Organizational data has become an essential tool for industrial manufacturers that want to remain productive and profitable. New applications coming to organizations offer the ability to leverage critical plant data interconnected with cloud-based technologies for process improvement, greater reliability, better control, enhanced training, and much more. Even if an organization is not currently moving toward cloud-connected applications and plant data analytics, that move is likely on the horizon because of the potential for productivity gains that can be realized by combining systems to augment and automate workflows.
As with any system, the highest-quality results are possible only when starting with the highest-quality input. To achieve the best results from new cloud-connected applications coming to plants, organizations must ensure that the data in the CMMS is “clean.” Cleansing CMMS data to enhance its reliability today will not only improve the organization’s current performance but also will ultimately make it easier for plants to adopt essential emerging technologies.
To keep the CMMS reliable, it is important that companies keep close tabs on how these systems are managed. A recent Emerson survey suggests that while 85% of users rate their CMMS as “very important” or “critical” to their business goals, 75% also rate the effectiveness of their CMMS as “poor.”
One reason for the high percentage of users reporting an ineffective CMMS is that common problems come up across organizations when managing these complex systems. When companies don’t take proactive steps to ensure standardization, cleansing, and enhancement of CMMS data, data drift can easily result in disorganization that spirals out of control. To avoid or counteract this CMMS degradation and prepare critical data for migration to a cloud-ready environment, organizations should focus on six common master equipment list (MEL) principles that, if not enforced, contribute to data drift in CMMS systems.
1. Set formatting standards and enforce them. Ideally, standards for data entry in the CMMS should be defined when the system is set up. Unfortunately, in practice, these standards are rarely defined and even more rarely enforced. As a result, it is not uncommon to find misspellings, inconsistent use of abbreviations and special characters, and duplication across multiple entry fields. This lack of standardization can quickly lead to duplicated entries and incomplete asset data, which will compromise the integrity of any reports the system produces. Ensure that users know the requirements for data entry, and enforce them using rules in the CMMS where possible. In addition, time spent removing duplicate MEL entries is time well-spent.
2. Identify incomplete and inaccurate MEL entries. Plants rarely fail to capture the most critical assets across the organization; however, smaller, less-critical assets are easily overlooked, especially during hasty additions or replacements. Start by ensuring that all assets identified in the CMMS still exist in the field. Next, check to make sure that all assets in the field are recorded in the MEL. Once the MEL is reconciled with the current plant configuration, cross-reference the asset nameplate and attribute data to ensure that it matches what’s installed in the field.
3. Confirm the location and equipment hierarchy and criticality structure. It is essential to ensure the consistency of location and equipment hierarchies throughout the site as well as across the organization. Develop clear definitions for each level of CMMS hierarchies, and confirm that identical process lines have matching hierarchy structures. Also keep a close eye on individual records to ensure that they have not been orphaned when parent records haven’t been assigned. Keep hierarchies reasonable. Watch for entries with too few or far too many levels.
4. Be on the lookout for limited and poorly organized data. Poorly organized data quickly renders CMMS entries unusable. Check all MEL entries to be sure that enough detail exists to determine the equipment type for each asset. In addition, ensure that equipment subclasses are used to accurately describe the service that each piece of equipment performs. Confirm that the number of total work orders and related costs have been recorded accurately and that failure classifications, along with their problem, cause, and remedy codes, are properly assigned and sufficiently detailed to be useful.