The Impact of Poor CMMS & EAM Data Quality on IIoT Initiatives

The industrial Internet of Things (IIoT) holds the promise of transforming how traditional asset intensive companies do business. For asset-intensive businesses there are major opportunities to improve asset performance, offer new services, improve operational efficiency, and pioneer new business models. Companies are under tremendous pressure to adopt IIoT and those who fail to do so or lag behind will be at a serious competitive disadvantage.

The digital transformation to IIoT requires more than adopting new technologies. It requires changes to people, processes and to information management. Without an effective system to manage asset information you will not be successful in adopting IIoT.

 

Some of the Challenges to IIoT Initiatives Posed by Poor Quality Asset Data

 

Lack of Prioritization and Planning

  • Too much IIoT information is generated without appropriate planning and prioritization resulting in too many alerts and unnecessary work orders being generated without the information required to use them effectively

 

Disconnected Systems

  • Manufacturing, production, DCS, EAM, CMMS and other systems are disconnected resulting in multiple asset registers needing to be maintained and getting out of sync
  • There is no single system that provides a 360 degree view of the information available across systems for a given asset making it difficult to make good decisions and optimize operations, production and maintenance

 

Inefficient Productivity and Reliability Programs including Predictive Maintenance Programs

  • Reliability programs like reliability centered maintenance (RCM), Failure Mode & Effects Analysis (FMEA) require a good asset hierarchy with accurate and complete equipment classifications and attributes to be effective
  • IIoT and predictive maintenance initiatives require an accurate asset hierarchy and intelligent analysis to determine which equipment could benefit most from IIoT and predictive maintenance efforts and to accurately measure impact on maintenance productivity and downtime

 

No Process for Updating Asset and Maintenance Information in Connection with an IIoT Implementation

  • No ability to prioritize where IIoT should be implemented first
  • No ability to stage and visualize all the asset data changes required to implement IIoT
  • No ability to view all of the information in one place required to understand how IIoT information relates to existing maintenance processes
  • No approvals process for approving large scale changes to EAM or CMMS asset data required in connection with IIoT initiatives

 

Many Companies Lack the Asset and Maintenance Master Data Foundation to Implement IIoT Effectively

Basic EAM and CMMS data quality issues negatively impacting IIoT readiness include the following:

  • Missing equipment and missing key information about equipment
  • No standard naming conventions for equipment
  • Unclassified or improperly classified equipment
  • Asset Hierarchy not organized to effectively standardize the collection of performance, FMEA and other reliability information required for IIoT
  • Inaccurate criticality making it difficult to prioritize the implementation of IIoT
  • Missing Task Lists, incomplete task lists, poorly structured task lists, task lists missing key information like how long the task will take which will waste wrench time and make it impossible to plan and schedule effectively, track time and improve maintenance operations and get the intended benefit from IIoT alerts and information
  • Missing Preventive Maintenance Plans, too many PMs, or inappropriate PMs for critical equipment resulting in lower maintenance productivity and inability to focus on critical equipment and tasks and inability to get the intended benefit from IIoT alerts and information
  • Missing Class and Characteristics for Equipment, Locations, Materials and Task Lists resulting in the inability to use IIoT data effectively

 

Some of the IIoT Challenges for Equipment Suppliers

 

IIoT also offers equipment suppliers the opportunity to sell additional parts, service contracts and IIoT condition monitoring to asset-intensive customers. However, in order to effectively roll-out these initiatives suppliers need a system to manage asset information in their install base so that they have the accurate asset data they need. Without an accurate view of the as-maintained status of equipment in their install base they will not be successful.