How Iot Data Is Powering Maintenance Management Function
The Wealth of IoT Data
The wealth of IoT data offers tremendous value to maintenance management functions. Here, the quality of the value you derive depends on the kind of wealth you have. Means the general trait of your data, determined by their sources, timeliness, and accuracy have a high impact on the overall value it can offer. If you wish to create the wealth of IoT data that helps you materialize your business objectives:
- first off, identify the data type that would be required to fulfil your objective and the data you can collect from machines or in the field. Here, you might find the gap between these two data points. Reducing this gap is a long-term goal that could be achieved as the sensor and network technology advances in the future.
- Secondly, validate the data available with you on the dimensions of timeliness, accuracy, and reliability to filter out the relevant data.
- Thirdly, build a CMMS software architecture that can translate the relevant data into information.
A lot of effort goes into the planning and execution of making IoT data usable for the MRO functions. The initial journey begins when you set your objectives—what information you need from the IoT data. Every move ahead in this journey hinges on that specific “need.” Here take a look at how companies in asset-intensive industries are using IoT to transform their maintenance management function.
No benefit of IoT data in maintenance is even close to predictive maintenance. It is for two key reasons:
- IoT data allows you to predict maintenance requirements and asset failures. You get enough time to schedule the best field service technicians based on availability and skill set thus making the process streamlined.
- The data-driven ability to perform maintenance scheduling on ad-hoc basis saves your time and money and increases the first-visit effectiveness.
For example, temperature sensors in HVAC equipment can monitor the airflow efficiency and can react to low airflow conditions by sending alert to the system for filter maintenance or replacement. Similarly, sensors in solar panels connected through IoT can generate work orders as and when required.
Data-driven Inventory Management
Inventory is integral to maintenance function. But even today, most of the companies rely on a spreadsheet or paper-based process for inventory control and management. Such processes cause common inventory management mistakes like:
- Incorrect data entry: manual entry of data leads to misleading information.
- Mismanaged warehouse: often it is not the data entry methods but what type of data being recorded. Since the processes are manual, there is no mechanism to check the quality of data.
- Poor Communication: Poor communication within the organization, especially between office executives and warehouse staff can also lead to erroneous data entry.
In an attempt to avoid these mistakes, companies have beginning to rely on computerized maintenance management software. The software can capture and process the IoT data to provide companies with visibility into the inventory levels.
By using IoT data to predict the inventory levels, including stock-in and stock-out of spare parts in different locations, you can optimize the spare parts stock and control the expenditures on new purchases. Just like you only schedule a visit when it necessary, you only order the new stock when required. It gives you the opportunity to use the free capital more efficiently.
IoT data is useful in making decisions related to asset performance and team performance. Regular monitoring and tracking of the team, as well as assets and greater visibility into the process, enables the management team to set KPIs (key performance indicators) and track the progress.
The management team needs to understand that optimization of a process or even the team performance is not the optimum way to utilize the wealth of data. The key is to drive transformation. A large amount of IoT data can be processed using CMMS maintenance software that you can analyze to find out what is working in the favor and what is not, and then quickly replace the existing process with a new one.
For example, you can see who is the best performer in the team and what is the usual average performance of the team members. Based on the data, you can plan training and skill development programs for field service technicians who are lagging behind. Also, you can develop a reward, recognition, and compensation program for star performers. Similarly, you can plan on replacing the asset that is continuously causing menace and reduce downtime.
Better planning at the initial stage ensure better data. With better data, you get reliable information, which in turn results in enhanced decision-making capabilities. Early implementers of IoT in maintenance have reported extraordinary benefits of visibility, transparency, and efficiency in the process. You too can revisit your processes and check to see how IoT can transform your maintenance management function.
This content is accurate and true to the best of the author’s knowledge and is not meant to substitute for formal and individualized advice from a qualified professional.
© 2020 Bhupendra Choudhary