Compared against the development of visionary new automotive electronic systems, such as intelligent highways and driverless cars, documenting designs and repairing faulty vehicles seems unglamorous. But in fact, documentation of vehicle electrical systems is a slow, costly and error-prone task; and speeding fault rectification saves money, reduces commercial vehicle downtime, and enhances brand image in the eyes of the customer. So, actually these unglamorous activities have rather important commercial impact. This article examines new technology to improve the process of both documentation and troubleshooting.So what’s the problem?
We all recognize that vehicle electrical systems have become very complex over the past decade or two, driven by the huge growth in vehicle electronics, including embedded software. The vehicle’s electrical system distributes power and signals around the vehicle, acting much like the central nervous system of the human body. As the number of electronic systems has grown, so has the number of signals and hence the complexity of the nervous system. For regulatory reasons this nervous system must be accurately documented, usually via schematic diagrams, wiring lists, location views, and the like. Indeed, creation of complete documentation can be on the critical path for shipping a new vehicle.
It might be possible to keep up with the growth in electrical system content by adding documentation staff. But actually the challenge is more difficult than it initially appears for two reasons. First, electrical systems suffer a very high rate of change as designs are improved, new features added, components upgraded, and so forth. Second, multiple options offered to the public generate a huge variety of possible electrical configurations, each of which must be documented.
Without substantial automation it becomes either very costly or downright impossible to create and maintain correct documentation. This in turn can lead to legal risks: For example, what happens if an accident occurs because a vehicle has been incorrectly serviced due to out-of-date documentation?
But the task goes beyond solving the documentation creation challenge. Unfortunately, vehicle electrical systems can be unreliable: Fuses blow, terminals become corroded, grounding studs fail, etc. Although fault diagnostic systems continue to improve, in a noticeable proportion of cases, fault identification is down to a human technician—pouring over that documentation. With system complexity high and configuration complexity even higher, the unfortunate technician needs some help.
Increased electrical complexity makes troubleshooting difficult.
And again there is a business issue
Automotive service organizations (i.e. dealers) are normally franchised networks. Speedy fault identification is important to their profitability, so they will pressure vehicle OEMs to provide a very efficient environment for their technicians.
Perhaps more important is the experience for the end customer. Few things are more frustrating than a long wait for a vehicle to be fixed, except perhaps a return visit to the garage because the original repair did not cure the problem. This in turn impacts brand image, a subject of vital importance in the competitive automotive market. And for commercial vehicles such as heavy trucks, delivery vans, and taxis, excessive downtime has a very direct revenue impact.
Given the importance of accurate documentation and rapid fault diagnosis, it is surprising how little technology has been applied to the task. Although processes vary somewhat, it is all too common for electrical system documentation to be manually re-created from design data, with all the cost, accuracy, and timeliness issues that entails. Automation is often restricted to drawing aids and content management systems. And as for trapping as-built rather than as-designed data—forget it!
Just as bad, the service technician’s environment usually amounts to little more than electronic paper—and sometimes even real paper! Documentation is static, hard to navigate, and not configuration-specific. No wonder troubleshooting doesn’t always go according to plan.
Better technology is needed, both for documentation creation and delivery and for the service technician end user. Fortunately this is now becoming available, not only via one-off custom developments but also via standardized, commercial software that can be configured and then built into a larger environment.
Documentation creation and distribution
The key here is to re-use engineering design data directly, ideally embellished or modified to reflect the vehicles that are actually built. Automating design data re-use solves the change management, accuracy, and timeliness challenges at a stroke—providing the design process is itself well controlled so accurate data drives the documentation process. Creating accurate electrical design information is relatively straightforward now that software tools are available that focus on data rather than drawings, because powerful validation and consistency checking are possible.
To re-use this design (or manufacturing) data automatically for documentation and troubleshooting requires quite a bit of technology, however. Most important is a rich model that captures all aspects of the design data. A sophisticated data model allows many useful manipulations to be automatically performed, for example automatic creation of supplementary artifacts such as equipment lists and wire lists.
A second example of data model leverage is automatic re-partitioning, perhaps to remove the need for confusing off-page cross references. Another example is behind-the-scenes linking of data from adjacent domains: Object matching technology can crawl over related information to create links with diagnostic procedures, 3D models, location diagrams, fuse box diagrams, and the like. Just these three examples represent huge documentation-creation time savings, as well as improving quality by minimizing human intervention.
A further aspect of data leverage solves the configuration complexity challenge. If the electrical data model captures option configurations, this can be linked with a vehicle configuration database (often based on vehicle identification number (VIN)) to allow push-button creation of configuration or even vehicle-specific documentation.
Finally, technology to automate transformation of graphical content is needed to support tasks such as diagram synthesis, re-layout, symbol replacement, language switching, and change memory. Applied together these technologies can substantially automate rapid creation of accurate, valid, vehicle specific documentation compliant with both regulatory and practical demands.
Engineering data from multiple domains can be automatically repurposed for documentation and service.