Asset performance management is an essential part of any profitable and effective asset-intensive enterprise. Asset performance management tracks asset usage and utilization during production and collects data about operating conditions and maintenance history.
Asset performance management takes into account surplus inventory and equipment kept idle for backup, as being able to bring these assets online when needed is crucial to减少停机时间。Manufacturing downtime等于损失的收入。
A company’s asset performance management practices should align with the company’s overall goals. All enterprises and organizations in the private sector with significant physical assets need to reduce downtime, as every minute of manufacturing downtime equals lost revenue.
In addition to reducing the number of complete stops in production, asset performance management also seeks to increase overall equipment effectiveness. Organizations need to be able to accurately project operating expenses when making budgeting decisions. Applying historical data to the future is ineffective if an asset’s operation varies dramatically as conditions change.资产绩效监控数据为将来的性能提供了重要的基准。
Manually-collected data still plays a role in asset performance management during visual inspection of assets, but in current practice the vast majority of information about asset performance is collected digitally. Sensors can wirelessly transmit information about the status of assets and equipment to a central database, providing a wealth of information about asset performance.
Companies that prioritize lean operations with minimal overhead may have to contend with an increase in equipment running outside of the conditions it was designed for, resulting in unplanned downtime. Asset performance management teams need to be prepared to quickly bring production back online.
One of the most important tools for asset performance management is software.乐动体育软件最新版资产绩效管理软件provides specialized tools for tracking asset performance. Sensor data from an entire production line can be navigated easily, and visualization tools can distill performance trends into easily comprehended graphs and charts.
As the price of digital sensors has dropped over the last few decades, the greatest barrier to increased sensorization has become networking itself. The cost of running cables from the sensors to a central database can be enormous. The information gathered by sensors could end up trapped in the locally attached computer; limiting its accessibility to only employees using the local machine.
These tools are able to provide incredibly subtle insight into how a plant or facility functions. Machine learning algorithms can reveal cascading effects caused by small variations in asset performance, allowing companies to make informed decisions about asset optimization that would have previously required a lot of guesswork.规定维护软件可以创建物理资产的数字双胞胎，使公司能够在数字环境中完全模拟对机械和设备的调整，以检查拟议更改的影响。
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