There’s a litany of reasons that Smart Manufacturing – or the strategic use of data to analyze tools, materials, and factories in microelectronics manufacturing – is at the epicenter of the tech talent wars. From the need for more tech talent to fuel digital transformation across all industries to the great resignation and great retirement of workers en masse, the demand for tech talent continues unabated. The war for talent is especially fierce for microelectronics manufacturing companies looking for new data analytics staff as they work to overcome misperceptions about the manufacturing sector, compensation, and the generational divide.
Overcoming the Bunny Suit Myth
There are good reasons for software, industrial mechanical, and electrical engineers to choose the microelectronics industry for a career. Engineers can capitalize on their math and science skills in a unique discipline like data analytics to bring high value to teasing out complex challenges in the manufacture of semiconductors or many other types of microelectronics.
Despite the wealth of career opportunities offered by the microelectronics manufacturing industry today, attracting engineering talent is a tough challenge. One of the biggest obstacles is the perception that manufacturing often involves factory lines and bunny suits, the coveralls worn in cleanrooms. For data process engineers and software developers, wearing a bunny suit is uncommon and has become even rarer during the pandemic, with remote work becoming more prevalent and more manufacturers taking advantage of the higher processing capacity and speed, and stronger security of the cloud.
The microelectronics industry also faces a brand awareness challenge. As digital transformation powers innovations in industries such as automotive, healthcare, communications, logistics, and data centers, microelectronics producers and their suppliers are often not credited for the advancements they enable. Yet engineers devise new manufacturing methods or use data to design cleaner processes that reduce the carbon footprint of products from many companies including household names such as Apple, Samsung, and Sony.
Mid-level Data Engineers the Linchpin to Industry Advancement
The talent crunch plagues all levels of the industry. However, it’s the mid-level, experienced data analytics and signal process engineers who have the knowledge and experience to create significant advancements in fab improvements in the Smart Manufacturing realm. Experienced data engineers can comprise up to 90% of a microelectronics manufacturer’s data team and are highly sought after throughout the industry. This tight competition poses unique challenges for manufacturers who must combat the myth that the microelectronics manufacturing industry is not a natural career destination for data engineers and scientists.
One damaging misperception is that Smart Manufacturing consists strictly of factory work with low salaries. In reality, the technologies behind a smart semiconductor fabrication facility, or fab, are 10 times more complex than those at other types of factories – and more sophisticated than the tech used to build a rocket. Signal and data process engineers capable of working with these intricate technologies command starting annual salaries ranging from $80K to $16OK. An experienced fab engineer can earn $300K to $400K.
For an engineer who wants to work with complex, leading technologies, the semiconductor industry is the place to be. One industry leader said, “We can truthfully say to young people pursuing engineering as a career that the semiconductor industry is going to need more blockchain engineers in the future than any other field.”
New Generation of Tech Talent Clash with Old Engineering Culture
Young people are drawn to engineering careers because they want to create things and make the world a better place. Drawn to the field by a love of math or science, engineers like to explore ideas in an environment that encourages ongoing exploration. However, highly controlled engineering workflows in microelectronics manufacturing disciplines are unattractive to some younger engineers because of the deep technical expertise required, yet the industry is working to attract these groups, especially as baby boomers begin to retire.
While engineers entering Smart Manufacturing still need to develop fab process knowledge and experience in machine communication protocols, opportunities to work with new digital tools such as digital twins could entice talent to join the industry. One industry leader envisions building a digital twin as a breadboard for data process engineers – one where mistakes can be made and corrected and new ideas can take root. This creates an ideal place for a new engineer to hone skills, learn about the fab, and explore concepts without running up against tightly controlled workflows.
Another challenge is finding workers with the right mix of soft skills such as teamwork, communications, time management, and interpersonal relations. One senior leader said, “Without soft skills and the ability to engage people, you can’t lead in the modern era. Servant leadership is required.”
Traditional top-down management styles at many factories favor worker productivity over soft skills. Yet, younger generations of workers look for company cultures to be more egalitarian with flat management structures. It’s unclear how hidebound and new engineering cultures can co-exist. An industry expert suggested that an environment that offers engineers a generational blend of leaders and the ability to explore and experiment can attract the talent the industry needs.
Electronics manufacturers are grappling with how to attract the right mix of soft and hard skills. Many engineering grads seek jobs at software companies since their workgroups are typically more social with high levels of collaboration and feedback. For the semiconductor industry to attract and retain new talent, it must give engineers an environment that appeals to them.
Can Universities Prepare Students for Careers in Smart Manufacturing?
The next installment of this Smart Manufacturing talent series will address skills new data engineers and data scientists need to enter the industry, and whether higher education is preparing them with those skills.
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