Your Blueprint for CMMS Optimization
By seeing what could be, asset management professionals and CMMS practitioners can discuss applicability, benefit, and level of effort. Otherwise it’s hard to discuss the ideal model when you don’t know what it looks like. This collage shows advanced processes, strategic roles, and power features, which all together, enable an organization to maximize their investment in CMMS technology, while also hopefully achieving return on asset optimization.
A Work Management Process That Uses Advanced Processes
Not every organization will have the requirements to perform all of the steps shown. But by having this blueprint for CMMS optimization, leadership can create their own road map for success. For example, if a work order is thoroughly vetted, it might help:
- Verify urgency.
- Eliminate duplicates.
- Ensure the right asset is selected.
- Improve the problem description.
- Identify if functional failure is present.
- Flag work as a safety issue or high risk.
The reviewer (sometimes called gatekeeper) would also enter lead craft along with a rough estimate. All of the above improves data quality and analysis, which leads to better decision-making capabilities.
Common Work Order Initiation Mistakes—Which a Gatekeeper Would Catch
Originator Submits Duplicate
Sometimes a duplicate work order can be programmatically caught if the same asset number and problem code are entered up front. However, oftentimes the problem code is not filled in, or it’s given a different value, but it’s still a duplicate issue.
Work Order Priority
A work order priority should reflect the relative importance to all other work in the backlog. Unfortunately, this is often not possible because the originator seldom has familiarity with the existing backlog.
Level of Urgency
All that is really needed is a level of urgency from the requester—not a work order priority. The choices would be emergency, urgent, and routine. Emergency would require immediate dispatch, and urgent would require attention before the end of next shift. Anything marked routine would be properly planned and scheduled. Further, the gatekeeper would apply a priority value (for this routine work) that fits the backlog.
Work Order Description
This is really the problem description. Unfortunately, the originator sometimes states, “Replace this pump,” which is an action. It is preferred that they just say what the problem is.
Sometimes the requester does not know what the asset is, which means they choose an incorrect value. Or worse yet, this asset is not in the CMMS equipment register, thus it needs to be added.
Sometimes the operations and maintenance technician does not indicate whether or not a functional failure has occurred. This is important because failure data hinges on this entry (when YES).
Originator Name and Contact Information
It is important to know the originator’s name, so that the gatekeeper or planner can ask questions. Further, the repair technician may want to make contact.
Data Accuracy Is Important for Many Reasons
Early vetting ensures accuracy for the entire work order life cycle. Data accuracy is extremely important as this also prepares the backlog for advanced processes including automation. All together, early vetting does this:
- Improves overall backlog data quality and reporting, e.g., backlog growth trending.
- Prepares the backlog for accurate risk ranking as opposed to casual prioritization.
- Enables accurate work scheduling using automated resource leveling.
- Provides the planner with a selection set for what should be planned as opposed to guessing.
- Accurate data also means the leveling program can be run numerous times by the scheduler to build a weekly maintenance schedule, since it is automated.
Work order completion also requires accurate data—called transactional data. Examples include work order status updates, actual man-hours, parts used, service costs, failure mode, and work order feedback. Without this type of data accuracy, it is impossible to implement automated scheduling and chronic failure analysis.
Trusting the Technology and the Supporting Roles
It is natural for humans to not trust what they cannot see and touch. For example, in the case of an airplane pilot learning to become instrument-rated, it is initially challenging for them to trust instruments when it is pitch dark outside and the plane is bouncing up and down. Similarly, it is also hard to trust a CMMS database when so many people have update responsibilities. Further, you are only seeing one record at a time as opposed to trending data.
Trust is required throughout the process. Examples of this trust are shown below:
- The gatekeeper must trust the requester that they are entering a valid request.
- A scheduler must trust the craft estimate, craft availabilities, and estimate to complete (ETC) values.
- A scheduler must also trust the risk-based ranking, which affects the processing order.
- A maintenance supervisor must trust the weekly schedule as being accurate.
- A technician must trust the daily plan and the safety-hazard instructions, e.g., lockout/tagout.
Maybe the issue is not trust so much as it is just a lack of valid data. For example, the backlog could have poor prioritization and very few formally planned jobs. In this situation, it is common to find a maintenance supervisor sitting with the scheduler, and together they manually create the schedule. The supervisor will enter a rough estimate on the fly where missing. The scheduler then, trained in the graphical user interface drag-and-drop tool, will place the work order under the day of the week and make the assignment (as told by the supervisor).
This is called subjective selection. It is also a long, tedious process subject to many errors. Most importantly, this subjective selection process is only performed once, meaning it cannot be done again before final issue. Further, this process is only for one craft at a time, where an automated resource leveling program would handle multiple crafts. Plus, it could be run again during the final review meeting if alterations are made.
Vetting Is the Answer
Personally, I would trust the technology and require a gatekeeper role to verify the data and enter the rough estimate to enable automated scheduling. The importance of the gatekeeper cannot be overstated. I would even hire a gatekeeper before I hired the first planner. Every organization using a CMMS complains about data accuracy, but few take action to fix the problem. Therein, it is beneficial to have a data quality plan which identifies all CMMS update roles, fields they update, and the importance of each.
Reviewing the Process
Work Order Initiation
Some organizations have a service request which precedes the work order. This screen is minimalistic in design, making it simpler for the originator to submit. In addition to corrective work being submitted, there is also automatic preventive maintenance work order generation. Plus, there can be condition-based maintenance as submitted by the technician. All of the above is reviewed by the gatekeeper or call center. Emergent work is dispatched; the gatekeeper evaluates functional failure. In addition, they enter lead craft and apply a rough estimate. Once the gatekeeper finishes the review, then an automated risk-ranking can be applied.
Some organizations have a defect elimination program with various teams looking for and eliminating defects. A significant finding would result in an individual work order.
Before the CMMS goes live, there is some setup required, such as work types, priority range, work order status values, failure code libraries, and commodity codes. There is also foundation data, which must be loaded with things such as locations, assets, item master, and inventory balances.
Planning and Scheduling
As mentioned earlier, the automated risk-ranking program runs after the gatekeeper has completed review. This program runs nightly and inserts a numerical ranking to each work order in the backlog.
At this point, a resource leveling program can be run, which compares estimates against availability using the order provided by risk-ranking. Leveling stops after enough work for a week is processed. This output is then presented to the planners to formally plan the work. The weekly maintenance schedule is reviewed before issue and then released for the week; supervisor creates daily plans and conducts shift briefing.
Major project scheduling can be accommodated using a work-breakdown structure for budgets (and scope tracking), CMMS work orders for actuals, and scheduling software for percent complete. This integrated design allows for a project cost report to be issued within minutes of project completion.
Work Order Feedback
Work order feedback separates the best from the rest. This type of communication from the working level supports continuous improvement. It is the maintenance strategies which are refined over time that ensure the right work is done on the right asset, at the right time, by the right resource.
The failure mode is identified in three pieces: failed component, component problem, and cause code.
Run Bad Actor Report
This report is truly the endgame, and it’s called the bad actor report. The reliability team, for example, would sort the output by average annual maintenance cost divided by replacement cost to get a top 10 list. Then the team lead would dynamically select one asset, at which point a pie chart would show failed components, component problems, and cause code. This failure analytic enables the team to focus on recurring failures at the failure mode level, and then to take action to eliminate recurrence or mitigate effects.
Create a Living Program
By configuring the CMMS to store reliability-centered maintenance analysis results, the reliability leaders can create a living program which is easily refined over time.
Any work order with a functional failure requires a failure mode at job completion. A script then performs instant comparison of the work order to the reliability-centered maintenance application, sending a notification to the reliability engineer.
If that asset or failure mode was not yet entered, then the reliability engineer could review and approve a new entry along with the suggested maintenance strategy. At this point, the preventive maintenance coordinator would be notified of a new PM-job-plan requirement.
If that asset and failure mode DID EXIST, then the reliability engineer would perform a different type of analysis.
- A work order matrix is mentioned in the above discussion. This design would be a new application within the CMMS to create a numerical ranking. There would be a two-dimensional matrix containing work types across the top and equipment criticality on the left side. Each intersection would have a numerical value where the most important work would have the highest value. A script would read the entire backlog each night and apply a fair ranking. As stated, this ranking would be used by the leveling program to help the planners identify what work should be planned next.
- There can also be a new tab on the asset application called Business Risk Exposure (BRE). A review team would answer questions such as likelihood, consequence, and risk mitigation capabilities. This BRE value could be used in the work order matrix.
- The BRE is also used to indicate what assets should receive reliability-centered maintenance analysis versus preventive maintenance optimization. The lowest grades would usually apply original equipment manufacturer recommendations.
Imagine Future Perfect
CMMS utilization can be much more than managing assets and creating work orders. Rather, it can be about taking charge of your future to make better decisions. All that is required is your imagination. If you are able to tailor your CMMS in support of asset management concepts, then you will be taking a significant step forward toward operational excellence.