OEE is often defined as availability x performance x quality rate. But it can really be much simpler & more intuitive than that. OEE is simply the extent to which potential output was achieved over some scheduled period of time. That's it. AV, SR, & QR are components of OEE: Availability (AV) is a measure of equipment uptime. Speed Ratio (SR) compares the target cycle time with the actual cycle time achieved. This is sometimes called Performance Efficiency. Quality Rate (QR) captures the portion of total parts produced that were actually good parts. Here is an explanation of why multiplying these three components together is algebraically equivalent to OEE & why improving any combination of them can help your business when strategic needs require producing more parts in less time. #productivity #businessintelligence #analytics #data #culture #operationsmanagement #executivesandmanagement #leanmanufacturing #digitaltransformation #manufacturing #automotive #dataanalytics #excel #powerbi #datavisualization #lean #continuousimprovement #operations #operationalexcellence #oee 4.0 Solutions Zack Scriven George Forde Jeff Winter MARIANA MOSCOSA FactoVia
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Why do people claim that multiplying three terms together (AV, SR, & QR) & calling it OEE can be a meaningful KPI? Here's the math. OEE is an acronym for Overall Equipment Effectiveness, the extent to which potential output was achieved over some scheduled period of time. Improving it can be helpful in many situations. Availability (AV) is a measure of equipment uptime. Speed Ratio (SR) compares the target cycle time with the actual cycle time achieved. This is sometimes called Performance Efficiency. Quality Rate (QR) captures the portion of total parts produced that were actually good parts. The equation often used to relate these terms is OEE = AV x SR x QR. But why is this? What’s the rationale for this claim? #productivity #businessintelligence #analytics #data #culture #operationsmanagement #executivesandmanagement #leanmanufacturing #digitaltransformation #manufacturing #automotive #dataanalytics #excel #powerbi #datavisualization #lean #continuousimprovement #operations #operationalexcellence
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Optimizing Production & Manufacturing with Data-Driven Insights 📊 Tired of production bottlenecks? 🏭 Let's leverage technology to streamline your operations! By implementing a Gráfico de Control (Control Chart) for key production metrics, you can gain real-time visibility into your processes and identify potential issues before they escalate. Here's how it works: 1. Establish Baseline: Track your production metrics (e.g., cycle time, defect rate) over a period to establish a baseline. 2. Set Control Limits: Determine upper and lower control limits based on your baseline data. 3. Monitor in Real-Time: Use a digital dashboard to visualize your data and identify any deviations from the control limits. 4. Identify Root Causes: Investigate any points that fall outside the control limits to pinpoint the source of the problem. 5. Implement Corrective Actions: Take immediate action to address the root cause and prevent future occurrences. Benefits: Reduced Waste & Costs: Early detection of issues prevents costly rework and delays. Improved Efficiency: Optimized processes lead to faster production cycles and increased output. Enhanced Quality: Consistent monitoring ensures product quality meets your standards. #LeanManufacturing #QualityControl #DataDriven #ProcessImprovement #SupplyChainOptimization #Sustainability #CostReduction 📈♻️💰 https://lnkd.in/e6bZd3eY
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Did you know that unplanned machine downtime can significantly disrupt production and lead to substantial financial losses? Effective downtime management involves identifying and addressing issues before they escalate. Here are some key strategies: 👉🏻 Detailed analytics. Utilise data to understand downtime causes and patterns. 👉🏻 Real-time monitoring. Implement systems that provide live updates to detect issues promptly. 👉🏻 Preventive measures. Develop and apply strategies to prevent future occurrences. By proactively managing downtime, you can enhance manufacturing efficiency and reduce operational costs. #Manufacturing #ProductionEfficiency #DowntimeManagement #SmartFactory
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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
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As the year comes to a close, we recommend taking a broad view of your manufacturing data to understand how you’re performing and set SMART goals for next year. What are SMART goals? They are goals that are Specific, Measurable, Attainable, Relevant, and Time-Specific. Basically, they are goals that set you up for success! In order to create SMART goals, you need good production data displayed in a way that is easy to digest. We created the dashboard shown here in Vorne XL, but you can create something similar in whatever reporting system you use to understand the baseline from which you can improve upon next year. The first half of our dashboard shows a broad overview of OEE and OEE Losses for a quick look at how we did in the first half vs second half of this year. The next half dives deeper into our production data with a focus on the analysis of particular work centers, downtime by line, and the top losses in the first and second halves of 2024. These are just suggestions to help you get started in creating your own dashboard and setting SMART goals for a successful 2025! #manufacturingdata #overallequipmenteffectiveness #smartgoals
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As the year comes to a close, we recommend taking a broad view of your manufacturing data to understand how you’re performing and set SMART goals for next year. What are SMART goals? They are goals that are Specific, Measurable, Attainable, Relevant, and Time-Specific. Basically, they are goals that set you up for success! In order to create SMART goals, you need good production data displayed in a way that is easy to digest. We created the dashboard shown here in Vorne XL, but you can create something similar in whatever reporting system you use to understand the baseline from which you can improve upon next year. The first half of our dashboard shows a broad overview of OEE and OEE Losses for a quick look at how we did in the first half vs second half of this year. The next half dives deeper into our production data with a focus on the analysis of particular work centers, downtime by line, and the top losses in the first and second halves of 2024. These are just suggestions to help you get started in creating your own dashboard and setting SMART goals for a successful 2025! #OEE #manufacturing #SMART
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🔍 Unlocking Efficiency with Pareto Analysis: The 80/20 Rule 📊 In business, 80% of problems often stem from just 20% of causes. Pareto Analysis (the 80/20 Rule) helps identify and focus on the most impactful areas for improvement. How to Use Pareto Analysis: 1. Identify the Problem: Define the issue (e.g., customer complaints, defects). 2. Collect Data: Gather relevant data on the issue. 3. Categorize the Data: Group issues by common causes (e.g., types of defects). 4. Calculate Frequency: Find how often each issue occurs. 5. Create a Pareto Chart: Visualize the data to see which issues contribute the most. 6. Focus on the Vital Few: Prioritize actions for the 20% of causes creating 80% of the problem. Example Applications: Customer Complaints: Pareto shows 80% of complaints come from poor quality and delayed deliveries. Manufacturing Defects: 80% of defects are caused by faulty machines and operator errors. Pareto Analysis helps businesses make data-driven decisions, optimize resources, and achieve sustainable improvements. #ParetoAnalysis #ContinuousImprovement #DataDriven #QualityManagement #80/20Rule
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Cause and effect diagrams facilitate insight into problems. They draw on the experience of people in close contact with the area of concern. https://bit.ly/3UuKSxu #SPC #Manufacturing #QualityControls #Data
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𝗧𝗵𝗲 𝗱𝗮𝗶𝗹𝘆 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗿𝗲𝗽𝗼𝗿𝘁 𝗶𝗻𝗱𝗶𝗰𝗮𝘁𝗲𝘀 𝘄𝗲 𝗮𝗿𝗲 𝗮𝗰𝗵𝗶𝗲𝘃𝗶𝗻𝗴 𝗼𝗻𝗹𝘆 𝟭𝟳𝟳 𝗽𝗮𝗿𝘁𝘀 𝗽𝗲𝗿 𝗵𝗼𝘂𝗿 (𝗽𝗽𝗵). 𝗛𝗼𝘄𝗲𝘃𝗲𝗿, 𝗮 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝘁𝗶𝗺𝗲 𝘀𝘁𝘂𝗱𝘆 𝗰𝗼𝗻𝗳𝗶𝗿𝗺𝘀 𝘁𝗵𝗮𝘁 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸 𝗰𝗲𝗻𝘁𝗲𝗿 𝗶𝘀 𝗰𝗮𝗽𝗮𝗯𝗹𝗲 𝗼𝗳 𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝟮𝟯𝟬 𝗽𝗽𝗵, 𝗳𝗮𝗰𝘁𝗼𝗿𝗶𝗻𝗴 𝗶𝗻 𝗮 𝟭𝟱% 𝗮𝗹𝗹𝗼𝘄𝗮𝗻𝗰𝗲 𝗳𝗼𝗿 𝗺𝗶𝘀𝗰𝗲𝗹𝗹𝗮𝗻𝗲𝗼𝘂𝘀 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝗶𝗲𝘀 𝗮𝗻𝗱 𝗿𝗲𝗽𝗮𝗶𝗿𝘀. • 𝗞𝗻𝗼𝘄 𝘆𝗼𝘂𝗿 𝗮𝗰𝘁𝘂𝗮𝗹 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆, clearly defined. • 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀 by investigating issues, collecting data, and engaging all departments using the PDCA cycle (Plan-Do-Check-Act). • 𝗔𝗰𝗵𝗶𝗲𝘃𝗲 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗼𝘂𝘁𝗽𝘂𝘁 from the work center to meet its full potential. With 𝘀𝗼𝗹𝗶𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 on your process, combine 𝗱𝗮𝘁𝗮 𝗰𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 to ensure the live KPI's are visible. From the 𝘀𝗵𝗼𝗽 𝗳𝗹𝗼𝗼𝗿 𝘁𝗼 𝘁𝗵𝗲 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱, I will collaborate with your teams to make this a reality. Feel free to send me a message, and let's have a chat! #ContinuousImprovement #Manufacturing #DataDriven #Factbird #ShopFloorOptimization #OEE #ManufacturingIntelligence #ProcessImprovement
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The Importance of Implementing Predictive Maintenance Today I want to share an inspiring success story that shows how predictive maintenance can revolutionize operations and significantly increase profitability. Explore the PDF to discover the strategy behind the effective implementation of predictive maintenance. In our daily operations, we often hear about how downtime can lead to substantial financial losses. This is where the critical role of predictive maintenance (PdM) comes into play. By leveraging advanced data analytics and machine learning, PdM predicts equipment failures before they occur. This proactive approach transforms maintenance management by reducing unplanned downtime, cutting costs, and improving operational efficiency. Implementing PdM is more than just an upgrade; it is a strategic necessity for any organization striving for excellence in maintenance management and overall operational performance. I am sure you will find this story compelling and insightful. We’d love to hear from you! Have you implemented Predictive Maintenance in your organization? What challenges and successes have you experienced? Share your stories and insights in the comments below. Your feedback and experiences are valuable to our community. Let's learn and grow together! Guillermo Cárdenas Cardenas.gmo@outlook.com Cell +52 5531995695 https://wa.link/fp21kn #PredictiveMaintenance #MaintenanceStrategy #ProactiveMaintenance #SmartManufacturing #OperationalExcellence #Industry40 #DataDriven #ManufacturingInnovation #MaintenanceManagement #ContinuousImprovement
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