The 5 IoT Trends Business Should Look for in 2021
2020 has been a crucial year for IoT, but most of its potential
READ MORE >>Data can be described as facts and statistics collected together for reference analysis. It is used for the basis of reasoning, calculation, or planning something. The effectiveness and efficiency of the maintenance will always depend on accurate data – something that can’t be avoided by any companies. Here are the things that the leader has to pay attention to: good data management and getting better maintenance.
Poor scoping and targeting are the main issues due to lack of maintenance. The company will systematically analyze years of locomotive-failure data. With more accurate and time-based maintenance rationalization, managers can manage more than 80 percent of the required maintenance tasks and save more than 30 hours of maintenance per year. Coupled with lower repair costs, the companies can invest those costs into a new technology that can improve maintenance and asset replacement decisions.
The company discovered that the main source of the problem was its poor planning process. Because such orders failed to account for the issue's criticality or the asset's location, technicians were often forced to drive long distances to do relatively small tasks while more vital ones awaited nearby. With good technical aspects collaboration will allow planners to cluster tasks by location, and prioritize tasks based on the impact of commercially important service-level agreements. This will increase maintenance efficiency by more than 15 percent and save an hour of planning work a day.
Time efficiency is one of the main parameters that should make the significant impact for the company. Predictive maintenance is a technological method to track equipment performance in real time and predict machine failure so that the companies can fix their machine before its downtime. Predictive Maintenance utilizes condition monitoring via real-time data collected through the Industrial