Asset performance management (APM), like manufacturing itself, is evolving to leverage the digital technology associated with Cloud, the Industrial Internet of Things (IIoT), Mobility, and Big Data and the associated Analytics. This overall industrial shift has been referred to as both Industry (or Industrie) 4.0 or Smart Manufacturing. Accordingly, LNS has set forth a vision of how APM must evolve in support of these highly digital, capable manufacturing assets which we call APM 4.0.
In my last post, I differentiated between the idea of a Digital Twin as it applies to products and as it applies to Smart Connected Assets. This leads to the point where we believe that a definition of what is the functionality a Digital Twin must have to be useful in the context of APM 4.0 from the LNS perspective is appropriate. Several areas of differentiation exist between assets that are production related versus products designed for consumer use:
- Life of the asset/product
- Variability in configuration during service life
- Complexity of the asset/product
- Service versus replacement decisions
Production Asset Life Measured in Years – A Twin Must Last as Long
Assets used in manufacturing or support of infrastructure and transportation have life spans measured in years to decades. Many production plants have useful lives of 25 years or more while infrastructure assets such as a hydroelectric dam might have a service life of 100 years or more. Products targeted to the consumer market, even appliances and vehicles, typically have a life expectancy of five to ten years for the most part with consumer electronics often replaced annually. The implication for the Digital Twin of these very different life spans is significant. For physical assets, it means the twin must be accessible for that entire life span, and newer technology associated with Digital Twins must scale backward for compatibility
Long Life Means Maintaining the Evolutionary Record
This long life means that the historical record of the twin must be maintained to facilitate accounting and reporting for as long as that asset is in service. In certain industries, the actual configuration of an asset train must be part of the traceability and genealogy record of the products produced on that line. This means the twin must have not only a time synchronized history but a product linked history.
The data storage associated with this long life and structurally complex twin all but demand Cloud storage. The ability to have the as-maintained bill-of-material (BOM) immediately accessible to both operations and maintenance staff means the twin has to be in lock-step with the actual asset, not updated asynchronously. The US military B52 bomber is an example of this, where it is often quipped that for these 50-60+ years old aircraft the only original component on those still flying, is the nameplate, everything else having been replaced over the lifespan of each airplane.
Production Asset Complexity is a Given and Singularity is Common
The smart products market is largely consumer-oriented, with many variations on each model. Products range from quite simple to moderately complex. In an industrial setting, production assets and the infrastructure to support them are just the opposite – they often exist as unique objects, and in the case of a large plant like a refinery or power station, each one can be incredibly complex. Also, many times the production complex may have multiple moving elements such as a mine or rail system with assets that are mobile and repositionable. This means that as each asset is complex and unique, so too must the twin be unique and complex.
The implication is that the construction and maintenance of the twin must be automated and affordable since the cost can only be spread across that asset, not an entire production run. It also means that the performance data for the asset, in the form of simulation models, must be tuned to the specific asset and maintained in its as-operated state.
The Digital Twin Must Embrace Financial Models
Unlike most consumer smart products that are disposable or only marginally repairable, obviously, things like automobiles are an exception, production assets invariably are designed for long service lives with repair processes part of the expectation of the assets' history. This means the Digital Twin model of a production asset must incorporate adequate financial models to facilitate the simulation of alternative operation versus forecasted repair costs.
An example would be to simulate wear under different operating conditions and analyze the total cost to maintain in each scenario to facilitate making the optimal operational decision. Ultimately, this extends to modeling within the twin; the service versus replacement cost scenarios and the disposal cost simulations. So, the APM 4.0 Digital Twin is going to need access to a very rich financial model as well as the operational performance and service life simulations.
The Production Asset Digital Twin is Community Property
In the consumer world, the Digital Twin often remains the property of the manufacturer. While they may share it with the consumer as part of the delivered product or as a service, the twin really is vendor centric and the user has little need to use the twin except when the AR/VR experience is the product. This is very different in the production asset environment where dozens of parties may have a need to interact with the Digital Twin. Maintenance staff, from many different disciplines, operators, financial analysts, production engineers, and process designers all have a need to interact with the twin. This means the Digital Twin will be adding far more value, but it will also have to serve multiple masters.
Realistically this next evolution of the Digital Twin for physical Smart Connected Assets is going to take several years to grow into full capability and for users to understand how to best utilize twins to improve their performance. Smart users will understand that by starting now. They must grow their skills and knowledge in parallel with the market as twins evolve to meet the complex needs. These users will be in a better position than those that delay and wait for a stable future. The reality is it will never come as technology keeps providing more tools and power to aid us in our pursuit of Operational Excellence.