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The worldwide automotive trade is within the midst of main adjustments and challenges in opposition to the development of electrification and intelligence. In line with the current statistics launched by a neighborhood auto trade affiliation, the gross sales of China’s gas automobile market have declined for 3 consecutive years. With the intensification of the value conflict, some automotive corporations have even withdrawn from the market. The auto elements producers caught in it are going through the issue of learn how to survive and develop in opposition to the more and more fierce competitors.
Yanfeng Auto International Automotive Technology Co., Ltd. (hereinafter known as “Yanfeng Auto”) is a number one Chinese language automotive elements provider specializing in automotive inside and exterior trim, automotive seats, cabin electronics and security methods. Headquartered in Shanghai, Yanfeng Auto has 9 R&D facilities, greater than 240 factories and technical facilities in 20 international locations all over the world, with over 55,000 staff. Dealing with challenges, Yanfeng Auto’s strategy is to work with corporations like IBM with superior know-how, trade expertise and technical experience to speed up its personal data-driven digital transformation to cut back value, enhance effectivity and scale for company-wide innovation.
Situation 1: Mechanically convert huge exterior normal orders to inside orders with the pure language studying functionality of IBM Watson Discovery
Yanfeng Auto receives an enormous variety of orders from automakers and downstream producers each day, and it beforehand needed to manually convert exterior normal orders to inside orders primarily based on expertise. In every manufacturing facility, it took a mean of 150 minutes a day for 2 workers members to kind the orders manually, accompanied by 15% classification errors. That presents huge challenges for the corporate by way of labor value and effectivity.
Leveraging the highly effective pure language studying functionality of IBM Watson Discovery and the hands-on help of IBM Customer Success Manager (CSM) team, Yanfeng Auto efficiently constructed up an AI mannequin that was skilled with its blended knowledge of structured knowledge and unstructured textual content, masking 180 million historic knowledge, with over 200 permutations and combos. The mannequin has realized the foundations behind the interior orders comparable to normal orders. The AI mannequin helps the corporate notice a completely automated execution course of with out handbook operation, growing the order classification accuracy charge from 85% to 97%.
Situation 2: Understand high-speed transmission of huge knowledge between department manufacturing workshops and headquarters with Aspera Module of IBM Cloud Pak for Integration, establishing knowledge basis for clever stock platform with predictability.
The Clever Manufacturing Division of Yanfeng Auto hopes to work with IBM CSM group to discover the way in which of increase its clever stock platform with predictive capabilities. To drive predictive resolution making and automated recognition, they want a considerable amount of knowledge throughout the corporate for AI mannequin coaching. Nevertheless, the primary roadblock is its outdated approach of information transmission.
To keep up real-time situational consciousness of the elements stock in numerous manufacturing workshops in additional than 240 factories all over the world, Yanfeng Auto must shortly transmit again to headquarters the 1000’s of real-time photographs taken at every plant. Beforehand, the Clever Manufacturing Division used the standard copy and paste technique to switch the photograph information by batches. Because of gradual transmission velocity, huge community delays, and critical packet loss, they needed to manually choose and replica the photograph information by batches and repeat the method a number of occasions. This was not solely time-consuming but in addition made it simple to make errors. On the identical time, if the transmission was interrupted, it couldn’t be reconnected and resume transmission robotically, nor might they customise the transmission velocity, or totally make the most of the transmission bandwidth of the spine community.
With help of IBM CSM group, Yanfeng Auto efficiently deployed Aspera Module of IBM Cloud Pak for Integration inside solely at some point to construct up a light-weight enterprise-level file switch resolution for Yanfeng Auto, which elevated its file switch velocity by 10 occasions, saved handbook ready time, prevented human errors, realized automated transmission resumption and automated community reconnection. With this resolution, Yanfeng Auto now can dynamically configure transmission bandwidth and velocity restrict with out affecting the efficiency of its ERP core system and maximize the transmission effectivity of its real-time monitoring information, laying the info basis for realizing the division’s imaginative and prescient of increase an clever stock platform with predictive capabilities.
Situation 3: Break the operational bottleneck brought on by Kafka, an open-source knowledge extraction device. With Occasion Streams Module of IBM Cloud Pak for Integration, you’ll be able to simplify the method of extremely obtainable knowledge extraction.
Yanfeng Auto has beforehand deployed an open-source Kafka cluster in every department manufacturing facility to extract knowledge from a number of real-time manufacturing knowledge in its MES system and supply them to the MI Kanban (Dashboard) System of every manufacturing facility for question and show. Nevertheless, this open-source system poses a number of operational complexities.
For instance, for every handbook set up, deployment, configuration, improve, and upkeep, it could take days or perhaps weeks and incur an enormous labor value. Furthermore, it was not ready to make sure enterprise-level safety and excessive availability, and it didn’t help pure integration with the core enterprise methods and the widespread manufacturing methods. Lastly, there was no Kafka technical help or after-sales assure, ensuing within the want for ongoing funding in workers coaching and skilled consulting companies.
With the help of IBM CSM group, Yanfeng Auto has efficiently adopted Event Streams Module of IBM Cloud Pak for Integration in considered one of its factories as a prototype for real-time knowledge extraction. The information-generating software extracts knowledge—resembling elements manufacturing shifts, manufacturing portions, demand portions, rework portions, sequencing and different related manufacturing knowledge—from the MES system and sends them to the corresponding knowledge subject channel. Purposes that extract knowledge can use the info immediately by subscribing to the corresponding subject channel of Occasion Streams. The MI Skynet Kanban (Dashboard) system can choose specified desk fields for subsequent dashboard show and early warning evaluation.
By deploying Occasion Streams, the enterprise-level knowledge extraction resolution, Yan Feng can obtain “one-click” deployment, out-of-the-box use, zero downtime rolling upgrades, and at all times have the newest steady model of Kafka. Occasion Streams comes with a graphical operation interface, which requires little extra expertise coaching. It additionally takes benefit of high-security, geo-replication, and enterprise-grade catastrophe restoration capabilities of the product. Furthermore, different functionalities like superior schema registries and wealthy Kafka connectors and extensible REST APIs make it simple to scale. As well as, IBM gives enterprise-level after-sales service, skilled session, and well timed troubleshooting, serving to the consumer to acquire the technical experience they want.
Situation 4: Understand clever manufacturing capability estimation and planning for core manufacturing gear with Determination Optimization Module of IBM Cloud Pak for Knowledge to cut back prices and enhance effectivity.
In auto elements manufacturing, injection molding is likely one of the vital processes. Yanfeng Auto gives numerous automakers with inside elements resembling instrument panels, which require a core gear of injection molding machine to provide. As a result of completely different specs of the instrument panels of assorted automobile fashions, the manufacturing course of requires gear changeovers. For instance, when the fabric is switched from black to white, the gear must be cleaned; when switching from white to black, it doesn’t must be cleaned. Switching from gold to crimson requires different extra actions.
Tools switching is not going to solely contain value, however have an effect on manufacturing scheduling and stock administration. For instance, how do they decide the optimum financial batch dimension of various merchandise whereas decreasing stock prices? How do they stability the capability of a number of machines for a whole yr whereas assembly buyer wants? How can they estimate the capability of the machine to raised modify the plan, maximize the effectivity of the machine, enhance productiveness, and cut back time beyond regulation? How will they make sure that the plan might be applied in manufacturing and that adjustments might be responded to in a well timed method once they come？
Within the context of the continual enlargement and alter of demand for numerous auto elements, and the truth that productiveness and manufacturing assets are very restricted, the standard manufacturing planning technique is predicated on expertise and handbook calculation, which simply causes issues resembling low manufacturing effectivity, excessive stock value, heavy labor burden and extra. All of this might significantly have an effect on the manufacturing effectivity of the corporate, so it’s mandatory to seek out new methods to develop affordable manufacturing planning and scheduling schemes.
After rounds of discussions with consultants from IBM CSM group, IBM Consultants Lab and IBM China Growth Lab, IBM consultants developed a complete and agile resolution for Yanfeng Auto with Decision Optimization Module of IBM Cloud Pak for Data. The answer has two complementary elements—the general multi-machine, multi-month planning scheme and the single-month tremendous scheduling scheme.
The answer helps almost 100 workers in additional than 20 factories to plan the capability of a whole lot of injection molding machines with extremely detailed and particular plans. Every define plan is accompanied by an correct scheduling plan, which is very sensible for follow-up steering for manufacturing. Additionally it is an agile resolution: planning a set of schemes solely takes just a few or dozens of minutes, drastically bettering the responsiveness to future adjustments. If the client wants or manufacturing assets change, Yanfeng Auto can modify the plan at any time. Based mostly on an agile and customary platform, this business-friendly resolution might be simply tailored and scaled to different manufacturing amenities and different related areas.
The IBM CSM group has accompanied Yanfeng Auto on its journey of digital and clever transformation for 2 years: from the preliminary realization of automated conversion of exterior orders to inside orders; from fixing the issue of high-speed knowledge transmission in department factories all over the world to the headquarters; from changing its open-source device with an IBM enterprise device constructed on open supply to simplify its IT operational complexity for high-availability knowledge extraction, to the newest AI-powered options to appreciate manufacturing capability estimation and planning for its core manufacturing gear. From knowledge integration and administration to making use of AI to its enterprise course of and planning, Yanfeng Auto has been actively co-creating with IBM technical and enterprise consultants to show applied sciences to tangible enterprise values.
Yanfeng Auto is likely one of the trade pioneers in China to handle enterprise challenges with a “data-first” technique. Yanfeng Auto can also be the pioneer consumer of IBM in China that has been working carefully with IBM to co-create first-of-a-kind scenario-based options with IBM Cloud and AI applied sciences.
About Yanfeng Auto
Yanfeng Auto Worldwide Automotive Know-how Co., Ltd. (known as “Yanfeng Auto”) is a world automotive elements provider, dedicated to offering carmakers and different customers with inside and seating options that meet the wants of as we speak’s and tomorrow’s driving, redefining the way in which you chill out, work and play within the automotive. Headquartered in Shanghai, the corporate has 9 R&D bases, greater than 4,200 R&D groups, greater than 240 factories and technical facilities in 20 international locations all over the world, and greater than 55,000 staff worldwide, offering world automobile producers with the design, growth and manufacture of auto elements merchandise. With product innovation and forward-looking analysis, Yanfeng Auto will assist automakers discover the long run, deliver higher human-car interplay expertise to world auto shoppers, and actively promote the evolution of automotive driving expertise.
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