Ukraine conflict stalls the automotive industry’s engine

The motor vehicle producing industry globally is bracing for bigger difficulties pursuing the Russia – Ukraine conflict. The globalization of creation, with aspect of it being in the conflict location, is breaking up source chains and is halting output of vehicles inside of and outside the house Russia and Ukraine. Studies are foreseeing a worsening of the electronic chips crisis because some vital raw components are coming from the location. The worry of stagflation may also hinder automotive income by postponing unessential buys.

Belief by Bogdan Maioreanu, eToro analyst


Owing to a absence of parts from Ukraine-dependent suppliers, including Fujikura, Nexans and Leoni that deliver important wire harnesses for the German vehicles, the generation of Audi A4 and A5 types at Audi’s house plant in Ingolstadt, Germany, is suspended from March 7-11. In Neckarsulm, output of A6 and A7 types is paused from March 7-18. Audi has also imposed an order freeze for its hybrid styles mainly because of creation interruptions, with Porsche suspending Macan, Panamera output, while the BMW Team is halting creation at vegetation in Munich and in Dingolfing, the two Germany, upcoming week, as effectively as output at the group’s Mini factory in Oxford, England. Mercedes-Benz expects to decrease creation at some of its European vegetation as provides of pieces generated in Ukraine operate limited. Ukraine hosts much more than 20 international automotive providers like Bosch, Fujikura, Eurocar, Prettl, Aptiv and much more than 30 automotive vegetation. There are more than 60,000 workforce in the Ukrainian automotive business. Even though most of the providers are located shut to the western border with Hungary, Slovakia and Poland, still outside of the armed service operation zones, the conflict presently disrupted source.

In the longer time period the crisis in Ukraine has the possible to worsen the chip crisis. A grim estimation of the Secretary of Commerce Gina M. Raimondo finds that “median stock of chips has fallen from 40 days in 2019 to considerably less than 5 days.” This usually means that if anything disrupts a overseas semiconductor facility for even just a few months, it has the opportunity to shut down manufacturing amenities in the US and not only. The chips producer Taiwan Semiconductor Manufacturing Organization (TSM) that represents 50% of the international pure wafer foundry market place declared that it will observe Russia sanctions. But Russia accounts for 42 p.c of palladium, 70 percent of neon, 40 percent of nitrogen and 30 percent of xenon global exports which are significant components of semiconductor production. If Moscow retaliates by halting exports, the world’s semiconductor industry will be afflicted. Experts estimate that Taiwan experienced diversified its sourcing for these components and experienced currently stockpiled inventory. In accordance to study company Techcet, the 2022 Electronic Fuel market place is envisioned to leading US$7 billion, driven largely by logic chip fab expansions. There are other sources for the uncooked materials than Russia and Ukraine. On the other hand, in a international current market if just one provider is lower off, other

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Aftermarket Product Sales of Internal Combustion Engine Vehicles Will Grow to 2030 and Beyond

ICE Aftermarket Longevity Is Significant to Over 400,000 Business Outlets That Install and Sell Automotive Products Across the U.S.

Peak ICE aftermarket, the year when Internal Combustion Engine Vehicles reach their maximum aftermarket product volume, will not arrive until after 2030.”

— Jim Lang

FORT WAYNE, IN, USA, October 27, 2021 / — Aftermarket Product Sales of Internal Combustion Engine Vehicles Will Grow to 2030 and Beyond.

“Internal Combustion Engine (ICE) Vehicles will achieve significant U.S. automotive aftermarket product growth to 2030 and beyond, contrary to the widely-held expectations that Electric Vehicles will rapidly eliminate ICE aftermarket product sales,” said Jim Lang, President of Lang Marketing Resources, a leading automotive market intelligence firm headquartered in Fort Wayne, Indiana with over 25 years in the vehicle products industry.

“Peak ICE aftermarket, the year when Internal Combustion Engine Vehicles reach their maximum automotive aftermarket product volume, will not arrive until after 2030,” predicted Lang. “This is significant to the more than 400,000 business locations across the U.S. that repair vehicles and sell automotive products.”

Millions More ICE Vehicles

Despite growing annual EV sales, the number of ICE vehicles on the road will increase between 2021 and 2030.

Regular hybrids and mild hybrids (both have batteries recharged by internal combustion engines) are included as ICE vehicles in this analysis because most mileage of non-plug-in hybrids is ICE powered.

EV Future VIO

While EVs will steadily increase their share of new car and light truck sales in the U.S., their share of vehicles in operation (VIO) will climb at a much slower pace.

Even with aggressive annual sales growth, EVs will account for only approximately 7% of the total VIO by 2030. BEVs will represent an even smaller share.

EV Aftermarket Impact Delayed

Aside from Tires and certain Accessories, cars and light trucks do not make substantial contributions to aftermarket product volume until they are at least five years old. This will delay the impact of the rising annual sales of new EVs on the ICE aftermarket.

EV Low Average Age.

Since the runup in the number of EV vehicles on the road will occur late in the 2020s, EVs in operation during 2030 will have a very low average age, less than 3 years. BEV average age will be even lower, less than 2 years.

ICE Vehicle Aftermarket Growth to 2030 and Beyond

With their relatively small VIO and low average age, Electric Vehicles (PHEV and BEV models) will eliminate less than 2% of ICE aftermarket product sales in 2030, aside from Tires and certain Accessories. BEVs will eliminate an even smaller portion of ICE aftermarket product volume.

As a result, ICE cars and light trucks will continue to increase their aftermarket product volume through 2030 and beyond.

Jim Lang
Lang Marketing Resources, Inc
+1 260-399-1699
[email protected]

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This Automotive Company Revs Up Machine Learning To Turbocharge Engine Quality

By Keith E. Greenberg, SAP

Automotive manufacturer Mahindra Heavy Engines Limited (MHEL) has been building powerful diesel engines for more than 70 years. But changing market demands forced this venerable company to face a 21st century dilemma.

MHEL needed an extended quality testing program for internal combustion engines in order to reduce cost while accelerating the product manufacturing lifecycle.  And there was no time to waste. 

But because of the technical resources required, and the fact that the data was staged in multiple stand-alone servers, the process was slow and costs high.

So, the Mumbai-based company took a radical step: replace its outmoded physical methods with virtual testing – using artificial intelligence/machine learning (AI/ML) while incorporating data from a variety of sources.

How it’s done

To understand MHEL’s challenges and objectives, we need to take a brief glimpse at how things work there.

Currently, quality testing accounts for one percent of engine manufacturing costs. In the final phase of quality testing, the engines undergo what are known as “cold” and “hot/load” tests to identify defects and ensure quality.

What that means: in a cold test, the engine’s crankshaft is rotated with an electric motor, while software analyzes data from different sensors. 

  • Tests take approximately 140 seconds for each engine.
  • Engines that fail then undergo hot/load testing – which requires the engine to be fired and take two to three minutes.
  • Then come the load tests, which can go as long as 12 minutes.

Many engines don’t need the hot/load tests. MHEL’s challenge was eliminating these unnecessary steps without compromising quality.

Driving change

To hear company representatives tell it, MHEL has thrived because of unconventional thinking and the innovative ways it has utilized resources. 

Therefore, the logic went, why couldn’t MHEL rely on ML to validate engine quality, eliminating the need for avoidable tests for those engines that already met hundreds of predefined parameters?

To make that happen, a predictive quality ML model had to be designed to analyze test results and other data to determine engine performance and quality. This tool would identify the likelihood of oil leaks and other flaws generally detected during hot/load testing. 

Improvising possibilities

MHEL turned to SAP to manage business operations. Drawing on solutions created through the SAP Integration Suite, the new model eased complexity by unifying data from an array of sources – calculating in such factors as engine suppliers, in-house manufactured parts, engine assembly, and user-plant defects.

This wealth of information, combined with specific parameters and cold test results, allowed each engine to be positively classified as “Further Hot Test Required,” “Further Load Test Required,” or “No Further Test Required.”  Remember: prior to the introduction of the new model, even engines that didn’t need additional testing underwent the extra steps — costing MHEL both time and money.

“This first-of-its-kind use

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