Brad DeMarco’s Post

Unlock Hidden Potential: Master OEE for Peak Production Performance 💡 Did you know that manufacturers who track OEE see up to a 20% increase in production efficiency? Understanding your equipment’s performance can uncover bottlenecks and drive continuous improvement across your operations. 🌟 Overall Equipment Effectiveness (OEE) is a key metric for understanding how well your manufacturing equipment is performing compared to its full potential. It's made up of three essential components: ✔️ Availability – Is the equipment running when it's scheduled to? ✔️ Performance – Is the machine running at its optimal speed? ✔️ Quality – How much of your output is free from defects? 🚨 Why track OEE? Tracking OEE allows you to pinpoint where production losses are happening: ⚙️ Availability Losses – Downtime or breakdowns reduce the time equipment is operational. ⚙️ Performance Losses – Slowdowns and minor stoppages hurt production speed. ⚙️ Quality Losses – Defective products or rework eat into efficiency. Knowing where your inefficiencies lie allows you to: - Increase equipment uptime - Boost production speed - Improve product quality - Drive continuous improvement across the organization 📈 Real-World Results Recently, a manufacturing company implemented MachineMetrics across their production line, and in just two weeks, they saw a significant ROI. They were able to identify and fix a recurring issue causing equipment downtime, which led to a 15% increase in availability and a huge reduction in production delays. By simply tracking OEE in real time, they also reduced waste, improved quality, and increased overall output—without adding more machines or labor. This is how powerful real-time data can be! 🔎 How MachineMetrics helps: MachineMetrics automates the collection of real-time data from your machines, giving you a clear view of OEE performance across your factory floor. Instead of relying on manual reporting, you can instantly see where improvements are needed and take action. 🚀 Curious about how real-time OEE tracking can transform your business? Let’s connect! MachineMetrics can help you track OEE and unlock the potential hidden in your operations! 📈 #OEE #OperationalExcellence #ProductionEfficiency #LeanManufacturing #SmartFactory #IIoT #DataDrivenManufacturing #MachineMetrics #Industry40 #FactoryOptimization

Manipulating data to look good is easy. Making sustainable changes that reflect reality is hard. Only one of these helps. This manipulation may not always be intentional. Sometimes, while calculating metrics like OEE, manufacturers tend to set unrealistic target production rates within OEE calculations. The first step to calculating OEE is usually figuring out the ideal run rate of a piece of equipment. But this number cannot be arrived at through assumptions but should be based in reality. When you end up with an inflated OEE, you cannot identify the gaps in the production process, defeating the entire purpose of tracking metrics. If you’re looking to make sustainable changes, this is what you should do instead: Use historical data to set targets and figure out actual performance over the past months Account for factors like operator skill, material differences, and equipment fluctuations Having considered variability, arrive at realistic benchmarks and be flexible with them Regularly monitor and update target rates based on the ground reality Eugene Paradizov’s snippet below is from our episode on a deep dive into OEE. If this interests you, see links in the comments. #oee #integrity

From working on OEE solution. These are short notes about this solution. 🔧 What is OEE? OEE (Overall Equipment Effectiveness) is a key metric used to evaluate the efficiency of manufacturing equipment. It combines three critical factors: 1. Availability: Measures the percentage of scheduled time that the equipment is actually available for production. 2. Performance: Assesses how efficiently the equipment runs compared to its maximum speed. 3. Quality: Tracks the percentage of good parts produced without defects. 📊 Why is OEE Important? By tracking OEE, companies gain valuable insights into production bottlenecks, downtime, and inefficiencies. It helps: - Identify areas for improvement. - Reduce waste and operational costs. - Boost overall productivity. In essence, OEE enables smarter decision-making through real-time data, ensuring every asset performs at its best. #OEE #ManufacturingExcellence #ContinuousImprovement #OperationalEfficiency #LeanManufacturing #DigitalTransformation

📊 Unlock the Power of Data in Manufacturing with Precision and Ease! 🛠️ Measuring the weight of what your machine produces opens up a world of possibilities for comparison. From assessing the variance between raw material input and packaged output to calculating sigma (standard deviation) across different batches, and monitoring performance amidst varying raw materials and time, the insights are invaluable. But that's not all! 🚀 Whether it's quantifying hourly production in kilograms or other key parameters crucial for enhancing productivity, we've got you covered. And the best part? Implementing these metrics is not only simple but also cost-effective, tailored to fit seamlessly into your market dynamics. Ready to revolutionize your manufacturing process? Let's chat about how we can elevate your performance metrics and drive success! 🔍 #ManufacturingExcellence #DataDrivenDecisions #EfficiencyUnleashed

🏭 Optimizing Production & Manufacturing with Data-Driven Insights! 📊 Imagine: Identifying the top 20% of production issues responsible for 80% of your downtime. 🤯 Solution: Utilize a Diagrama de Pareto to analyze production data and pinpoint the most impactful areas for improvement. Here's how: 1. Collect data: Track production issues, delays, and defects over a specific period. 2. Categorize: Group issues by type (e.g., machine failure, material shortage, operator error). 3. Rank: Arrange categories by frequency (highest to lowest). 4. Visualize: Create a Pareto chart, highlighting the top contributors visually. 5. Focus: Prioritize efforts on the most impactful issues for maximum efficiency gains. Benefits: Reduced downtime: Target critical issues for faster resolutions. Improved efficiency: Streamline processes and optimize resource allocation. Cost savings: Minimize waste, rework, and lost production time. Sustainability: Optimize resource usage and reduce environmental impact. #ParetoAnalysis #ProductionOptimization #ManufacturingEfficiency #DataDriven #Sustainability #LeanManufacturing Rating: The combination of Producción y Fabricación and Diagrama de Pareto is a powerful one. The Pareto principle is a proven tool for streamlining processes, and its application within the manufacturing and production context can lead to significant improvements in efficiency, cost savings, and sustainability. This approach is highly effective and highly recommended. 👍 https://lnkd.in/e6bZd3eY

I think this is a good approach to OEE. you need to have a flexible model that can be shifted easily as some of the decisions may need to be tweaked down the road. Also, OEE is not a grade like you would recieve in school. it's a measurement tool that is meant to help identify and improve the system as a whole.

Every so often I see a webinar along the lines of “Implementing OEE in under an hour” This is definitely do-able. IF you already have all your data points mapped out. The time consuming part of every OEE implementation I’ve seen and done is figuring out what data to use, what data is valid, and getting everyone to agree on what is the correct data in the first place. “Is the machine/line/plant running” is usually the easiest of the pieces to determine with consensus. Oddly enough cycle time, and especially design cycle time to compare with actual cycle time has been one of the most challenging pieces. This tracks with my experience though. Many vendors don’t build in cycle time tracking into their equipment because it’s relatively easy to measure manually for proving everything meets spec. Design cycle time is usually lost to the ages. Quality is usually one of the easiest pieces to integrate, with the main question focused on WHEN quality data is collected. Most processes don’t have real time metrics on quality so there is more integration that needs to happen to update OEE for a batch when quality is collected. My approach is simple. 1. Pick a running state to start, worry about automated downtime reasons and more granularity as the next step after implementing OEE. 2. Make an educated guess for cycle time and design cycle time then adjust. 3. You can ALWAYS adjust the OEE calculation once you get quality data, so if you have it great, if not it’s okay to ignore the quality portion to start. Get started, learn how it works for you, then adjust and improve. Isn’t that the whole goal of OEE in the first place? May as well approach implementing OEE in the same way 😎

Manipulating data to look good is easy. Making sustainable changes that reflect reality is hard. Only one of these helps. This manipulation may not always be intentional. Sometimes, while calculating metrics like OEE, manufacturers tend to set unrealistic target production rates within OEE calculations. The first step to calculating OEE is usually figuring out the ideal run rate of a piece of equipment. But this number cannot be arrived at through assumptions but should be based in reality. When you end up with an inflated OEE, you cannot identify the gaps in the production process, defeating the entire purpose of tracking metrics. If you’re looking to make sustainable changes, this is what you should do instead: - Use historical data to set targets and figure out actual performance over the past months - Account for factors like operator skill, material differences, and equipment fluctuations - Having considered variability, arrive at realistic benchmarks and be flexible with them - Regularly monitor and update target rates based on the ground reality Eugene Paradizov's snippet below is from our episode on a deep dive into OEE. If this interests you, see links to the full episode in the comments. #oee

🚨 Do Bottling Manufacturers Really Know Their True OEE? 🚨 In the fast-paced world of bottling manufacturing, efficiency is everything. Yet, despite the recent advancements in manufacturing data analytics, a critical question remains: Do manufacturers truly understand their OEE (Overall Equipment Effectiveness)? Many companies pride themselves on their OEE metrics, but how accurate are these figures without causal loss analysis? Traditional OEE calculations often overlook intricate details of production losses in bottling lines, leaving a significant gap in understanding true operational performance. At LineView Solutions, we believe that true OEE can only be measured with a comprehensive causal loss analysis. Our innovative approach digs deeper, identifying the specific reasons behind inefficiencies and providing actionable insights to drive real improvements. Imagine having a clear, accurate understanding of every aspect of your production line’s performance in real time! This isn’t just about numbers on a dashboard; it’s about transforming your day-to-day operations, maximizing your efficiency, and staying ahead of the competition. Isn’t it time to question whether your current OEE metrics are giving you the full picture? Discover the difference with LineView Solutions – because knowing the cause is the first step to eliminating the loss! #OEE #Manufacturing #Efficiency #Innovation #FactoryoftheFuture #LineViewSolutions https://lnkd.in/eMHtQHtb

Improving current OEE rates can be a challenge for manufacturers, but with the right data, you can target areas negatively impacting OEE, and make increasing it an easier task. With PlantRun, you can monitor all historical OEE data, and reach an OEE rate that you are truly happy with, something that seems unachievable when relying on manual data collection. More than just an OEE and KPI reporting package PlantRun provides any level of production control and automation, and backed up by training and technical support, the systems ensure maximum value and long term reliability. More information available at: https://lnkd.in/eUWj4Tg #oee #productivity #industry40 #industrialautomation #leanmanufacturing #digitalisation #smartfactory