At production sites, we are often told to increase the capacity utilization rate. Although this term is used often, its meaning is profound. In this blog, learn the definition and its relationship to non-defective product rate, the importance of overall equipment efficiency, and the seven major equipment losses experienced in manufacturing.
What does capacity utilization rate mean?
The capacity utilization rate is an index that “measures the percentage of an organization’s potential output that is actually being realized”, according to Investopedia. In other words, it shows how much production equipment during operations is being used for production. This information provides helpful insight into how well production is reaching its potential.
There are two types of equipment utilization rates: hourly utilization rate and performance utilization rate.
Hourly utilization rate
Hourly utilization rate is the time – from when a production facility is powered on – and the percentage of time that production is taking place. It’s calculated by subtracting downtime, or the time the production equipment is stopped, from the load time, or the time power is on, and then dividing that by the load time.
There are several causes of a decrease in operating rates, such as failure, setup/adjustment, tool change, and startup. Thankfully, in recent years, predictive maintenance capabilities, made possible by artificial intelligence (AI) using an Edge Computing platform, foresee potential failures and create efficient maintenance plans, shortening recovery time and reducing unplanned downtime.
Performance utilization rate
Performance utilization rate is the percentage of time equipment operates as it performs. When a production equipment experiences a malfunction, the performance utilization rate will decrease. It is calculated by multiplying the base cycle time, or the base unit time of production, by the processing quantity and the operating time. Alternatively, you can calculate the net uptime divided by the working time.
Occasionally, manufacturers find that a piece of machinery or production line stops operating for a short period of time. Although not for long, this delay can impact performance operation rates. Again, with predictive maintenance powered by AI and Edge Computing, companies can monitor and stay on top of this.
What is the non-defective product rate?
The non-defective product rate, or ratio, indicates how many undamaged products are available. This is calculated by subtracting the defective quantity from the total processed quantity and then diving that value by the processed quantity.
Manufacturing defects and manufacturing reworks often impact the non-defective product rate. Many think that with a rigorous final inspection, there will be an increase in the rate of good and undamaged products. But, because the rate of good products is based on the result of the production equipment, and not the inspection process, the rate of undamaged products may decrease if the processing quantity does not change. In some cases, there are defects lurking somewhere within the production process, impacting the rate of good products. Edge Computing platforms are frequently leveraged to monitor production equipment to prevent those manufacturing defects and reworks.
The term yield and yield can sometimes be confused with the non-defective product rate. Yield and yield is the ratio between the input material and the products produced from the input material. Non-defective product indicates the number of undamaged products.
What is overall equipment efficiency?
The final comprehensive evaluation of production lines and production equipment is referred to as overall equipment efficiency. To calculate, you must multiply the hourly utilization rate, the performance utilization rate, and the non-defective product rate.
The overall efficiency of production equipment can be improved and is an important indicator when evaluating the management level of the equipment. In many cases, the actual overall equipment efficiency is less than the expected overall equipment efficiency. There is not a lot known about the actual overall equipment efficiency or yield and yield for different factories and manufacturing plants, as this is often classified as top secret.
The results will also vary depending on what is being manufactured, the season, the workers, and more. When a factory production line has just started up, the overall equipment efficiency will be lower. When stable operations begin, the overall equipment efficiency is often maintained at a high value. It’s also important to note that as a production line nears its end of life, the actual overall equipment efficiency will likely be lower.
When designing the production line, production engineering departments are responsible for bringing the actual overall equipment efficiency as close as possible to the total equipment efficiency. Because of this, it is crucial to reduce the following seven equipment losses outlined below.
What are the 7 major equipment losses?
There are the seven losses that reduce the overall efficiency of production equipment, including failure, setup/adjustment, tool change, start-up, dry operation, moment stops, and defect/correction, some of which are discussed above.
Failure when it comes to equipment losses is straight-forward. It is the failure of the equipment. When equipment fails, production cannot be done in time, which then impacts the hourly utilization rate. Utilizing Edge Computing to perform predictive maintenance can help mitigate failures and speed up recovery, as well as predicting failures and issuing alarms based on data discrepancies. As maintenance plans can be put in place at this prediction stage, recovery time is often shortened.
Read More: Preventive Maintenance, Predictive Maintenance, and Edge Computing
Setup and adjustment
Setup and adjustment refer to the time it takes to set up equipment in the workplace as well as the dimensioning during processing. Some manufacturers are leveraging robots to shorten the time it takes to set up. For example, for companies that require the setup and adjustment of very large and heavy workpieces, or even very small workpieces, robots can be very useful. On the other hand, automation may be avoided depending on the amount of flow on the assembly line or the level of complexity when processing specific materials. Human handling could be more suitable when machining accuracy and precision are required for setup.
Tool change refers to the replacement of tools, such as cutting tools and drills. Modern installations, such as machining centers (MCs), often have the functionality to automatically change tools. This automation is configured to detect wear and tear on the tool and then automatically change the tool. Edge Computing platforms that use edge AI are extremely effective in detecting tool wear and automating tool change.
The term rising refers to the time it takes from when the equipment is turned on to the time the equipment is running at full speed. In recent years, equipment has had a much faster start up speed than in the past.
Dry operation happens when the equipment is moving, but it is not performing correctly. This, too, has not been as apparent in manufacturing over the last few years.
This occurs when a piece of equipment stops frequently for a short period of time. It is often said that the cause of the suspension is unknown. Production equipment manufacturers design and manufacture with high reliability to minimize the number of chocolate stops, but as the cause is unknown and occurs suddenly, it may be difficult to respond. As there is occasionally a trend in the conditions when a stop occurs, it is necessary to constantly monitor remotely with Edge Computing to catch the trend.
Defects and rework
Defects refer to defective products, and rework refers to the process of reworking those defective products. Reworking can often be labor-intensive and costly unless the unit price of the product is inherently high. Defects can occur in the product design stage but can also occur as a result of production equipment failure. Because of this, it’s essential to monitor equipment – with the help of Edge Computing – by inspecting parts during the production process and identifying where the failure is happening.
Improve the overall efficiency of equipment
Within this blog, we have explained what the capacity utilization rate is, as well as the several terms related. It is important to strengthen equipment management at each stage of the production process to improve the overall efficiency of equipment. Edge Computing is a crucial tool in helping to manage facilities.