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Quality in real time: How IIoT is changing automotive production

By Michael Martin   

Industry Innovation & Technology Production Automotive assembly automotive IIoT manufacturing quality Technology Testing

Defects are spotted and fixed before vehicles roll off the assembly line.

Engineer using tablet with machine real time monitoring system software. PHOTO: FOLOLIA

As we move into the Fourth Industrial Revolution, or Industry 4.0, some consider automation to be a recent phenomenon. It’s not.

Take the automotive industry: long before the internet or computers, Henry Ford realized if cars were going to replace the horse and buggy and change the way we travel, he had to find a faster way to build them. As a result, he created the assembly line, which automated many of the tasks.

This revolutionized the auto industry, and manufacturing. As cars rolled down a 140-foot line, assembly went from 12 hours to 93 minutes. More importantly, automating the process lowered the price of the Model T from $850 (about $21,000 today) to just $260 ($3,500). Ford had created an inventory and a price point that the masses could afford.

Automotive manufacturers now face realities Henry Ford never had to contemplate. Companies using advanced technologies such as artificial intelligence (AI) and the Industrial Internet of Things (IIoT) are driving unprecedented changes within the automotive industry. New operating models involve connected systems that reduce costs while improving other factors such as efficiency, product quality and time-to-market. Under these conditions technology is expected to do more and always work – downtime is not an option.

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Until recently, manufacturers applied an assembly line model to production. In auto plants, vehicles were built using the same design and manufacturing plans. Processes were mostly manual, with even the critical quality assurance stage executed as a stand-alone task on the line.

We’ve all heard of “Friday afternoon” or “Monday morning” vehicles, which refer to the hit or miss human element, with misses often not being caught until after the car is built.

Quality in real time

IIoT is increasingly used to improve the manufacturing process. Instead of building, then checking afterward, manufacturers are testing in real time as the vehicle moves along the assembly line to immediately detect, identify and correct defects. Machine-embedded IIoT sensors check quality assurance (QA), monitoring machinery for weakness, and enabling it to fix itself.

One major car manufacturer is now performing all its testing along the assembly line before the body is even on the chassis.

Today’s cars have dozens of built-in CPUs used to monitor and control vehicle functions, but they’re also used to test processes during production. As vehicles become more complex, value is added to the bottom line. Unlike 20 years ago when QA would focus on the engine, the transmission and other major components, manufacturers now check systems not imagined years ago. Are the seats heating and cooling as they should? Do brake-activated seatbelts actually work? With IIoT, computers are always talking to each other to ensure all parts work seamlessly and exactly as designed. Manufacturers no longer build lemons.

As plants with their sprawling, complex systems and equipment become instrumented through the IIoT, AI and data analytics provide deeper insight into the data generated on the factory floor.

IIoT advances

This insight is improving reliability, quality, safety, and equipment performance, while leading to a better understanding of the various factors that impact productivity, drive up costs and impede time to market.

But as IIoT advances, cyber crime becomes a growing threat to businesses. All connected systems are vulnerable to attacks. Most of the valuable data generated from IIoT devices appeals to hackers who want to make money from the information, wreak havoc, or worse.

Manufacturers are susceptible to industrial and economic espionage as hackers attempt to steal intellectual property and internal operational information. Consequences include financial loss because of lower productivity to dangerous work conditions.

As cyber criminals adopt AI, OEMs will have to keep pace and use it to defend their vehicles from attack. It’s not just cars and trucks – the end-to-end vehicle ecosystem must be protected at every stage and with a dynamic response that escalates as the threats advance.

While the threats are real, technology companies are developing cybersecurity solutions that keep pace with IIoT and connected devices. To prevent breaches, systems must be designed to embed security as technology is developed and deployed. This approach is spreading as automotive companies are required to comply with rigorous security regulations.

Connected technology is expected to mesh into virtually every industry ecosystem. Even so, IIoT is still evolving. Manufacturers at the beginning of an IIoT journey should not consider this an all or nothing model. It takes time to transition to newer systems. A thoughtful and systematic approach will drive valuable results.

Michael Martin is the Internet of Things lead executive for Network Services at IBM Canada.

Comments?
E-mail jterrett@plant.ca.

 

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