What Good Is The Data If You Don’t Know What To Do With It?
As maintenance, reliability, and asset management professionals, we are in an amazing time. We can collect virtually limitless amounts of data on the condition of our assets. With this data, we can determine the exact condition of the assets, predict when the next failure is likely to occur and how it will occur. Besides, with all of this data, we can move to prescriptive maintenance, where the maintenance actions are determined based on the asset condition, not a predetermined strategy. I’ll touch more on prescriptive maintenance in next week’s post.
The ability to have access to and the ability to collect all this data is called the Internet of Things. The Internet of Thing is essentially the “interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.” With all this information available, and access to advanced data analytics and machine learning, no wonder maintenance, reliability, and asset management professionals are excited about it. But what good is the data if we don’t know how to use, or worse, can’t execute the right maintenance at the right time.
Without The Basics
So you have IoT technology and are collecting the data. Maybe your organization is using the data to determine the condition of the assets. This use of the IoT is relatively new to your organization and was implemented in an attempt to improve on the high cost of maintenance and low asset performance. Senior leadership fully supported this endeavor as it seemed more in line with today’s technology and could be quickly and easily implemented, with a great ROI.
Based on the data and analytics, a warning is raised about the rapidly deteriorating condition of a critical asset. The work notification is automatically triggered in the CMMS and is ready for the work management process. But, the work management process is not operating as it should be and as a result is a major contributor to the high cost of maintenance. The work notification goes unreviewed and not acted upon for 3 days, and the critical asset’s condition continues to worsen. Finally, a planner sees the request and begins the planning the repair.
The planning is completed, and a parts requisition is raised. The requisition is automatically routed in the CMMS to the storeroom. The lead time in the CMMS for the part is 5 days, so the staff order it as usual (when in reality the lead time is 20 days). The part is finally ordered after 4 days from when the requisition is received. By this point, the critical asset is almost at a failed state. The part is finally received at the site but sits in the receiving area for 2 days before the planner is made aware. At this point, the planner schedules the work for the next opportunity which luckily is the next day. At this point, the finally ready to execute 29 days after the initial request was made. Right before the maintenance staff get ready to shut down the asset for the repair, it shuts itself down due to a catastrophic failure…
With the Basics in Place
Now, take the above scenario, but instead, the organization already has the cost of maintenance under control and is achieving good asset performance. By having these two indicators in place, it would show that the basics of maintenance are in place and functioning well. Senior leadership still supports the use of IoT but realizes that it will build upon the foundations that are in place.
Once the notification is received in the CMMS, a planner begins the work management process almost immediately. The part requisition is reviewed by the storeroom the same day, but the true lead time is known at 20 days. Knowing this, the storeroom and site leadership team determine that it would be best to expedite the spare part in. The part arrives in 10 days, and the planner is notified immediately. The work is scheduled for tomorrow. In total, the time from when the notification was sent out until the work is ready to execute in 11 days. A far cry from the 29 days in an organization that does not have a good work management or spares management program in place. The repair is executed, and the asset is restored to as good as new condition without any impact on the operation.
Comparing these two scenarios above, it would reason that IoT is a great tool in the maintenance, reliability, and asset management professionals toolbox. IoT is just that, a tool. And without the basics in place, the tool is not as effective as it can be. If you are thinking about utilizing IoT, be sure to have the basics in place first, or else you will have just have another cost contributor to your already high maintenance costs.
If you are leveraging IoT in your toolbox, please comment on whether you have the basics in place or not and the benefits you are seeing from leveraging this powerful tool. Also, if you are leveraging IoT would it be possible without the basics.
Remember, to find success; you must first solve the problem, then achieve the implementation of the solution, and finally sustain winning results.
I’m James Kovacevic
Where Education Meets Application