By Shreeya Mishra
In any production environment, the ability to maintain a dynamic balance in uptime, run time, and fully productive time is crucial. This delicate equilibrium ensures that a finished product can be manufactured at the lowest cost and highest efficiency. However, managing this balance can be challenging, and getting it wrong can have detrimental effects on plant performance. One of the key variables in achieving optimal performance is machine availability.
Machine availability, also referred to as uptime, is the total amount of time a machine actually runs compared to the time it was scheduled to run. It is expressed as a percentage, representing the machine's operational time. The scheduled time is determined by factors such as available capacity, raw material availability, workforce readiness, and sales orders. During the scheduled time, the machine may experience periods of downtime that can impact its availability.
Machine availability is a basic but critical Key Performance Indicator (KPI) in manufacturing. It plays a significant role in understanding the efficiency and effectiveness of a manufacturing operation. By measuring the time, duration, and reason for downtime, availability serves as an "anchor" that helps compile other KPIs to optimize processes at the machine or plant level.
Machine availability refers to the amount of time a machine is operational and ready for production. It is calculated by dividing the actual operating time by the total available time, excluding planned maintenance and scheduled downtime. This KPI provides valuable insights into the reliability and performance of individual equipment or production lines.
Impact on Overall Equipment Effectiveness (OEE)
Machine availability is one of the three KPIs used to determine Overall Equipment Effectiveness (OEE) in manufacturing. OEE is a comprehensive metric that evaluates the efficiency of a production process by considering availability, performance, and quality.
Performance and Quality KPIs
The other two KPIs in OEE are performance and quality. Performance measures how efficiently a machine or production line runs, taking into account factors like speed and production rate. Quality, on the other hand, assesses the level of defects or rejected products during the manufacturing process.
To accurately measure machine availability, several variables need to be considered:
Maximum Time : Maximum time refers to the total planned operating time for a machine or production line. It encompasses the time required for maintenance, changeovers, and scheduled downtimes.
Actual Time : Actual time represents the actual operating time of a machine or production line, excluding planned maintenance, scheduled downtime, and unscheduled disruptions.
Failure Rate : Failure rate indicates the frequency and severity of failures or breakdowns that result in machine downtime. By analyzing failure patterns, manufacturers can proactively address reliability issues and take preventive measures.
Planned Production Time : Planned production time is the time during which a machine or production line is intended to be operational and available for production, excluding scheduled maintenance and downtime.
The calculation for machine availability is relatively straightforward. It is determined by dividing the total run time of a machine by the planned production time. The formula can be expressed as follows:
Availability = Run Time / Planned Production Time
For example, let's consider a scenario where a machine runs for 8 hours, with 4 hours of downtime, during a 12-hour shift. To calculate the availability of this machine, we would use the formula:
Availability = 8 hours / 12 hours = 0.666 (or 66.6%)
Therefore, the availability of the machine in this case would be 66.6%.
Overall Equipment Effectiveness (OEE) is a crucial metric used to assess the efficiency and productivity of manufacturing equipment. By measuring the OEE, businesses can gain insights into how to improve their operational performance and increase their overall productivity. While OEE consists of three components, availability is particularly important as it serves as the foundation for calculating other metrics within the OEE framework.
OEE is a comprehensive measure that takes into account availability, performance, and quality. It provides a holistic view of equipment efficiency and effectiveness. The formula for calculating OEE is:
OEE = Availability x Performance x Quality
Each component is calculated separately and then multiplied together to obtain the final OEE score. While performance and quality can be formula-driven, availability requires meticulous data collection and analysis.
Machine availability and machine reliability are both important metrics in determining strategies to improve the availability of machines. However, they have distinct differences that should not be overlooked. Understanding these differences is crucial for optimizing processes and maximizing productivity.
Machine Availability: Uptime and Operability
Machine availability is a metric that measures the amount of time a machine is operable and available to perform its designated tasks. It indicates the percentage of scheduled time that the machine is up and running efficiently.
How is Machine Availability calculated?
To calculate machine availability, the uptime of the machine is measured against the scheduled time. This provides a clear picture of how often the machine is ready to operate as intended.
Its Importance in Process Improvement
Machine availability is a crucial metric as it reveals the potential for utilizing the machine during scheduled production time. By identifying any gaps or instances where the machine is not available, production managers can take proactive measures to improve uptime and minimize downtime.
On the other hand, machine reliability measures the failure rate of a machine in relation to its actual performance. It assesses the probability of a machine being able to produce good parts within a specified time frame.
Factors Affecting Machine Reliability
Machine reliability is impacted by various factors such as maintenance breakdowns, jams, tool breakages, and other variables that lead to machine failures. Even if a machine is available, any of these issues can significantly lower its reliability score.
The Relationship to Machine Availability
It is not uncommon for a machine to have a lower reliability score compared to its availability score. This is because availability measures the operability of the machine, while reliability takes into account the machine's actual performance and its ability to consistently produce accurate results.
Both machine availability and machine reliability play vital roles in process improvement and productivity optimization. By accurately assessing these metrics, production managers can identify areas of improvement and devise actionable strategies.
Enhancing Availability
By analyzing machine availability, managers can identify the reasons for downtime and take appropriate actions to ensure maximum uptime. This may include implementing preventive maintenance schedules, optimizing repair and maintenance processes, and investing in spare parts inventory management systems.
Improving Reliability
Improving machine reliability requires a deeper understanding of the root causes of machine failures. By conducting thorough root cause analyses, managers can address the underlying issues that lead to breakdowns and malfunctions. This may involve regular maintenance checks, operator training, and continuous monitoring of machine performance.
Machine availability is crucial for any manufacturing operation. A high level of uptime ensures that production targets are met and customer demands are satisfied. However, achieving optimal machine availability requires more than just hoping for the best. It involves implementing best practices, promoting a culture of efficiency, and utilizing software solutions.
Culture: The Foundation of Machine Availability
The first step towards improving machine availability is instilling a culture of efficiency within the organization. Often, operations overestimate their Overall Equipment Efficiency (OEE) due to a lack of awareness and outdated measurement tools. To bridge this gap, managers must strive to understand the available production time and make necessary changes to enhance OEE. Cultivating a culture of efficiency typically starts with top-down decision-making. Factors like market volatility, competition, and cost pressures motivate managers to prioritize machine availability. By recognizing the importance of continual improvement, organizations can create an environment conducive to maximizing uptime.
Maintenance: Reducing Downtime Events
Maintenance activities form a significant portion of downtime events in manufacturing operations. These events can either be planned or unplanned, but in either case, they can significantly impact machine availability. To mitigate unnecessary downtime, manufacturers need to collect and analyze equipment data effectively.
Traditional manual methods of data collection and analysis are time-consuming and prone to inaccuracies. By employing a machine data platform, manufacturers can automate data collection and standardization processes. This ensures that maintenance teams have real-time information about equipment performance and health. Leveraging this data, businesses can optimize maintenance strategies, such as adopting a condition-based approach or automating work orders in a Computerized Maintenance Management System (CMMS).
Optimized Processes: Enhancing Efficiency
Inefficient Standard Operating Procedures (SOPs) can contribute to downtimes caused by factors like wait time, staging issues, and inventory management problems. By streamlining and standardizing SOPs, organizations can reduce downtime occurrences and improve machine availability.
An analysis of accurate data can identify process inefficiencies and training gaps. Managers can use this information to develop better SOPs, provide remedial training, and align procedures across different shifts. Additionally, optimizing processes related to inventory control, staging, and work in progress (WIP) can directly impact machine availability.
While the above strategies can enhance machine availability, embracing software solutions can significantly amplify their effectiveness. Industrial Internet of Things (IIoT) platforms offer real-time machine monitoring, eliminating manual data capture and analysis.Using cutting-edge edge devices, such as the ones provided by NERP, manufacturers can capture, structure, and send machine data to cloud-based analytics engines seamlessly. This eliminates the need for manual reporting and data entry, empowering operators with visualizations that contextualize data and provide actionable insights.
Traditional methods of monitoring and managing machine performance can be time-consuming and prone to errors. However, with the advent of innovative technologies, such as NERP, businesses can now leverage data-driven insights to improve machine availability and optimize their manufacturing processes.
Instantly Connect Your Equipment
The implementation of NERP is a breeze, thanks to its user-friendly interface and seamless integration capabilities. Once connected, NERP starts gathering equipment data in real-time, providing a comprehensive overview of machine performance. This information can then be analyzed and used to identify areas of improvement, helping businesses enhance productivity and reduce downtime.
Actionable Insights with Dashboards
NERP offers intuitive dashboards that provide a visual representation of critical performance metrics. By leveraging these dashboards, businesses can quickly identify instances when equipment is falling behind part count goals. This allows the maintenance team to take immediate action and rectify the issue, minimizing production delays and maximizing machine availability.
Efficient Maintenance Management with Notifications
In addition to dashboards, NERP also features a notification system that alerts the maintenance team of downtime events. By being promptly notified of any equipment failures or malfunctions, businesses can ensure swift intervention and minimize the impact of unplanned downtime. This proactive approach to maintenance management not only improves machine availability but also enhances overall operational efficiency.
Accurate Benchmarking for Continuous Improvement
NERP enables businesses to develop accurate benchmarks across various key performance indicators (KPIs), such as cycle times and planned downtime. By comparing current performance against these benchmarks, businesses can identify inefficiencies and prioritize improvement efforts. This data-driven approach helps businesses reduce machine downtime, increase throughput, and achieve continuous improvement in their operations.
Identifying Opportunities and Eliminating Waste
NERP allows businesses to quickly identify their biggest opportunities and areas of waste. By analyzing equipment data, businesses can pinpoint bottlenecks, minimize idle time, and optimize machine utilization. This proactive approach to waste reduction helps businesses improve machine availability, reduce costs, and streamline their manufacturing processes.
NERP is a cutting-edge platform that autonomously collects and standardizes equipment data. This plug-and-play solution enables businesses to seamlessly connect their equipment, allowing them to access real-time data and gain valuable insights into machine performance. By automating the process of data collection and standardization, NERP eliminates the need for manual data entry, reducing human error and saving valuable time. By utilizing dashboards, notifications, and accurate benchmarking, businesses can identify areas for improvement and eliminate waste. With NERP, businesses can unlock their full production potential and stay ahead in the competitive market.
.jpg)
.jpg)
.png)
