It is generally essential for the top line of your business to grow annually. Still, you must also ensure the bottom line, which helps in funding that growth, is equally healthy. This is especially important if you own a manufacturing company and need to be efficient in your production process.
One incredibly effective way to ensure the production line is running at its optimal performance is to strike the right balance of manufacturing KPIs in place. Moreover, with the rise and evolution of automation and robotics in the manufacturing sector, manufacturers must focus on automation KPIs to measure their company’s performance.
Some of them are leading indicator KPIs that provide valuable insights into forthcoming performance. In contrast, others are result-based KPIs that tell you how you’ve done. In this guide, we discuss how to pick the right KPIs for your manufacturing business and look at some of the top automation KPIs to track in your business .
Automation in the Manufacturing Sector
The manufacturing sector has been profoundly benefiting from automation and robotics, particularly from the use of cobots (collaborative robots) in factory settings. Unlike industrial robots that do all the work in place of human workers, cobots are primarily designed to collaborate with those workers and automate processes.
At present, an increasing number of manufacturers have started exploring how collaborative robots can transfigure their company’s operations by boosting efficiency. If you have been using robots and cobots for some time now, you may find yourself in either one of these situations:
- The robots are performing well but are not as productive as you predicted, and you do not know the reason why.
- You feel that you could boost the robot's productivity further, but you are unsure where to start.
- You do not have the time to solve all the issues in the process and optimize robots simultaneously.
- Your overall throughput isn’t that good, but you don’t know how to tell if the robots can help improve it.
Like every machine, cobots are most useful when you use them to their maximum potential. But, the problem is, how would you know if you’re using a robot/cobot to its optimum potential or not?
Well, there are automation KPIs (key performance indicators) for that, and you can use them to measure the performance of robots in your factory. You can then use the data you collect to enhance the performance of your robotic cell and the overall manufacturing line.
What are Manufacturing Metrics and KPIs?
You’re probably familiar with the idea of metrics and KPIs, which is short for Key Performance Indicators. Perhaps you already use some of these KPIs to monitor your manufacturing line’s performance.
A metric is basically any number your company might keep track of. Each metric has its own individual uses.
On the other hand, KPIs are metrics that enable you to determine the success of a process. They are ideally associated with your business objectives and provide valuable insights into your company’s performance as a whole.
A few metrics might be more beneficial for tracking the progress in your business than others. Still, all metrics should be able to provide you some kind of insights into what goes on in your business processes.
For instance, PM schedule compliance might not reveal much information about the company’s overall profitability. Still, it does give you some insight into how your maintenance processes are doing.
By keeping track of KPIs over time, you can assess which parts of the overall process work well and which parts couldn’t benefit from additional improvement.
For instance, a manufacturer aiming to achieve top customer satisfaction will most likely use customer satisfaction as a KPI for his business. However, other maintenance metrics, such as PMP, won’t be of much help here.
Altogether, there are hundreds of KPIs. However, the question is, “which KPIs are most essential for cabot automation?” The challenge for businesses is to choose only those key performance indicators that’ll help them improve their process and add value to their products. Picking too many KPIs can be worse than not picking any at all.
Tip: As a manufacturer, you might want to keep track of both metrics and KPIs. If your key performance indicators seem off, the more comprehensive metrics will provide additional insights into why it is so.
Strategic KPIs vs. Operational KPIs
Many KPIs are designed to assess a business’s performance at a broader management level. They’re known as Strategic KPIs and aren’t very useful for evaluating the performance of machines. To evaluate shop floor technology, you’ll need to use Operational KPIs, like machine uptime and downtime, overall equipment effectiveness (OEE), and product quality.
These will help you enhance the manufacturing process at a lower level. Both types of KPI are related to each other. Hence, you must be able to connect your Operational KPIs to your Strategic KPIs and broader goals.
For instance, if the goal of your business is to boost profits, return on capital may be an essential Strategic KPI, and machine uptime can be an appropriate KPI to opt for. However, if your objective is to boost customer satisfaction, product quality, or cycle time might be more important, based on your customers’ needs.
Most Important KPI Properties in Automation
The best automation KPIS have specific characteristics, which we will have a look at one by one:
Linked with other operational KPIs
The operations performed by the robot will affect other KPIs within the business, such as manufacturing cost per unit, time from order to shipment, and plant downtime. You must ensure the metrics used for the cobots have clear links to broader effects on the business.
Even though you must calculate your cobot’s return on investment (ROI), a metric like that will not tell you how to boost its operation.
Easy to measure
KPIs that are difficult to measure will not be measured at all. When picking KPIs for your business, ask yourself how much time it will take for you to collect the data. After this, you can consider whether you would be happy to spend that time gathering data when you are occupied elsewhere. If not, it is not considered a good KPI.
Cobots make it relatively simple to collect data since they can log it directly within their respective programs. It is generally a good idea to log your key performance indicators on a continuous basis, as you can then compare both short-term and long-term data. This also simplifies the process of quantifying the effect of minor changes on the robot’s performance.
Focused on one or more of the common losses
Many of the performance gains in cobots can be obtained by dealing with some common losses. The KPIs reflecting these losses will possibly point to techniques of enhancing performance.
Simple and straightforward
The best KPIs can be understood without additional training. Moreover, the simpler your KPIs are, the most beneficial they will be for everybody to optimize the manufacturing process.
Why Manufacturing Businesses Should Track Important Metrics and KPIs
Manufacturers that monitor their firms with KPIs and other metrics tend to be significantly better off than those that don’t. Many manufacturers have found it to be true, and after implementing it, have benefited from the following advantages:
More consistent product quality
A manufacturer who keeps track of the right metrics will be significantly better at identifying and eliminating the problems that hamper their products’ quality. This means higher production rates with significantly fewer product rejects.
Meet business objectives
When manufacturers keep track of their KPIs, they can successfully accomplish their business objectives, especially when the chosen indicators line up with those objectives. For example, a company that tracks product throughput will most likely enhance productivity by ensuring their equipment is able to operate nonstop without ever crashing or breaking down.
Improved maintenance practices
Certain maintenance practices are also enhanced when manufacturers track the right KPIs. Companies that track metrics such as the planned maintenance percentage (PMP) and mean time between failure (MTBF) tend to be more focused on preventative tasks compared to reactive ones.
Rather than hurrying to fix a problem once the system crashes, they will work more on preventing the breakdown from happening in the first place. Eventually, this streamlines a company’s maintenance costs and makes their facilities more durable and reliable.
How to Apply KPIs to Robotics
Indeed, you must be thinking about how these KPIs can be applied to automation and how robots fit in it. Are they just like any other equipment? Manufacturing machines are typically evaluated using the Overall Equipment Effectiveness (OEE) metric.
Manufacturers can use this metric for robots/cobots too. However, it doesn’t really indicate how to enhance the robot’s performance, nor does it provide sufficient information to help you improve your cobot setup. With OEE, you can only calculate efficiency for the paired cobot and CNC equipment setup.
In reality, you need a definite way to quantify the efficiency of the robot individually. To obtain the most from robots/cobots, you need to “zoom in” on how they’re performing. Hence, for this, you must pick some automation KPIs.
Top Automation KPIs to Track in your Business
The manufacturing industry has constantly been evolving ever since the industrial revolution. However, most of the key performance indicators that would’ve been applicable when Henry Ford began manufacturing cars are still the same ones that are applicable today.
The only distinguishing factor is that you can now track with higher accuracy and precision using specialized KPI dashboards. Having said that, here are the top automation KPIs to track in your business.
Throughput is one of the most fundamental operations key performance indicators for the manufacturing industry. It is used to measure the production rate of a line, machine, or plant over a specified period, i.e., how many units are produced on average. This allows to operations department to determine whether they’re capable of meeting production deadlines or not.
While cycle time is used for measuring the time it takes between 2 points, you must monitor throughput in real-time. This is because when throughput decreases, it typically indicates that there is some problem on the line. The throughput can be increased by:
- Calibrating the machines to run at an ideal cycle time.
- Eliminating downtime.
- Improving the maintenance of machines.
- Changing the tooling or raw materials required to produce the goods.
- Reducing the steps in a cycle or number of touches to minimize shortstops.
First Pass Yield
Many metrics used in the manufacturing business include the number of defects produced by a process, e.g., yield. The yield KPI is at the heart of production profitability and efficiency and is a primary performance and quality measure.
It is probably the most important KPI production measurement that measures the percentage of products manufactured to specifications without being scrapped or requiring any rework the first time through the manufacturing process.
Measuring the First Pass Yield (FPY) identifies which of the processes call for substantive rework, influencing total cycle times, affecting throughput, and giving you a target of a 100% yield in which there were no defective parts produced.
You can easily estimate the yield by identifying if a particular cycle was successful or not, i.e., without failures such as dropped or misplaced parts. However, there is no easy way for robots to detect automatically whether a particular part has physical defects unless they’ve been integrated with autonomous metrology sensors.
They typically rely on automatic or manual inspection processes to determine if a product has been manufactured to specification. If necessary, you can combine a robot with external metrology devices to measure the yield automatically.
Changeover time can represent many different operational procedures. However, it mainly indicates the amount of time it takes to load/unload, calibrate, retool, program a new job. It is most relevant when there is a switch from one task to another.
Some of the most common examples are changing staff during a shift change or changing products on an assembly line. When taken as an average, the changeover time KPI can help you determine which job parts and types might call for some minimization in setup time, where possible.
By tracking the changeover time, manufacturers can easily fine-tune their estimates, outline their total cycle times by part, and identify the need for better planning, greater operator training, and proactive preparation of required materials.
Downtime is the heartbeat of every manufacturer. People mainly relate downtime with a machine in need of repair. However, this metric is typically a combination of both scheduled and unscheduled downtime.
The operations department mainly uses this metric to determine when their assets require being replaced. When the facility has excessive downtime, everything moves downwards, and the company's overall health is at stake.
Having said that, tracking the machine downtime (amount of downtime or why downtime occurs) is crucial for comprehending the health of a facility and overseeing solutions to those problems. When you understand where and why downtime occurs, you can fix the issues and shift the maintenance percentage of a facility away from reactive and emergency maintenance.
This applies to scheduled downtime, too, as sometimes machines need to be put down on routine maintenance, which is essential to track.
You must be familiar with cycle time if you have experience in the manufacturing sector. It is one of the most prevalent metrics used at multiple levels of manufacturing businesses.
For instance, “Machine Cycle Time” measures a single machine’s processing time, whereas “Overall Cycle Time” measures how long it takes for a particular product to pass through the entire production process.
It basically represents the complete required to convert your raw materials into finished products, from one end of the line to the other. Traditionally, cycle time measures how long it takes, from when a product enters a process to when it is shipped.
For robots/cobots, it measures the duration of one robot sequence. Unlike its traditional definition, it means that it doesn’t really signify how many objects were processed since you may process several products per sequence.
- A short cycle time is optimal - Short cycle times are ideal as they indicate more products can be processed in a given period. The shorter the cycle time is, the more optimized your robot is.
- A long cycle time is undesirable - A long cycle time indicates fewer products can be processed in a given period. Even though some operations might genuinely take a long time, there are plenty of ways you can optimize them.
Cycle time can be deemed the most fundamental metric for boosting your cobot’s performance. When you push down the cycle time of each step, you’ll ultimately benefit from a reduced overall cycle time too.
Utilization is used for measuring how long robots are being used compared to how long they could theoretically be used. After all, a robot is only of help when it is actually being applied to tasks within the business. You'll not get a return on investment if it sits idly, gathering dust in a corner.
There are many ways to measure utilization in companies, with the most widely used methods coming from manufacturing. Some of these methods factor in efficiency, yield, and other properties. Still, most of these methods are not suitable for evaluating robots since they primarily depend on other processes within the business.
The most beneficial way of measuring robot utilization is to identify the percentage of time when running a program. This way, you can assume that a robot that is running a program is ultimately performing the task. While this doesn’t speak much about the robot’s efficiency at the task. It does ensure the robot isn’t sitting idle.
One thing that makes cobots unique is that they can easily be switched between tasks. Therefore, you may use the same robot for a packaging task and then move it to a polishing task, etc. It’s quick to launch a new program, and even if you just run each task for a few hours, you can still achieve high utilization of the robot.
Suffice to say, automation is vital for today’s KPI monitoring and reporting solutions. However, you must remember that the automation manufacturing metrics and KPIs you need to track in your business might differ from someone else’s.
Only choose, measure, and track those KPI manufacturing metrics that are significant to your own organization to obtain the best possible results.