Why Your Organization Needs IoT Data-Based Maintenance Management?
IoT is nothing new, but it is not old even. It always comes up in the news with the new feature and allures everyone. Today, it is rare to find out someone who is not aware of the Internet of Things or its benefits. Small, medium or large, all size companies are thriving to become part of this beautiful and limitless technology. One who has already adopted it are enjoying immense success and benefits in their business.
How is significant IoT Data?
IoT data holds tremendous value to maintenance management functions, but no doubt, the quality of value is directly dependent on the quality of the data you receive. This implies that source, timeliness and accuracy greatly influence the overall value data can offer. If you are planning to create IoT data that can aid to materialize your business objective, then, you must find out the following aspects.
- 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.
Let’s check how companies in asset-intensive industries are utilizing IoT to change their existing maintenance management functions.
The best feature that IoT data can offer is predictive maintenance, and we can say this on the basis of two key reasons. The progress in sensor and network technologies allows IoT data to help asset-intensive industries to optimize their maintenance management functions.
The first key reason: IoT data permits you to predict maintenance requirements and asset failures. It provides you with enough time to schedule the most favourable field service technicians based on their availability and skill set. Thus the process is streamlined successfully.
The Second Key Reason: The data-driven ability to conduct maintenance scheduling on an ad-hoc basis saves time and reduces the cost and improves first-time effectiveness.
For instance, HVAC equipment has temperature sensors to monitor the airflow efficiency and sends alert for filter replacement or maintenance when the airflow changes. In the same way, sensors embedded in solar panels which are connected through IoT can generate work orders whenever required and as per the need.
Data-Driven Inventory Management:
Inventory is an essential part of the maintenance function. There are many organizations that are dependent on a spreadsheet or other paper-based methods for inventory control and management. These processes, either a spreadsheet or a manual one, both can cause common inventory management mistakes like:
- 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.
To avoid these mistakes, companies have started using computerized maintenance management software. The software can collect and process the IoT data to facilitate companies with perceptibility into inventory levels. Use of IoT data to foretell the inventory levels say stock-in and stock-out of spare parts in different locations, organizations can optimize the spare parts stock and control the expenditure on new expenses. For instance, you can schedule a visit whenever required and order the new stock as per the need.
IoT data helps in making decisions related to asset and team performance. It allows the management team to monitor and track teams and assets to set Key Performance Indicators and track process (KPIs).
For example, you can find out the best performer in the team; in fact, calculate the team members’ regular average performance. Using the data, organizations can plan training and skill development programs for field service technician staggering. An organization can even organize reward, recognition and compensation program for star performers. In the same way, organizations can use data to replace the asset that is regularly causing threat and reducing downtime.
As we already know, IoT provides a lot more than we know, so using it for maintenance management functions can be a bliss for organizations. An organization should opt for better planning at the initial stage to ensure better data. Using relevant data, you can achieve reliable information and get enhanced decision-making capabilities. It is noted that early implementers of IoT in maintenance enjoy extraordinary benefits of transparency, visibility and efficiency in the operations. You should also review your on-going process and check how IoT can enhance your present maintenance management function.
Originally published at https://promptsoftech.com