The complexity of sophisticated systems today can be staggering. A form of maintenance intelligence could manage the complexity of systems to make operators and technical support staff more effective. With that said, consider this hypothesis: The capabilities of COTS information technology tools today could transform maintenance effectiveness on orders of magnitude beyond what is currently being done. The key lies in data resources that are readily accessible.
What does exist for many systems is some form of logistics regarding parts replacement frequency or reliability and maintenance ticket tracking. What doesn't exist or is difficult to extract is machine digestible data of a system's inter-connective relationships. This is where the S1000D is visionary in developing wiring modules that can provide such a data silo. But what can you do with all this data?
The S1000D wiring module provides for more than just inter-connectivity information, it also provides hierarchical relationships of components. Effectively the S1000D can capture deeply nested information that is crucial in understanding a system's inter-workings. This deeply nested insight from S1000D wiring modules can make software much more aware of a system's interactions than a human being's ability to understand a system no matter how experienced the expert is!
By realizing the potential of wiring modules the justification to adopt a IEWD (Interactive Electronic Wiring Diagram) solution is much more than lowering costs to maintain drawings or in aiding a technician or engineer to trace a wire on a diagram when troubleshooting a system. The type of information an S1000D wiring module can provide allows for the ability to sense relationships across multitudes of diagrams and therefore provide an infrastructure that can now be integrated to other information systems or databases. E.g. populating meta data from OEMs' data-sheets to the wiring terminals of components potentially allows automated monitoring of a system's operational idiosyncrasies through data mining, no wire sensory technology needed. Applying data analytic technologies that can correlate to component interconnections is a windfall benefit of an IEWD solution!
We can go further with this idea; A powerful and effective IEWD solution can easily integrate to logistic and maintenance ticket intelligence data silos that cite component reliability, intermittent behaviors and behavioral characteristics related to operational stresses or interactions. Let's not forget maintenance forums whose data can be integrated as well, pulling in years of experience of human expertise. This gives the IEWD tool the ability to discover implied sources of problems immediately! Imagine a technician or engineer examining  a power or signal terminal on an assembly and because the IEWD tool can be integrated to data intelligence cubes of logistic failure rates of components and/or maintenance ticket data, it can sense problematic issues that exist in some deeply nested connection in some unrelated system. By associating various other data sources to the wring level prognostic capabilities could be developed. Consider this scenario: A power assembly is known to suffer from surges intermittently and the OEM hasn't resolve the issue yet. Because all direct and indirect wring that connects to the power assembly are stored through the wiring modules all problem areas can be known by performing a sophisticated query, giving technicians and operators a heads up as to what can go wrong before it happens! Effectively what is created through these synergies of data resources is a derived knowledge base that can evolve and learn! The machine literally becomes smarter and more capable to aid troubleshooting and lower maintenance costs.
Also think of situations where aggregate assemblies composed of sub-assemblies because of their complexity were simply replaced can now be evaluated with finer detail to where the actual problem sub-assemblies and/or components on sub-assemblies can be identified. These kinds of novel capabilities from data integration and analytics reduce costs for storing and replacing parts dramatically and enhances maintenance solutions lowering MTTR (Mean Time To Repair).
Yet there is further potential to integrating wiring data to other intelligence data and that is it opens the door for automated or A.I. assisted troubleshooting at the wiring diagram level. Granted this would be of a R&D exploratory venue for now but having the data infrastructure in place means deep learning technologies can be applied. The questions of how to use Artificial Neural Networks for maintenance analysis could be explored.
Extracting S1000D wiring modules from any system's current CAD or diagram resources does require specialized tools. These specialized tools aren't usually a part of the average tech pub organization's suite of software. However, COTS solutions are currently available on the market that can literally extract assembly and sub-assembly relationships as well as circuit inter-connectivity between components from static schematic diagrams and link circuits across multitudes of diagrams. Using such a tool suite builds the data silo needed to integrate maintenance intelligence. The project itself is not as monumental an effort as it might appear from the complexity of systems such as military and commercial aircraft or naval vessels with the right tools. In fact systems composed of hundreds of dense wiring diagrams can be done in a few months, this includes managing associated content media for every described component in the diagrams as well! These tools can also be applied to other types of schematics such as pneumatic and hydraulic systems and integrate those systems to data maintenance resources too.
The logistics data sources, maintenance ticket and forum resources as COTS tools do exist and most organizations have them. Most COTS data integration tools can perform the ETL (Extract Transform and Load) tasks needed for some data sources required from OEMs to the wiring modules. It is common for the DoD and other organizations to have technology assets such as SAP, Oracle, and MS SQL as data silos. Creating share points for such data assets is already apart of those existing COTS information technology infrastructures and is implemented as a SOA (Service Oriented Architecture). Those COTS tools also have the deep learning capabilities as well. As stated earlier an effective and powerful IEWD can easily integrate to SOA resources.
I will conclude with this note: Some in the industry view the IEWD as a nice to have tool but not a critical tool for maintenance. To those I argue that a IEWD with a S1000D wiring module capability is the corner stone that will provide the crucial data infrastructure that integrates other logistic and maintenance data that will pave the way to more effective system maintenance and enhancements solutions. Solutions that can be implemented immediately and whose cost benefits out weight initial costs of the IEWD.
Frank Lombard is the CEO of Atlas Dynamics Corp a leading provider of Interactive Electronic Wiring Diagram production tools.