6 Factors Currently Impacting Your OEE

September 02, 2020 by Stefanini

There are several factors that can be impacting your OEE – whether you know it or not. What are some of these factors? Read our Trends blog for the answer!

We’ve discussed OEE before. As a quick reminder, overall equipment effectiveness (OEE) is used to help manufacturers notice a problem in their operations, identify which percentage of manufacturing time is actually productive, and fix it while giving them a standardized gauge for tracking progress. When you’re measuring your OEE, remember that the goal is for continuous improvement.

But there are several factors that can be impacting your OEE – whether you know it or not. What are some of these factors? Read on for the answer!

How to Use OEE to Measure Manufacturing Productivity

OEE is a powerful figure, providing a lot of information in one number. As a result, there are multiple ways OEE is used to measure manufacturing productivity. It can significantly maximize production when calculated and interpreted correctly. Further, it is commonly used as a benchmark to compare any given production to industry standards, in-house equipment, or other shifts working on the same piece of equipment. According to Reliable Plant, standard OEE benchmarks include the following:

  • When an OEE score is 100 percent, it is considered perfect production, meaning you’re only manufacturing quality parts as quickly as possible with no downtime.
  • When an OEE score is 85 percent, it is considered world class for discrete manufacturers and is a highly-prized long-term goal. 
  • An OEE score of 60 percent shows there is considerable room for improvement and is typical for discrete manufacturers.
  • An OEE score of 40 percent is considered low; however, it is not uncommon for manufacturers just starting to track and improve performance. In many cases, a low score can be improved through easy-to-apply measures.

While OEE is a great tool for managers, it can also have a significant impact on employees working the plant floor. Plant floor metrics can include:

  • Target – a real-time production target
  • Actual – the true production count
  • Efficiency – also known as the ratio of target to actual, efficiency refers to the percentage of how far ahead or behind production is
  • Downtime – this term includes all unplanned stoppage time for each shift. It is updated in real time.

Other important terms that often come up when discussing OEE include:

  • Quality – this term refers to manufactured parts that don’t meet quality-control standards, particularly the ones that need to be reworked. It is calculated as Quality = Good Count / Total Count.
  • Performance – this term takes into account the number of times there are slowdowns or brief stops in production. It is calculated as Performance = (Ideal Cycle Time x Total Count / Run Time. When you achieve a perfect performance score in OEE, it means your operation is running as quickly as possible.
  • Availability – this factor takes into account planned and unplanned stoppage time. It is calculated as Availability = Run Time / Planned Production Time. Achieving a perfect availability score means your operation is constantly running during planned production times.

 

6 Big Losses Related to OEE Implementation

When implementing an OEE program into your operations, the biggest goal should be reducing or eliminating the most common causes of machine- or equipment-based productivity, also known as the six big losses. These six losses are categorized according to the three main OEE categories: availability, performance, and quality.

Available Losses

1.      Equipment Failure: unplanned downtime results when equipment does not run when it is scheduled for production. Unplanned maintenance shops, machine breakdowns, and tooling failure are common examples.

2.      Setup and Adjustments: changeovers, planned maintenance, machine and tooling adjustments, setup/warmup time, and inspections can all result in production downtime.

Performance Losses

1.      Idling and Minor Stops: also known as small stops, idling and minor stops occur when equipment stops for a short period of time. These stops can be caused by jams, wrong settings, flow obstructions or cleaning and are usually resolved by the operator.

2.      Reduced Speed: also known as slow cycles, reduced speed occurs when equipment runs at speeds slower than the ideal cycle time (the fastest possible time). Common causes of reduced speed include worn out or poorly maintained equipment due to poor lubrication practices, substandard materials, and bad environmental conditions.

Quality Losses

1.      Process Defects: this term refers to any defective part manufacturer during stable production, including parts that can be reworked and scrapped parts. Common reasons for process defects include incorrect machine settings and equipment or operator errors.

2.      Reduced Yield: this term relates to defective parts make from startup until stable production is achieved. Similar to process defects, this can also mean scrapped parts and parts that cannot be reworked. Reduced yield most often occurs after changeovers, during machine warmups, and incorrect settings.

Benefits That Come From Measuring OEE

According to Automation World, when used correctly, OEE can provide visibility into the root of plant problems, allowing you to identify your potential losses and understand where plants are falling short. The following are some examples of plants using OEE data to improve availability and performance:

  •  Reduce downtime without buying new equipment: in this example, an automotive manufacturer is experiencing unexpected downtime issues that are related to their assemble line tool track. By using station-specific OEE metrics, they were able to identify an operation that was frequently experiencing small stops. Further investigation revealed that when vehicles advanced beyond a certain point in that operation, the torque tool hose reach was too short. When the torque tool could no longer reach the desired part, the line would stop working. To eliminate this downtime, the automated work instructions were rewritten to begin torqueing the part earlier in the line. This quick change improved availability at minimal cost and may not have been identified without the station-specific OEE metrics.
  •  Identify and correct causes of performance shortfalls:  OEE is also a great tool for gaining larger scale insights, including comparisons of shift productivity. In this example, a manufacturer needs to increase line speed from 17 jobs per hour to 23 jobs per hour. One shift showcased production rates considerably lower than the other. Possible causes included a lack of operator training, machine faults or lack of just-in-time parts. However, without specific data, it was hard to know where to start. OEE was evaluated for machines, operations, and operators. Ultimately, they were able to figure out that the issue was cycle slowing caused by insufficient operator capability on the second shift. To remedy this issue, second-shift operators were given additional training and performance targets were reached.

Clearly, whether you choose to use OEE for machines, stations, lines or all three, it’s one of those necessary basic tools that can help you improve production short and long term.

Stefanini’s Approach

Manufacturers face a multitude of balancing acts: produce more while spending less, create customized products but use standard processes, reduce technology debt while reducing time to market. Finding this balance is challenging.

We’re here to help, with the expertise and experience to provide new ideas and insights. We take a customer-first approach to everything we do, analyzing your pain points and business objectives to co-create a solution custom fit for you. Want to learn more about how we can help you? Contact us today!

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