As a production company, maximizing your equipment’s productivity and tracking production in manufacturing is crucial to maintaining profitability and staying competitive in the fast-paced industry. One way to achieve this is by tracking your Overall Equipment Efficiency (OEE) and leveraging the insights gained to optimize your operations through data-driven decisions. In this blog post, we’ll explore what OEE is, why it matters, and how you can start tracking it today using automated systems and data analytics.
OEE or Overall Equipment Efficiency tracking is a data-driven approach used to measure the effectiveness of your equipment in producing goods or services. It considers three key factors: availability, performance, and quality. These factors are then multiplied together to get an overall OEE score, which ranges from 0 to 100%.
Availability refers to the percentage of time your equipment is available for production. If your equipment is frequently down for maintenance or repairs, your availability score will be lower, leading to equipment downtime reduction.
Performance measures how well your equipment performs when it’s running. This includes factors such as speed, setup time, and changeover time, which are key factors for production efficiency.
Quality refers to the percentage of products or services that meet your quality standards, which are critical for maintaining customer satisfaction. If you produce a high percentage of defective products, your quality score will be lower.
Here are 4 OEE (Overall Equipment Effectiveness) benchmarks commonly used in manufacturing:
Tracking your OEE provides several benefits to your manufacturing unit. Some of them are:
By tracking your OEE, you can identify areas of your production process that are causing bottlenecks or downtime, leading to improved production capacity. This also allows you to make data-driven decisions on how to optimize your operations and improve productivity.
Improving your OEE score directly correlates to increased productivity, which leads to higher profitability, a key advantage in a fast-paced business environment. By maximizing your equipment’s efficiency, you can produce more goods or services in less time, reducing costs and increasing revenue.
By measuring quality as a factor in your OEE score, you can identify areas where your products are not meeting your quality standards. This allows you to take corrective actions to improve product quality and customer satisfaction.
To start tracking OEE, you can use automated systems such as sensors or software to gather data on your equipment’s availability, performance, and quality. This will allow you to calculate your OEE score using the following formula:
OEE = Availability x Performance x Quality
You can then use this score to identify areas of improvement in your production process and take action to optimize your operations through data analytics.
OEE tracking is a simple yet powerful way to improve the efficiency and profitability of your production company. By production tracking, identifying inefficiencies, increasing manufacturing capacity, increasing productivity, improving quality, and proper industrial production capacity utilization you can stay competitive in the manufacturing industry and gain a competitive advantage in this fast-paced business environment.
Power BI is a powerful data analytics tool that can help manufacturing units track their Overall Equipment Efficiency (OEE) by providing real-time insights into their product management performance metrics. Here are some ways Power BI can help with OEE tracking:
Power BI can help production companies track OEE by providing real-time data visualization dashboards that can show the performance of each machine or equipment. This allows production managers to identify areas of inefficiency in their production process and take corrective actions quickly.
Power BI can integrate with different data sources like Microsoft Excel or SQL Server to collect and analyze data from different production systems. This makes it easier for production managers to get a complete view of their production process and identify the root cause of any issues.
Power BI allows production companies to create customized reports showing different KPIs (key performance indicators) related to OEE trackings, such as machine utilization, downtime, and production yield. This helps production managers to identify opportunities for improving production efficiency and profitability.
Power BI can be used to implement machine learning algorithms to predict potential issues with the equipment or machines. This allows production companies to take preventive measures to avoid downtime and improve overall production efficiency.
Power BI can be accessed through a mobile app, which allows production managers to monitor the production process from anywhere and anytime. This provides real-time visibility into production operations and helps managers make informed decisions quickly.
These are some of the best practices that should be implemented to improve OEE:
Successfully implementing OEE can be a challenge for some enterprises, hindering their ability to improve it. Assigning a digital or project partner can help overcome challenges and offer complete accountability for OEE implementation. With a consultant/partner in place, issues can be resolved, leading to successful implementation and sustainable changes.
Today, manufacturers should avoid using outdated manual data collection methods and managing paperwork or Excel files. Instead, they should adopt real-time monitoring to identify performance issues and analyze data for identifying trends and areas for improvement. This enables them to promptly address issues before they escalate into major problems.
Continuously review and improve processes to identify and eliminate waste, reduce downtime, and improve overall equipment performance. Encourage employees to participate in improvement initiatives and provide them with the necessary training and resources to make changes.
Root Cause Analysis (RCA) is recommended as it is a methodical problem-solving process that identifies the fundamental cause of a problem. By addressing the root cause instead of symptoms, the recurrence of any equipment problem can be prevented.
Identifying and eliminating the 6 big losses of manufacturing within your enterprise is crucial in calculating OEE and providing insights into areas that need improvement. Manufacturers should analyze the causes and amounts of these losses to identify where to focus their efforts. Typically, unplanned downtime should be the primary focus since it can result from various issues, including machine breakdown or logistics problems. However, other factors, such as performance loss on machines, may also impact productivity, and manufacturers should prioritize based on their data.
Power BI is a good fitting tool for tracking OEE in production companies. It provides real-time data visualization, integrates with different data sources, provides customized reports, and allows the implementation of ML algorithms to improve production efficiency. With Power BI, production companies can optimize their production process and improve profitability by making data-driven decisions based on real-time insights. So why not start tracking your OEE today using automated systems and data analytics and reap the benefits for your company’s success?
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