How to Calculate Availability in Microsoft Dynamics

Manufacturing availability is a critical metric for evaluating the efficiency and performance of a production facility. By measuring the amount of time that a manufacturing process is available and running, businesses can gain valuable insights into their operational effectiveness. This article will provide a step-by-step guide on how to calculate manufacturing availability in Microsoft Dynamics, a popular software solution for manufacturing companies.

Value of Availability Metric When Calculating OEE

One of the key indicators of overall equipment effectiveness (OEE) is availability. OEE is a measure of how effectively a machine or process is utilized during production. It takes into account factors such as availability, performance, and quality to provide a comprehensive view of production efficiency. Availability, in this context, refers to the percentage of time that a machine or process is available for production. It is an essential metric for identifying potential bottlenecks or downtime issues that can impact overall productivity.

When calculating OEE, availability plays a crucial role in determining the overall efficiency of a manufacturing process. A high availability percentage indicates that the machine or process is consistently operational and ready for production. On the other hand, a low availability percentage suggests that there are frequent breakdowns or maintenance issues causing downtime. By monitoring availability closely, manufacturers can pinpoint areas for improvement and implement strategies to enhance machine reliability and uptime.

Furthermore, availability is not just about the physical uptime of a machine; it also considers factors such as planned downtime for maintenance, changeovers, and other scheduled activities. Understanding the different components that contribute to availability allows organizations to optimize their production schedules and minimize disruptions. By maximizing availability and reducing unplanned downtime, manufacturers can improve overall equipment effectiveness and ultimately drive greater productivity and profitability.

Key Metrics for Measuring Availability

When calculating manufacturing availability, there are several key metrics that need to be taken into consideration:

1. Planned Production Time: This is the total amount of time that a machine or process is scheduled to operate.
2. Unplanned Downtime: This refers to the time during which a machine or process is not available for production due to unexpected breakdowns, maintenance, or any other unforeseen events.
3. Planned Downtime: Unlike unplanned downtime, planned downtime is the time intentionally set aside for scheduled maintenance, changeovers, or other planned activities that temporarily halt production.
4. Production Time: This is the actual time during which a machine or process is engaged in production activities.

These metrics will provide the necessary data to accurately calculate manufacturing availability in Microsoft Dynamics.

Furthermore, it is essential for manufacturing companies to continuously monitor and analyze these key metrics to identify trends and patterns that may impact availability. By closely tracking planned production time, unplanned downtime, planned downtime, and production time, organizations can proactively address issues and optimize their manufacturing processes for improved efficiency and productivity.

In addition to the mentioned metrics, another important factor to consider when measuring availability is the Overall Equipment Effectiveness (OEE). OEE is a comprehensive metric that takes into account availability, performance, and quality to provide a holistic view of equipment effectiveness. By incorporating OEE into the analysis of manufacturing availability, companies can gain valuable insights into the overall performance of their production processes and make informed decisions to drive continuous improvement.

Step-by-Step Guide to Calculating Availability in Microsoft Dynamics

Step 1: Access Microsoft Dynamics 365

1. Log in to Microsoft Dynamics 365: Use your credentials to access the system. Your access level will depend on your role within the organization.
2. Navigate to the Production Control Module: This module provides access to the tools and data necessary for managing and monitoring production activities.

Step 2: Gather the Required Data

To calculate availability, you need two key data points:

1. Run Time: This is the total time that the production equipment was actively running and producing goods.
   • Navigate to the Production Orders or Shop Floor Management section within Dynamics 365.
   • Select the relevant production order or job.
   • The Run Time can be found in the Production Order Details or by accessing the Job Card Terminal where operators log start and stop times for production runs.
2. Planned Production Time: This is the total time that was scheduled for production, excluding planned downtime (e.g., scheduled maintenance or breaks).
   • Within the same Production Orders section, find the planned production time.
   • This is typically defined during the planning stage and can be found in the Routing or Production Schedule details.

Step 3: Perform the Calculation

Once you have gathered the required data:

1. Open a Calculator or Spreadsheet: Microsoft Dynamics 365 may not automatically calculate this specific availability metric, so you can perform the calculation manually or in a spreadsheet like Excel.
2. Calculate Availability:
   • Divide the Run Time by the Planned Production Time.

Step 4: Record and Analyze the Availability

1. Document the Calculation: Record the calculated availability percentage in a report, spreadsheet, or directly into Microsoft Dynamics 365 if your system has custom fields or dashboards for OEE metrics.
2. Compare Against Targets: Evaluate the calculated availability against internal benchmarks or industry standards to assess the efficiency of your production processes.
3. Investigate Variances: If the availability is lower than expected, use Dynamics 365’s reporting and analytics tools to investigate potential causes, such as unexpected downtime, delays in starting production, or equipment failures.

Step 5: Continuous Improvement

1. Monitor Availability Regularly: Continuously track availability to identify trends, recurring issues, or opportunities for improvement.
2. Implement Process Improvements: Based on your analysis, take corrective actions such as optimizing production schedules, minimizing unplanned downtime, or improving equipment maintenance practices.
3. Leverage Microsoft Dynamics 365 Features: Utilize advanced features in Dynamics 365, such as Asset Management for preventive maintenance and Power BI for real-time analytics, to enhance data accuracy and improve availability tracking.

By following these steps, you can accurately determine the manufacturing availability in Microsoft Dynamics and gain valuable insights into your production efficiency.

Manufacturing availability is a critical metric that reflects the efficiency and reliability of your production processes. By calculating this key performance indicator (KPI) in Microsoft Dynamics, you can identify areas for improvement and optimize your manufacturing operations.

Furthermore, analyzing manufacturing availability over different time frames can provide valuable trend data that helps in forecasting production needs, scheduling maintenance activities, and maximizing equipment utilization. This data-driven approach enables proactive decision-making and enhances overall operational performance.

Common Challenges in Calculating Availability

While calculating manufacturing availability can provide valuable insights, there are several common challenges that businesses may face:

• Accurate Downtime Tracking: It can be challenging to accurately track and record instances of downtime, especially if there is a lack of real-time monitoring systems or manual data entry processes.
• Data Integration: Integrating data from different sources, such as production schedules, maintenance logs, and equipment sensors, can be complex and require advanced technical capabilities.
• Different Downtime Categories: Distinguishing between planned and unplanned downtime and categorizing them correctly is crucial for accurate availability calculations.

Addressing these challenges requires proactive monitoring, data integration, and robust processes to ensure accurate availability calculations.

Furthermore, another significant challenge in calculating availability lies in the interpretation of downtime data. It is not enough to simply record the duration of downtime; understanding the root causes and patterns of downtime events is essential for implementing targeted improvements. This requires in-depth analysis of downtime data, which can be time-consuming and resource-intensive.

In addition to the technical challenges, there are also organizational hurdles that can impede accurate availability calculations. Resistance to change within the workforce, lack of cross-departmental collaboration, and siloed data management practices can create barriers to implementing effective availability tracking systems. Overcoming these obstacles requires a cultural shift towards a data-driven mindset and a commitment to continuous improvement at all levels of the organization.

Integrating Smart Factory Tools for Accurate Availability Insights

To overcome the challenges mentioned above, many manufacturing companies are integrating smart factory tools into their operations. These tools leverage technologies such as Internet of Things (IoT), machine learning, and real-time analytics to provide accurate and timely data for availability calculations. By monitoring equipment performance, detecting anomalies, and automatically recording downtime events, smart factory tools enable businesses to optimize their availability metrics and make data-driven decisions to improve overall efficiency.

Furthermore, the implementation of smart factory tools not only enhances availability insights but also contributes to predictive maintenance strategies. By analyzing real-time data from machinery and equipment, manufacturers can predict potential failures before they occur, thus reducing unplanned downtime and maintenance costs. This proactive approach to maintenance ensures continuous production flow and minimizes disruptions in the manufacturing process.

Schedule a Mingo Smart Factory Demo Today

Curious to see how many steps it takes to calculate availability in Mingo Smart Factory? The answer is one. The availability calculation is automatically done for you in the manufacturing dashboard. With the integration of smart factory tools, companies can gain even deeper insights into availability metrics and further enhance their manufacturing processes.

Ready to take your manufacturing availability to the next level? Mingo Smart Factory offers a seamless, customizable solution that’s quick to implement and designed for the unique needs of your operations. Say goodbye to complex systems and hello to a user-friendly platform that grows with you, without the need for dedicated IT support. Connect with your existing equipment effortlessly, or let Mingo provide the necessary hardware for comprehensive data collection. Don’t let downtime hold you back—Talk to an Expert today and discover how Mingo Smart Factory can transform your manufacturing efficiency.