Automation majors are undoubtedly the most popular track among engineering majors with the widest adaptability and the longest dividend period.
Countless parents and children, as well as practitioners who are new to the industry, are repeatedly entangled between the two core paths: Which one to choose?
Which one has more “money prospects”?
Who can avoid the 35-year-old crisis?
Which one can go further?
Today, we use a complete career development curve to completely dismantle the underlying logic of automation majors – intelligent automation is the “fast lane” and industrial automation is the “long runway”.
Make the right choice and save ten years of detours.
1. Intelligent automation: skyrocketing in the early stage, relying on mathematical algorithms in the later stage
The career development curve of intelligent automation can be described in one word: first steep and then flat.
0 – 5 years: rocket rise
Your first job may just be a machine vision assistant engineer in a small company, with a monthly salary of 8,000.
But as long as you are willing to learn, you can change jobs after one year and it will be directly to 15,000; after another year, you can jump again and it will be 25,000.
This is the norm in the intelligent automation industry – it is normal to get a salary increase of 30% – 50% when changing jobs, and if it goes too far, it will be doubled.
Why did it rise so fast?
Because there are “shortcuts” to getting started with intelligent automation.
As a case study, I will use a student I once mentored. He majored in automation at Guangdong University of Technology. As soon as he graduated, he worked in machine vision research and development in the 3C industry in Shenzhen.
His personal experience is quoted below. What should he do when he receives a demand?
copy!
Halcon and OpenCV have ready-made operators, and GitHub and visual forums are full of mature project source codes. By changing parameters and adjusting templates, you can complete a part detection function in half a day.
It takes two or three days for the hands to be raw, and it takes a few hours for the hands to become familiar.
There is a rule in this industry: the law of hundreds of projects.
As long as you have followed 100 visual implementation projects, your level will naturally reach a higher level, and one year of stupidity is enough.
Therefore, the rapid salary increase in the early stage of intelligent automation is not a bubble, but a rapid improvement in capabilities – the salary your boss offers you must be based on how much value you create first.
5-10 years: Entering a plateau
At this stage, the curve of most people begins to flatten.
The difference between ordinary algorithm engineers and senior engineers is no longer about adjusting operators and modifying source code, but about mathematical ability.
Why do many people say that intelligent automation also has a 35-year-old crisis?
It’s because after the age of 35, relying solely on “copying ready-made solutions” has reached its ceiling.
If you want to move up the ladder, you can do 3D vision, deep learning algorithms, underlying motion control algorithms, and robot path planning. The key is mathematics.
Linear algebra, matrix theory, probability theory, these are the core for you to break through the upper limit.
Why does the Strong Foundation Program put mathematics first?
Because mathematics is the base of all engineering subjects.
10 years later: Very few people will venture up again
Those with a solid foundation in mathematics, from algorithm engineers to algorithm directors, R&D directors, and even technology company CTOs, the curve can still rise further.
But most people stay in the stable zone and either switch to management or take a salary cut to work as technical leaders in small and medium-sized companies. It is difficult to achieve a leapfrog increase in salary.
Who is intelligent automation suitable for?
The development curve of industrial automation is completely opposite to that of intelligent automation: gentle in the early stage, vigorous in the later stage, and there is no obvious ceiling.
0 – 5 years: Slow climb You are also just graduating. If you study industrial automation, you may earn a little over 10,000 yuan a month. You will do PLC debugging in a factory, go to the site every day, and stay up late to change programs. However, students who study intelligent automation are already sitting in the office and earning 20,000 yuan. It is inevitable that you will feel unbalanced.
But there is a reason behind this: Industrial automation requires five major abilities to be improved at the same time – electrical principles, PLC programming, touch screen configuration, inverter debugging, and production line process understanding. Without one, you will not be able to do it well.
Barrel Theory: Intelligent automation only requires two major abilities: mathematics + programming, which can be mastered in one year; industrial automation has five major abilities, and it will give you one year to master two. 5-15 years: Continuous rise But slowness has its advantages – high barriers. When you have mastered the five major abilities and understand technology, process, cost, and business, you will be a scarce talent in the industry. 15 years later: Entering no man’s land Industrial automation does not have a 35-year-old crisis, because, like medicine, it is an industry that becomes more popular as it gets older. With a PhD in automation, fresh graduates will get an annual salary of 2 million in smart manufacturing positions at leading domestic car companies – this is not only the aura of a prestigious school, but also the choice of the times. Who is industrial automation suitable for? Go forward 20 years, who knew that automation could become a top-notch engineering major? For the same master’s degree, more than half of the automation graduates from ordinary colleges may earn three to four hundred thousand, and the top ones can earn one or two million. What does China lack most now? Data from the Ministry of Human Resources and Social Security show that the talent gap in the field of intelligent manufacturing exceeds 20 million. The annual salary for core automation positions is generally 500,000+, and the annual salary of one million for leading companies has become the norm. First, look at mathematics, physics and practical ability Second, look at your willingness to study for graduate school Third, it depends on the family situation and career expectations Finally, although there are many people in intelligent automation, low-end parameter adjusters are saturated, and high-end algorithm talents are always in short supply. When you choose a major or a track, you don’t choose which one is popular, but which one is suitable.2. Industrial automation: Slow work produces fine work, and the older you get, the more popular it becomes.
If abilities grow slowly, wages will naturally rise slowly.
Newcomers who want to enter the industry cannot just rely on “copying”.
Can you copy the emergency troubleshooting for sudden production line failures?
Can you copy the overall design of the entire non-standard production line?
Can you copy the linkage debugging of multi-brand PLCs and the logic optimization of complex processes?
It all depends on real effort and time.
At this time, your curve begins to rise steeply, and smart automation students may already be waiting for you in the stable zone.
It is not uncommon for top automation chief engineers and production line integration experts to earn an annual salary of one million.
Why?
Because what the country lacks the most is not writers or hosts, but engineers who can put black light factories and smart manufacturing into practice. Industrial automation is where China’s manufacturing industry has grown from big to strong, and has been stuck.
3. Dividends of the times: Why is the upper limit of automation majors higher?
Push forward 20 years, if there is no shortage of automation talents, why should you be given a high salary?
The current dividends are dividends from the national strategy.
Of those one to two million, half is given by academic qualifications and abilities, and the other half is given by the premium in this era of automation.
There is a shortage of engineers who can upgrade the manufacturing industry.
Computers have made all walks of life intelligent, but for intelligence to truly be implemented in factories, production lines, and equipment, it all depends on automation.
Whether it is new energy, semiconductors, automobiles, 3C, food, medicine, or equipment manufacturing, all real economies are inseparable from automation.
Therefore, in the long run, automation majors are not limited by industry cycles, and the ceiling is higher than that of computers and electronic information alone.
But the high ceiling doesn’t mean that everyone can reach it. You have to have the ability and the patience.
4. Understand with one table: How to choose between two tracks?
Comparative dimensions
Intelligent automation
Industrial automation
Core track
Machine vision, robot algorithm, motion control, AI +
AutomationPLC industrial control, production line integration, intelligent manufacturing, non-standard equipment design
Career development curve
First steep and then flat, skyrocketing in the early stage, and easy to hit the ceiling in the later stage
First flat and then steep, flat in the early stage, and continuing to rise without an upper limit in the later stage
35 years old core competitiveness
Mathematical skills, underlying algorithm research and development capabilities
Process accumulation, solution design capabilities, full-process resource integration
Million annual salary threshold
Algorithm director, head of research and development of leading companies
Automation chief engineer, large-scale production line project
Project manager, factory director
The entry threshold is low
You can get started quickly with a basic programming background
High, it requires long-term accumulation of multi-dimensional capabilities
Industry barriers are low
Newcomers can iterate quickly and are highly substitutable
High, the experience barrier is thick, the older you are, the more popular it becomes.
Fifth, the last three “iron rules” to help you choose
→ Give priority to intelligent automation
The upper limit of industrial automation is higher
Industrial automation has strong stamina
As long as you are good at math and programming, you are still scarce.
Industrial automation has a high threshold and slow growth, but once you enter the industry, you will become the “iron hat king” who becomes more and more popular as you get older.
