Why Your Organization Needs IoT Data-Based Maintenance Management?

  • The first aspect is to find out the data type required to meet your objectives and the data you can quickly gather from machines or in the field. You might find the gap between the two data points and no doubt, overcoming this gap is a long-term goal that could be accomplished as the sensor and network technology modernizes in the future.
  • Now, you have to validate the available data on the aspect of reliability, accuracy and timeliness to find out the relevant data.
  • You have to build a CMMS software architecture that can interpret the appropriate data into information.
  • Data entry error: Manual data entry invites lots of errors and results in misleading information.
  • Mismanagement in the warehouse: Well, we can say that data entry method is not the sole reason behind the error, but it is the type of data being recorded which disturbs the whole process. Since the entire process is manual, there is no mechanism available to check the data quality.
  • Poor Communication: Poor communication is the third setback within the organization, particularly between office administrative/executives and warehouse staff. This miscommunication often leads to error in data entry.

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