Introduction
Manufacturing availability is a crucial factor in industrial operations that impacts profitability and productivity. It is defined as the amount of time that production equipment is available for use in a given period. The higher the availability, the more productive the equipment, and the more profitable the operation. Vanti’s AI-powered no-code platform offers manufacturers a unique way to enhance their equipment availability, optimize their processes, and boost their bottom line.
This blog post will explore the importance of manufacturing availability, the calculation of equipment availability, the role of Overall Equipment Effectiveness (OEE) in availability calculation, and tips for enhancing manufacturing availability. It will also discuss how Vanti’s platform can help companies improve their manufacturing availability, with a particular focus on predictive quality and process optimization.
Understanding Equipment Availability
To improve manufacturing availability, it is essential to first understand the concepts of machine and equipment availability. Machine availability refers to the percentage of time that a machine is up and running, while equipment availability is the percentage of time that all the machines in a production line are available for use. To calculate equipment availability, manufacturers use the following formula:
Equipment Availability formula = (Total Time – Downtime) / Total Time
The downtime includes all periods when the equipment is not available for use due to maintenance, repairs, changeovers, or any other reasons. Traditional methods of calculating equipment availability often have limitations, such as failing to account for unplanned downtime, measuring downtime manually, or ignoring minor stoppages. These methods can lead to inaccurate availability calculations, which in turn can negatively impact production planning and scheduling.
Overall Equipment Effectiveness (OEE) and Availability Calculation
OEE is a metric used to measure the effectiveness of manufacturing processes. It is calculated by multiplying three components: availability, performance, and quality. Availability measures the percentage of time that a machine is available for use, performance measures the speed at which the machine runs, and quality measures the percentage of good parts produced. For OEE availability calculation, manufacturers use the following formula:
Availability = (Run Time / Planned Production Time) x 100
Run Time is the total time the machine was operational, while Planned Production Time is the total time the machine was scheduled for production. Availability loss refers to the time lost due to unplanned downtime, setup time, and any other reasons. Calculating OEE availability provides manufacturers with a more accurate measure of their equipment availability, which helps them identify areas for improvement.
Tips to Enhance Manufacturing Availability
Predictive maintenance is a critical element in improving machine and equipment availability. By analyzing data from sensors and other sources, predictive maintenance enables manufacturers to identify potential issues before they become problems, allowing them to take action proactively. Real-time data monitoring also plays a vital role in enhancing availability. By providing manufacturers with insights into how their equipment is performing, data monitoring can help them identify trends and patterns, make data-driven decisions, and optimize their processes.
Automation and AI are other ways to enhance manufacturing availability. Automation reduces the need for human intervention and minimizes errors, which can lead to increased uptime and productivity. AI, on the other hand, can analyze large amounts of data and provide insights into how to optimize processes further. By identifying inefficiencies and bottlenecks, AI can help manufacturers improve their equipment availability and reduce downtime.
How Vanti’s AI-powered No-Code Platform Enhances Manufacturing Availability
Vanti is an AI-powered software platform that helps manufacturers minimize production halts and reduce unplanned downtime through process optimization and early quality forecast capabilities. Unlike other systems that mainly focus on predictive maintenance, Vanti’s platform is unique in that it concentrates on predictive quality and process optimization use cases.
Vanti’s self-adaptive machine learning models can be easily created by plant professionals without requiring advanced data science knowledge. By using AI to analyze real-time data, the platform’s predictive capabilities can predict poor product quality and streamline the production process to maximize equipment availability.
To prevent production halts, Vanti can detect product faults early by analyzing production data and identifying patterns that suggest potential quality issues. By alerting manufacturers to these issues early on, Vanti can help them take corrective action before the defects cause downstream issues or lead to product recalls.
Moreover, Vanti’s process optimization capabilities can reduce unplanned downtime by analyzing data from various sensors and sources to identify areas of the manufacturing process that are not performing optimally. By suggesting ways to improve these areas and addressing them early on, Vanti can help manufacturers prevent production halts and increase the overall efficiency of the production line.
Overall, Vanti’s use of advanced data analytics and machine learning technology can significantly improve productivity, reduce costs, and improve the bottom line of manufacturers by reducing unplanned downtime and preventing production halts.
Conclusion
Manufacturing availability is crucial for industrial operations as it can impact profitability, productivity, and customer satisfaction. To enhance manufacturing availability, predictive maintenance and real-time data monitoring play vital roles. Vanti’s AI-powered no-code platform is designed to improve manufacturing availability by providing end-to-end visibility into every aspect of a manufacturing operation, from machine performance to quality control. The platform leverages predictive maintenance and predictive quality approaches, which enables manufacturers to identify potential issues before they become major problems and address them proactively to minimize downtime.
At Vanti, we understand the challenges faced by modern manufacturers and our platform is designed to help manufacturers overcome those challenges by enhancing manufacturing availability, reducing downtime, and improving overall efficiency. Our platform is unique in that it focuses on both product and process health, which leads to higher first-pass yield and throughput. If you’re looking to improve your manufacturing availability and streamline your operations, we invite you to learn more about Vanti’s AI-powered no-code platform.
