With the rapid progress of automobile science and technology, the modern automobile manufacturing industry has undergone drastic changes, affecting all aspects of the automobile industry chain, including the chip manufacturing of automobile parts, the integrated development of parts, to the research and development of automobile software, the application of AI model, and the rapid change of automobile, which provides new challenges and opportunities for the whole automobile related enterprises.
Volume and cost reduction are the most discussed keywords in the automobile industry at present.
on the one hand, automobile enterprises compete fiercely with each other, and they constantly compete with each other for all kinds of performance and index data.
on the other hand, it is difficult for enterprises to reduce the cost of making cars.
the more cars they sell, the less they earn, and the car companies are caught in the dilemma of further cost reduction.
Cost reduction may be considered most in the field of vehicle manufacturing research and development, but in fact, in the field of after-sales service is also faced with the need to reduce cost.
With the shortening of the R & D cycle of automobile enterprises and the increasing complexity of vehicle structure, there are more and more software faults, and fault diagnosis is becoming more and more difficult.
Traditionally, it is difficult to locate and solve problems by capturing some data temporarily through some after-sales fault diagnosis instruments.
It is difficult to improve the efficiency of after-sales maintenance.
How to achieve intelligent diagnosis service for intelligent vehicles is a problem that every automobile company must consider.
As a high-tech enterprise providing automotive software services, Etherford, when it was founded, focused on automotive OTA business, facing the trend of automobile motorization and software, and creating a standardized and secure vehicle networking eSync service platform.
with the gradual deepening of cooperative car companies, the company found that relying solely on the technical capabilities of OTA can not improve the overall efficiency of digital operation and management.
That is, OTA can only be the way to solve the problem, but how to locate and analyze the problem can not be solved by OTA.
Need an important technology, intelligent diagnosis technology, through intelligent diagnosis technology to collect all kinds of vehicle data on demand, continuous collection to find the problem, locate the problem, and solve the problem.
To quote the McKinsey report, the two major technologies that will bring efficiency and cost reduction to the automotive industry in 2030, OTA updates ranked second, while predictive maintenance ranked first.
The picture is from McKinsey’s 2022 Automotive networking Service Analysis report, so what is automobile intelligent diagnosis technology and what intelligent diagnosis needs as the basis, according to the analysis of Etherford, at present, the remote diagnosis technology in the automotive industry is generally divided into five stages: basic fault alarm, fault data analysis, predictive diagnosis, machine intelligent learning, model ecological transaction.
Most automobile companies have completed the construction of the basic system of the first stage and the second stage, that is to say, through the construction of TSP or remote diagnosis platform, the vehicle has the ability of remote diagnosis, and the remote online diagnosis and data acquisition can be realized as needed.
The carrier of collecting information can be in many forms, such as the fault code and data flow information of parts included in traditional UDS diagnosis, or some log files, audio or video of software system.
The realization of these capabilities is helpful to the accurate analysis of vehicle fault analysis.
With the ability of real-time or continuous data collection, we need to create a failure fault model for each module of the automobile company, which should not only deal with the reverse modeling of the later data, but also need to carry on the analysis of forward design, which is helpful to provide the accuracy of the fault model.
Through the construction of a data model to accurately describe the specific parts of the vehicle or the overall behavior of the vehicle, by obtaining accurate data and comparing it with the data of the fault model, the safety and reliability of automobile parts can be ensured.
With the improvement of the maturity of the fault model, it can often bring accurate predictive service experience for automobile enterprises.
The development of the model should rely on artificial intelligence technology to simplify in the later stage.
Through the fusion calculation of multiple models to locate more complex software system faults.
When the construction of these data models is more mature, it can provide guidance for the follow-up parts research and development and automobile manufacturing from another convenience.
In order to realize the back-feeding parts supplier of the model.
Taking a car company that Etherford has cooperated with as an example, through the data of specific parts collected by the remote diagnosis platform, the training and development of predictive services are completed, and the potential fault problems of each car are timely and accurately pushed to the APP mobile phone of the user owner, so as to obtain a satisfactory after-sales experience.
This change is also reflected in the field of commercial vehicles, if commercial vehicle users can learn about the situation of the vehicle through remote diagnosis services, and carry out preventive maintenance and maintenance of important parts such as transmissions, suspension and chassis systems, it can effectively reduce the risk of shutdown and other losses, and minimize the possibility of failure through predictive and planned advance maintenance.
Through predictive services, car companies can provide comprehensive services for car owners.
Through vehicle inspection or on-site service, ensure that user owners can enjoy VIP-style service experience.
Similarly, through intelligent diagnosis technology, car companies can quickly deploy maintenance outlets overseas and reduce their dependence on maintenance technicians through the use of intelligent diagnosis platform, which is also the key way for many car companies to face overseas markets.
Etherford is currently cooperating with a commercial vehicle customer, and the follow-up will focus on the rapid after-sales capacity building of overseas maintenance through remote intelligent diagnosis technology.
At present, many automobile companies and parts suppliers have carried out the application of intelligent diagnosis technology, such as BMW and ZF, have carried out the research and development of intelligent diagnosis technology, together with partners to explore new ways of cooperation, including digital collaboration.
By sharing data and working methods among partners, and making full use of the convenience brought by digital technology, a new after-sales ecosystem is expected to be established.
At present, Etherford has been working with a number of mainframe factories to implement intelligent diagnosis projects.
at present, the market demand for intelligent diagnosis is gradually increasing, around intelligent maintenance, rapid maintenance, Etherford provides a complete set of solutions to better serve the car factory.
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