Guest Post by John Ayers (first posted on CERM ® RISK INSIGHTS – reposted here with permission)
Robots are developed to address a problem. For example, automating a production line. To achieve this goal, a multidiscipline engineering team is required.
The question is which engineering discipline should I study? I suggest you get a degree in System Engineering. This paper will explain why.
Let’s take a look at the key engineering disciplines that are involved in robotic design. They are:
- System engineering
- Computer science
- Electrical engineering
- Mechanical engineering
- Artificial Intelligence engineering
- Reliability engineering
- Industrial engineering
System engineers are responsible for the specification compliant functioning of the robot. This means they need to have good knowledge and understanding of electrical engineering, mechanical engineering, and computer science to make good decisions regarding the robot design and dealing with problems that will surely come up. The system engineer will determine root cause of a problem and the best way to resolve it. His decisions are based on input from the team.
Computer science involves designing the software for the ‘brains’ of the robot. That means developing various algorithms such as controllers or computer vision components to make the robot learn and recognized the environment around it.
Electrical engineers design the power system, controls, embedded programming (called firmware), feedback loops, and controls. It involves analog, digital, sensors, and signal processing design. Electrical engineers are responsible for the system electrical schematics and wiring diagrams.
Mechanical engineers are responsible for the structural, joint mechanism, bearings, heat dissipation, materials, and finishes design. The design of the robot is done on a CAD (computer- aided design) application program. Mechanical engineers are responsible for the robot configuration and drawings.
ARTIFICIAL INTELLEGENCE (AI) ENGINEERING
AI engineers have the responsibility to write machine learning algorithms to develop robotic artificial intelligence. The algorithms involve: using sensors, digital data, and remote inputs from a variety of different sources; analyzes the information; and acts on the insights derived from those data. AI engineers need a sound understanding of programming, software engineering, and data science.
Reliability engineers are responsible for durability and reliability of the robot to safety operate in the environment it was designed to operate in. This includes the selection and testing of components, equipment, and processes. They also are responsible for the root cause analysis of any failure. The goal is to design the robot with high reliability to minimize production interruption. Reliability engineers skills include statistics, data analytics, risk management, maintenance management, root cause analysis, and electrical engineering.
Industrials engineers have the responsibility to apply statistical methods and perform mathematical calculations to define the production line manufacturing processes, staff requirements, and production standards. They develop, test, and evaluate integrated systems for managing the industrial process including logistics and material flow and production space layout. This information is input to the robotic design team to ensure the robot is integrated into product efficiently.
The scientific discipline concerned with the understanding of interactions among humans. The goal of human factors is to reduce human error, increase productivity, and enhance safety. This field includes , biomechanics, industrial design, physiology, anthropometry, interaction design, visual design, user experience. Robots today in the factory have to look pleasing to the eye otherwise the product may not sell well.
WHY SELECT SYSTEM ENGINEERING TO STUDY?
Let me answer this question with a story.
Ken was a system engineer on a complex imaging system. The system included: software, electrical and mechanical hardware, and firmware (embedded code in a chip). When a problem arose, he first had to find the root cause of the problem. Then he had to decide if a hardware, software, or firmware change was the best solution. A software problem is difficult to find but easy to fix. Likewise with firmware. A hardware problem is easy to find but difficult to fix. In deciding the best solution, a number of tradeoffs were considered that included budget, schedule, and reliability. The Project Manager made the final decision based on the recommendation from the system engineer. The decision meant one of the engineering disciplines needed to update their design.
If you want to be a robotics system engineer, this is an example of how you must think.
Robotics design is complex and challenging. Many engineering disciplines are involved. If you want an exciting job and consider yourself a leader, I suggest you become a system engineer. They rule robotics design.
Currently John is an author, writer and consultant. He authored a book entitled Project Risk Management. It went on sale on Amazon in August 2019. He authored a second book titled How to Get A Project Management Job: Future of Work. It is on sale on Amazon. The first book is a text book that includes all of the technical information you will need to become a Project Manager. The second book shows you how to get a Project Manager job. Between the two, you have the secret sauce to succeed. There are links to both books on his website.
He has presented numerous Webinars on project risk management to PMI. He writes columns on project risk management for CERM (certified enterprise risk management). John also writes blogs for APM (association for project management) in the UK. He has conducted a podcast on project risk management. John has published numerous papers on project risk management and project management on LinkedIn.
John earned a BS in Mechanical Engineering and MS in Engineering Management from Northeastern University. He has extensive experience with commercial and DOD companies. He is a member of PMI (Project Management Institute). John has managed numerous large high technical development programs worth in excessive of $100M. He has extensive subcontract management experience domestically and foreign. John has held a number of positions over his career including: Director of Programs; Director of Operations; Program Manager; Project Engineer; Engineering Manager; and Design Engineer. He has experience with: design; manufacturing; test; integration; subcontract management; contracts; project management; risk management; and quality control. John is a certified six sigma specialist, and certified to level 2 EVM (earned value management). Go to his website to find links to his books on Amazon as well as numerous papers he has written. https://projectriskmanagement.info/
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