What is the role of AI-powered OEE dashboards in transforming manufacturing processes

The manufacturing industry is transforming to stay competitive in the global market. Advancements in technology are enabling more efficient, flexible, and sustainable processes. The need for improved quality, reduced cost, and meet market demand made manufacturer to modernize their operations. Here the OEE dashboard comes in the picture.

According to Brain & Company, companies that use data visualization are 5 times more likely to make faster decisions and 3x more likely to execute them than their competitors.

Overall equipment effectiveness (OEE) dashboards are an indispensable tool that consolidate critical metrics and quality to provide real-time insights into production process. Leveraging data from machines and operators, OEE dashboards empower organizations to be more sustainable and agile. AI-powered OEE dashboards are crucial for manufacturing industry. Do you know why? Read this blog to know what OEE dashboard is and how it revolutionizes the production process.

What is an OEE dashboard?

An OEE dashboard is a powerful tool that helps organizations in monitoring, optimizing, and analysing their production processes and efficiency. It leverages a real-time visual representation of key performance indicators and gives insights into the actual status of your machines and systems.

Data visualization helps identify the areas where improvement can be made to optimize productivity and reduce downtime. It integrates data from various sources such as machines, production lines, and operators This helps with:

• Enhanced existing plants instead of installing new machines
• Minimized errors
• Insights into reasons for losses like overproduction, waiting times, rejections, etc.

A well-designed OEE dashboard measures three key components:

Availability

• Measures scheduled time percentage that the equipment is operational.
• Records downtime and identifies the reason that causes machine stoppage.

Performance

• Assess the actual speed of production compared to its maximum potential speed.
• Highlight performance due to slow cycles or minor stops.

Quality

• Reflect good units produced ratio out of the total unit started.
• Identifies defects and rejects and helps improve the quality.

Examples of OEE dashboard

Our dynamic OEE dashboard for a manufacturing company

OEE dashboards for lean manufacturing

An OEE dashboard tailored for lean manufacturing serves as a powerful tool to optimize production efficiency, reduce waste, and drive continuous improvement. Key functionalities and structure of OEE dashboard:

1. Availability metrics:

Tracks the percentage of time that equipment is available for production.

Examples: Planned downtime (scheduled maintenance, changeovers), unplanned downtime (breakdowns, material shortages).

2. Performance metrics:

Measures the speed at which equipment operates compared to its maximum designed speed.

Examples: Slow cycles, minor stoppages, startup losses.

3. Quality metrics:

Evaluates the percentage of defect-free products produced by the equipment.

Examples: Rework, scrap, production of out-of-spec parts.

Why OEE dashboards are important for modern manufacturing organizations

OEE dashboards are significant tools for modern manufacturing organizations due to its transformative impact on operational efficiency and profitability. It provides real-time visibility, enhances proactive maintenance, enables continuous improvement, and optimizes resource utilization. Let’s explore the reasons why OEE dashboards are important:

Real-time performance monitoring:

OEE dashboards provide instant visibility of machine performance, downtime, and production rates.

Example: An automotive company can use OEE dashboards for several purposes such as monitoring machine uptime and performance metrics for its assembly line. This can help reduce downtime by 15%.

Identify challenges and inefficiencies

Highlights pain point areas, lagging in production, and inefficient processes.

Example: Food processing plants can identify challenges in packaging due to slow machine speed. OEE data can lead to a 20% increase in throughput process optimization.

Enhances in decision-making

Enables to gain actionable insights for improved decision making.

Examples: A pharmaceutical company can adjust production schedules based on real-time OEE insights that help reduce waste and improve delivery time.

Predictive maintenance

The use of AI helps to forecast equipment failure and schedule maintenance.

Example: A manufacturing plant can use the OEE dashboards to implement predictive maintenance. This dashboard can help reduce 25% of equipment downtime and increase machine lifespan.

Continuous improvement:

OEE dashboard helps facilitate continuous improvement by setting a benchmark and tracking progress over time.

Example: An electronic manufacturer can use dashboard insights to analyze trends and implement incremental process improvement. They can achieve 10% increase in OEE.

Real-time data for predictive analytics

1. Unplanned downtime and equipment failure

Challenge: Equipment failure results in unplanned downtime, disrupts production schedules, and increases costs.

Solution: Implement predictive maintenance

2. Quality control issues

Challenge: Variation in product quality results in rework, scrap, and customer dissatisfaction.

Solution: Real-time quality metrics monitoring makes it is easy to identify deviations from quality standards early.

3. Production efficiency and optimization

Challenges: Inefficient production processes lower throughput and increase production costs.

Solution: Analyze performance metrics such as availability, performance, and quality to identify bottlenecks and inefficiency.

4. Supply chain disruptions

Challenges: Supply chain delays can disrupt production schedules and result in inventory shortages.

Solution: Integrate supply chain data with OEE dashboards to get insights on material shortages and accordingly adjust production plans.

Suggested: How to prevent an 8% revenue loss through supply chain digitization?

Role of AI in enhancing AI-powered OEE dashboards

Artificial Intelligence plays a pivotal role in revolutionizing OEE dashboards by introducing capabilities beyond traditional analytics.

• Advanced analytics: AI algorithms analyze vast amounts of data (historical and real-time) to uncover hidden patterns and correlations. It not only allows accurate performance predictions but helps in proactive maintenance strategies.
• Predictive analytics: AI-powered predictive model uses historical records to predict equipment failure, enabling a proactive maintenance schedule and minimizing unplanned downtime. It helps in optimizing maintenance practices and enhances operational efficiency.
• Optimization: The algorithms optimize production schedules and resource allocation considering various factors such as demand forecasts, equipment capabilities, and operational constraints. It ensures that production resources are utilized efficiently, and errors are reduced.

Suggested: Benefits of using an OEE system for your manufacturing enterprises

Conclusion

Integration of AI with OEE dashboards enable you to take a transformative leap in manufacturing. These technologies help you achieve unprecedented levels of efficiency, reliability, and competitiveness in today’s fast-paced market landscape.

Contact Softweb Solutions for your data visualization needs. Our data analysis experts are experienced and have helped businesses of all sizes and industries to unlock insights hidden within their data.