OEE is Overall Equipment Effectiveness, a standard measurement to determine the efficiency and productivity of a manufacturing industry. Here, we’ll discuss ways to resolve the six big losses in OEE and the need for Power BI services to achieve the results.
The manufacturing industry has been growing despite various concerns due to supply chain disruptions, labor shortages, inflation, and restrictions that affected the global market in the last couple of years. According to Statista, global industry production (excluding the US) increased by 1.53% in December 2022. The emerging markets registered an increase of 3.3%, while US industrial production increased by 2.07% for the same period.
Deloitte released a report detailing the top five trends to watch out for in the manufacturing industry. Investing in technology to mitigate risk is the first and most important trend for 2023. This is an important factor as many manufacturers and working towards OEE improvement in production.
The six big losses in OEE (Overall Equipment Effectiveness) can severely affect the revenue and growth of a manufacturing enterprise. Technology plays a vital role in minimizing OEE loss and increasing the overall quality, production, and profits of the industry. Manufacturing companies partner with business intelligence service providers to digitally transform their processes and improve OEE effectively.
In this blog, we’ll read more about what OEE is, the losses of OEE, and ways to resolve them in a business.
OEE (Overall Equipment Effectiveness) is considered the gold standard to measure manufacturing productivity. A business with higher OEE implies being more productive and optimally using resources, while reducing defects or wastage. Quality, performance, and time are the three major parameters used to measure OEE.
Measuring OEE in manufacturing helps the industry improve its processes, benchmark progress, and increase the productivity of equipment by eliminating waste. Typically, a business with 100% OEE is termed perfect, while a business with 85% OEE (or more) falls into the world-class category. A typical industry will have about 60% OEE, and anything close to 40% or less is considered low OEE. This denotes that the manufacturer has a greater share of losses and should address the issues to get better results.
OEE = (Good Count × Ideal Cycle Time) / Planned Production Time
Availability | Planned Stops |
| Unplanned Stops | |
Performance | Small Stops |
| Slow Cycles | |
Quality | Production Rejects |
| Startup Rejects | |
| Overall Equipment Effectiveness (OEE) | Fully Productive Time |
Before we learn how to improve OEE, let’s first understand the six big losses that affect the manufacturing industry.
Equipment breakdowns and failure account for significant loss of time and productivity in an enterprise. This is usually categorized as availability loss as it is unplanned downtime. The equipment is not running when it is expected to run leads to wastage of time (puts everything behind schedule) and productivity (the factory produces a lesser quantity of goods due to equipment failure or breakdown).
This loss can also include relevant aspects such as tooling failure, unplanned maintenance, lack of material or operator (worker), or due to a blockage on either side of the manufacturing process. For example, if the production of a certain product involves eight steps, a disruption at the third step will affect the fourth step just as the disruption at the fifth step.
The second loss of OEE in production deals with the lack of availability of the equipment due to setup, installation, customization, or other adjustment requirements. This is the duration where the machine has to be running but is instead being adjusted (due to various reasons).
Though it is also considered availability loss, it comes under planned stops (as the workers or technicians stop work because they need to adjust the equipment before it starts running again). Cleaning, periodic maintenance, warmup time, cool down time, quality inspections, etc., are some examples of this.
Minor stops or idling time is the short duration when the machine’s operator stops its usage to resolve an issue. This is usually a minute or two (for each stop). It is categorized as performance loss because the equipment is available and running but is not performing (or producing) during that short period.
Minor stops can include machine idling due to a slight delay in feeding input material, incorrect settings, misaligned sensors, material jams, design complexities, and periodic mandatory cleaning sessions. All kinds of stops or breaks (in production) that are for less than five minutes for each period come under this type of OEE loss. These can be hard to track and can lead to major breakdowns if ignored.
This is the duration when the equipment is slower than the Ideal Cycle Time, thus resulting in the production of fewer goods than expected. It is categorized as performance loss as the equipment is not producing as many goods as it usually does. The Ideal Cycle Time is the fastest possible time taken to manufacture a product. It is a theoretical value calculated based on the given specifications of the machine.
Many reasons can lead to reduced speeds. A few common causes are improper equipment maintenance, poor lubrication, jamming, worn-out spare parts, bad working environment (unsuitable for production), poor quality raw or input materials, inexperienced operator, sudden shutdowns, etc.
Every batch produced may have some defective parts or goods despite the production process being stable throughout. Both scrapped products and the ones that can be reworked or reused are totaled in this loss. OEE measures quality based on the First-Pass Yield, which makes process defects a quality loss issue. If the quality of the products is good, they wouldn’t be marked defective.
Process defects can be due to various reasons like wrong or incorrect settings, providing wrong raw materials to the equipment, the inefficiency of the operator, or the expiration of materials (commonly found in pharmaceutical and food industries).
The last OEE loss is reduced or lesser yield caused by process defects. Reduced yield is also categorized under quality loss. Though it can occur at any stage of production, reduced or lesser yield is mostly noticed (in high frequency) after changeovers. It is also calculated from the perspective of First-Pass Yield.
Reduced or lesser yield is caused by different reasons, such as wrong settings, suboptimal changeovers, incorrectly implementing warmup cycles, or due to using equipment that generates waste after startup.
OEE is a quantifiable number. Many manufacturing businesses look for ways to improve the OEE score, which ultimately indicates high-quality production values. Popular strategies like Total Productive Maintenance (TPM) and Lean Management use OEE charts to create better procedures and improve overall product quality.
Here’s how to resolve the six big losses in OEE in manufacturing:
The first step should always be the calculation of OEE. You need to start by knowing where your business stands before you work on improvements. This also helps in correctly identifying the problem areas to find the most suitable solutions. While the OEE formula is simple enough, the calculation can be complicated and confusing. Also, using outdated or incorrect data will lead to a wrong score. Talk to Power BI experts to set up a customized OEE dashboard and get the score in real-time.
Digitalization is the process of using the latest technology to automate and upgrade systems for better results. Small losses, slower cycle speeds, etc., cannot be measured properly in the long term unless you have a definite tool in place to record every break or delay. Digitalization makes this possible by integrating the necessary applications with the equipment and streamlining data flow in the factory. IoT (Internet of Things) devices collect data from equipment in real-time and help supervisors flag delays, errors, breakdowns, etc.
Build a knowledge management system that can be easily accessed by operators and workers in the factory. The system can recommend workers the right time to schedule preventive maintenance checks, send alerts for changing oils, and create a checklist to ensure that there is little to no chance of the machinery breaking down due to repair or damaged spare parts. Since the maintenance programs can be scheduled during non-productive times, the business can reduce delays and losses.
SMED technique is the main principle of lean production. It reduces the time taken to complete equipment changeovers by simplifying the process. The idea is to reduce the changeover time to a single digit. It reduces manufacturing costs and makes it easier to make changes to the products without losing too much investment. Once the manufacturers have a smoothly functioning system in place, the workers can increase the batch sizes to produce more goods in fewer batches. This is known as standardizing the processes to increase overall efficiency. It also reduces variations that lead to defective goods and wastage.
Resolving the losses in OEE to improve its score is a continuous and long-term process. Manufacturers have to work with a reputed Power BI company to digitally transform the processes and automate recurring tasks.
Standardization, error-proofing, preventive maintenance, and employee training can be handled by the consulting company to help the manufacturing enterprise achieve its goals and generate greater profits through increased performance and productivity.
They have the experience and agility to understand what’s possible and deliver to our expectations.
