs we often use in business are not directly suited to measuring robots. Until recently, there wasn't much information available about how to apply KPIs to collaborative robots. To solve this, we've published a new eBook called "Top 5 KPIs: How to Measure and Improve the Performance of Collaborative Robots." It explains how KPIs apply to robots, introduces the most useful metrics and explains how to measure them.
How the Top 5 KPIs Link to ROI
The Top 5 KPIs listed in the eBook are listed below, along with examples of how they could be linked to the ROI calculations. How you use them specifically will depend on the configuration of your cell.
- Cycle Time — This measures the time it takes for the robot to complete one sequence. It can be used to compare the robot's operation with the previous manual operation. For example, if the robot completes the operation 15% quicker than the manual process, this will soon add up to a lot of time saved. This information could be incorporated into the ROI calculation as part of the total robot working time.
- Cycles Completed — This measures the number of sequences completed with the robot. In many cases, it can indicate how many operations have been successful. You can use it to calculate the yield of the process, which could be used in the ROI calculations when calculating the scrap costs.
- Utilization — This measures the percentage of time the robot is used vs the time it sits idle. It can be used to quickly and accurately calculate the robot's downtime for the ROI.
- Efficiency — This indicates how efficiently the robot has been programmed. This can be very useful if your ROI is longer than expected. For example, if you have a ROI of 3 years, but your Efficiency is only 20%, you have strong evidence that improving the robot programming would improve the ROI.
- Wait Time — This indicates the amount of time which the robot is waiting for other processes to finish. High wait times may indicate times where the ROI of the robot can be improved by optimizing the processes which interact with it.
These five KPIs have been found to directly reflect the performance of collaborative robots, so they are a good candidate for making the robot's ROI more accurate.
Record the Data
When you have picked your KPIs, you then need to measure them. There are a few ways you can do this, but the two ends of the spectrum are:
- Infrequent, manual logging — This is where a member of your team manually writes down the metric periodically, either on a piece of paper or using an app. This data is then entered and analyzed using software tools, like a spreadsheet or MES software. It is usually inaccurate and time consuming.
- Automatic logging with cobot-monitoring software — This is where the robot automatically sends the metric data to a centralized software system, which allows you to view and analyze the data in real time. Insights is an example of such a system, which is specially designed for use with collaborative robots. This method is accurate and instantaneous.
The key to recording your KPIs is consistency. Measure accurately and as often as possible. For ROI calculations, it makes most sense to use long-term KPI data, e.g. over the period of a month rather than over, say, an hour. This is very easy in Insights, which allows you to easily change the time window to view the metrics for an hour, a day, a week or a month.
Finally, use your logged KPIs to calculate the ROI for the robotic cell. Some of the data may still be an approximation, but your metrics will help to provide a more accurate value, as well as justify and clarify the effect of the robot on the business.
Download the Lean Robotics ROI Calculator to work out the return on your robot cell.