Computer Science Vs Mechanical Engineering: 10 Factors To Consider

Computer Science Vs Mechanical Engineering: 10 Factors To Consider

 

The image displays 10 factors to consider in computer science vs mechanical engineering

 

Computer Science vs Mechanical Engineering – The Endless Conundrum

 

The 12th standard results are out! And kudos – you have aced the PCM group (physics, chemistry and, mathematics) with flying colors. Unlimited options have opened up, and now it’s time to call upon your dream specialization and college. But with great possibilities come great confusions. And the most typical query is – ‘Computer science vs Mechanical engineering – which is better?’

 

Core Syllabus: Computer Science vs Mechanical Engineering

 

Computer science is relatively a new field that studies computation, operating systems, programming, and applications in several industries. The core subjects covered are:

 

  • Data Structure & Algorithms
  • IT Workshop – (Sci Lab/MATLAB)
  • Discrete Mathematics
  • Computer Organization and Architecture
  • Operating Systems
  • Design and Analysis of Algorithms
  • Database Management Systems
  • Formal Language, Automats, and Complier
  • Object-Oriented Programming
  • Compiler Design
  • Computer Networks

 

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On the other hand, mechanical engineering is the oldest, broadest specialty of engineering, which combines physics, mathematics, and material science to design and build systems. The core subjects covered are:

 

  • Thermodynamics
  • Fluid Mechanics & Fluid Machines
  • Strength of Materials, Material Engineering
  • Instrumentation & Control
  • Heat Transfer
  • Solid Mechanics
  • Manufacturing Processes & Technology
  • Kinematics & Theory of Machines
  • Design of Machine Elements
  • Automation in manufacturing

 

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Future Prospects: Computer Science vs Mechanical Engineering

 

Computer Science(CS)

 

After rigorous training in computer science, one could pursue their interests in the following:

 

  1. Artificial Intelligence
  2. Game Design
  3. Network
  4. Computer Graphics
  5. Data Science
  6. Language Programming
  7. Bioinformatics and the prospects are endless

 

Mechanical Engineering(ME)

 

With a solid grasp in the core areas mentioned above, one can diversify into several dynamic industries like:

 

  1. Mechatronics
  2. Nanotechnology
  3. Robotics
  4. Advanced Manufacturing
  5. Automobile engineering
  6. Aerospace engineering

 

The above list is incomplete but expanding with leaps and jumps in technology.

 

The two fields are no longer mutually exclusive but deeply intertwined in the present times. Picture this scenario – you are finally on the much-needed vacation in Kerala. You impulsively decide to dive into a freshwater lake in Alleppey – with your smartwatch still strapped on!

 

Who do you think has done a more commendable job – the materials engineer who has ensured that your watch stays waterproof or the computer scientist whose coding enables Google to surprise you even after a decade with a throwback reminder of this getaway. In case you are stumped, say ‘cheers’ to the Industrial Revolution 4.0.

 

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Role in Industry Revolution 4.0: Computer Science vs Mechanical Engineering

 

The Industrial revolution 4.0, aka Industry 4.0, refers to the present-day era, where digitalization and automation have deeply integrated with every aspect of the manufacturing industry. In simpler terms, we are in an age where even a mundane chore like swatting flies is done the ‘smart way’. So how does this impact the field of engineering and computer science?

 

The following are the critical components of Industry 4.0:

 

  • Cyber-Physical Systems
  • Internet of Things (IoT)
  • Internet of Services
  • Big Data Analytics
  • Augmented reality
  • Autonomous Robots
  • Additive manufacturing
  • Cloud Computing
  • Simulation modeling
  • Cybersecurity

 

Rather than the confines of textbook definitions, this article explores a mechanical engineer and computer scientist’s evolving roles based on the ten components listed above. Hopefully, this will help one in making a more informed choice.

 

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1. CPS (Cyber-Physical Systems):  Computer Science vs Mechanical Engineering

 

A Cyber-Physical system refers to a system where a machine’s mechanical components are monitored, controlled, and coordinated by computer programming and network. This definition sounds a bit intimidating. Still, the truth is that with every single passing day, these systems are steadily becoming an integral part of our lives.

 

Ex – Consider the example of road traffic safety. Studies have shown that 60% of roadway collisions can be prevented if the vehicle’s driver gets a prior warning by 0.5 seconds. Therefore collision avoidance technologies are being developed and constantly refined to address this issue. This success of such technologies requires the combined efforts of a computer programmer and an automobile engineer.

 

CS: The real-time data collected from sensors installed in vehicles must be stored, analyzed, and an appropriate response has to be conveyed via a feedback algorithm. Also, ‘smart’ cars need to exchange information with ‘Vehicle to vehicle’ transmission using efficient wireless networks. These are some of the ‘Cyber’ components that are mainly the computer scientist’s domain.

 

  ME: The engineer works on the ‘physical’ component, focusing on autonomous vehicles (AVs), adaptive cruise control (ACC), lane departure warning, and early collision avoidance systems. These collect information about traffic, road conditions, vehicle-pedestrian proximity, and automatically initiate safety maneuvers like emergency brakes.

 

2. Internet of Things (IoT):  Computer Science vs Mechanical Engineering

 

IoT refers to physical gadgets or pieces of equipment embedded with various sensors, software and feedback technologies. These are interconnected and exchange data with other devices or systems via the internet. We are most familiar with this concept by using ‘smart home’ applications. Today numerous home appliances like refrigerator, coffee maker, washing machine, indoor lighting, video doorbells, and burglar alarms are remotely controlled through mobile phone applications.

 

CS: Four crucial software components are paramount for the successful functioning of the ‘smart home’ gadgets:

 

  1. IoT device software – Presently, many domestic appliances are installed with microprocessors/microcontrollers containing sophisticated software systems. These software systems expose the appliance sensors to the external world through wired/wireless connections.
  2. Gateway software: This software connects the device to the home’s or residential building’s local network
  3. Smartphone app: This enables one to perform several functions like turning devices on/off, monitoring and managing them from the local premises, or even a remote location.
  4. Cloud software: This provides an end-to-end IoT solution. It can simply be an application to manage multiple user accounts or a secured platform to access, analyze and manage all sensor data in real-time.

 

Here, the computer scientist’s responsibility is to ensure that all four components are well incorporated and smooth without any glitches.

 

So if all goes well, at the end of a tiring office day, you can get home daily to a freshly brewed cup of coffee while a set of clean dishes sparkle in the dishwasher rack.

 

ME: While designing the appliance in the blueprint stage itself, the engineer must keep in mind that the hardware must be well integrated with the software. He needs to determine how and what kind of sensors are incorporated into the gadget. The sensors have to be long-lasting and sturdy enough to withstand all types of wear and tear.

 

These will gather millions of gigabytes of information on almost everything happening in the product, such as the boiling water temperature in the coffee pot or the dishwater’s rinse duration. The engineer will install the appropriate parameters like ‘cut off temperature’ of the coffee maker or maximum time of ‘rinse cycle’ in the dishwasher by using this information.

3. Internet of Services: Computer Science vs Mechanical Engineering

 

The Internet of Services (IoS) is the real innovation after IoT. Beyond manufacturing ‘intelligent products,’ companies also need to think about providing long-term service to ensure customer loyalty. Consumers always have a better experience with products that promptly register user feedback and flexibly upgrade their functions.

 

CS: A computer scientist’s job does not end with writing reams of complex codes and installing complicated software programs. Like the engineering counterpart, the computer programmer has the responsibility of ensuring smooth functioning in the long run.

 

The programmer needs to promptly identify and fix ‘bugs’, i.e. errors in codes within the operating system or any location in the software. When functionalities become outdated, the coder should carefully remove them without disturbing the software’s overall performance. Constant review and up-gradation of the software will ensure accurate data recording, analysis, and smooth workflow implementation.

 

ME: As a machine keeps running, the mechanical components can gradually wear down, require lubrication and, sensors can register faulty calibrations. Using the cloud data, the engineer can review the machine’s performance installed locally or even halfway across the globe. More importantly, the non-stop stream of information aids in recognizing the early signs of equipment failure.

 

Instead of reactive maintenance (repairing equipment after it fails), the engineer can make an informed decision about a preventive maintenance schedule. Such a decision goes a long way in ensuring optimal equipment performance, avoiding unplanned downtime, and saving the company from financial losses.

 

4. Big Data Analytics: Computer Science vs Mechanical Engineering

 

It refers to the elaborate process of evaluating large volumes of data to identify market trends, correlations, and user preferences. It incorporates predictive models, statistical algorithms, and sensitivity analyses. Various sources collect data – internet clicks, web server records, mobile and cloud applications, social media pages, and equipment logs. It is then organized, configured, rectified for errors, and analyzed by analytics software.

 

CS: A computer scientist shares the common roots of data analysis and technology with a data scientist, but their pathways are not entirely identical. Data science utilizes coding language to sift through enormous data, but it is not concerned with a software program’s actual workings.

 

Instead, it is more focused on algorithms that reveal trends in data and predict behavioral patterns in the future. Computer science knowledge gives a good headstart in handling data science and formulating sound technical solutions. Also, a practical interpretation of algorithms leads to innovative business solutions.

 

ME: It might seem that there is not much of a mechanical engineer role in data science, but one couldn’t be farther away from the truth. The well-updated engineer applies machine learning to complex data. A significant amount of industry-based data is generated by the sensors arranged in networks.

 

And it is the engineers who design the sensors to measure parameters like speed, force, temperature, and much more. They utilize the inferences drawn from such data analytics and design next-generation equipment that are safer, reliable, and far more dependable.

 

5. Augmented reality: Computer Science vs Mechanical Engineering

 

People often use the terms ‘augmented reality (AR) and ‘virtual reality (VR) interchangeably, but they are not the same.

 

Virtual reality refers to a completely immersive experience that excludes the physical world’s elements. On the other hand, augmented reality integrates digital components into a real-world scenario. To explain it in one word- think ‘Pokemon’.

 

CS:  A person with a good foundation in computer science can focus either on becoming an AR designer or an AR developer.

 

An AR designer is the one who modifies technology and superimposes it on live surroundings. His prime focus is to study user interface, user experience and transform it from good to the best. The process involves closely looking at interaction design principles, design process, and accessibility. He also needs to have a good grasp of 3D modeling and animation.

 

An AR developer is the one who handles visualization, structure formation, and outlining ideas suggested by the designer. Following skills are required:

 

  1. Good programming experience in computer languages (JavaScript, C++)
  2. Web and mobile application development skills
  3. Eagerness to build modifiable software engines that ensure a customized user experience

 

Only when the virtual information is accurately overlaid on the live surroundings can practical, precise decisions be taken.

 

ME: A widespread application of AR is designing ‘plant layouts’. ‘Plant layout’ refers to the process of strategically placing machines, processes, and services within the factory space to ensure the optimal output of high-quality products with the lowest cost of production. Traditionally organizations did this by building miniature scaled models in the physical form. It was the most typical way to visualize the layout, and multiple people could review the model simultaneously.

 

Plant layout design is a team effort, but the mechanical engineer must work closely with architects, fire & electrical engineers to give crucial inputs on the workflow pathway. He is responsible for ensuring that raw materials, equipment, workstations, finished products, and even scrap disposal have a proper factory location. If these factors don’t synchronize well, the total manufacturing cost and time will shoot up, incurring huge losses.

 

Using an AR-based system enables the engineer to place virtual objects in natural environments allowing instant visualization of the plan. This system will allow him to generate multiple layouts, effectively coordinate with other team members, modify and choose the most desirable outcome.

6. Autonomous Robots: Computer Science vs Mechanical Engineering

 

Also called ‘Autobots, these sophisticated robots perform tasks with a high degree of autonomy. They are an intersection of artificial intelligence, robotics, and information engineering. These are three essential elements to their effective functioning:

 

a. Perception – collect data from its environment

b. Decision- evaluates data and chooses a response based on its programming

c. Actuation – execute the corresponding maneuver

 

CS: All autonomous robots require a sophisticated level of computer programming in addition to excellent mechanical and electrical structures. Just like humans, they need a well-designed brain and neurological system.

 

The applications are endless, starting from simple movements such as walking, crawling, jumping to more sophisticated functions like human interaction, speech recognition, facial expressions, and social intelligence. Aren’t we all familiar with Sophia -the robot manufactured by a Hong Kong-based company that also received Saudi Arabia citizenship? Speculations are she might be mass-produced this year to navigate the healthcare, retail, and airline industries’ troubled times.

 

ME: Engineers play a vital role in the perception and actuation elements. They install input devices like laser scanners, stereo-vision cameras, and force sensors in spectrometers to pick up information from the environment. In case an autonomous robot comes across a table rather than bumping into it, it will change its direction. When a robotic vacuum cleaner comes across a corner with excessive dust, it will spend more effort cleaning it up before moving ahead.

 

After collecting data and finalizing a decision, the action is executed with an actuator. Actuators are mechanical moving parts of a machine that carry out tasks such as opening or closing a valve. It is like the body’s muscles, which pick up, set down, push and pull objects. A mechanical engineer specializing in robotics will design its range of motion, keeping in mind the various stresses and strains it will have to face.

 

7. Additive manufacturing: Computer Science vs Mechanical Engineering

 

Additive manufacturing refers to making objects by adding materials. When producing things by traditional means, materials are reshaped by cutting, carving, drilling, or milling. But in additive manufacturing (also called 3D printing), the objects are first digitally designed by CAD (computer-aided design) software.

 

The software then directs the hardware to deposit material, layer by layer, in a specific geometric shape. Each layer deposits on the preceding layer of wholly or partially melted material. Different materials are used to create 3D objects like thermoplastics, metals, ceramics, and various biochemicals.

 

Think of Tom Cruise and his clever impersonation masks in the Mission Impossible movie series – although things are still not so fancy! Nevertheless, the applications are now widespread.

 

Surgeons have now started using this technology in designing dental implants. Key advantages of 3D printing are:

 

a.cost-saving

b.lesser factory to market time

c.improved customization and personalization.

 

CS: Along with improved hardware, efficient programming languages are required to simplify the high-end process and make it widely available for mass production. A computer scientist plays a significant role in the following three key domains:

 

  1. Programming for better design
  2. Improved compiler technique to speed up production and improve prints
  3. close monitoring for software snags

 

ME: Strong foundations in mechanical, structural, computer-aided design, and material engineering help develop a superior quality implant. Its close resemblance to the human tooth in size and consistency reduces implant-induced irritation and infection.

8. Cloud Computing: Computer Science vs Mechanical Engineering

 

Cloud computing refers to delivering services through the internet- Google cloud, Microsoft, IBM, and Amazon web services. Commonly provided functions include email, storage, and backup, data retrieval, creating and testing apps, analyzing data, delivering software on demand. Files are stored remotely and are easily retrievable.

 

Public services are available online for a fee, whereas private services are hosted on an exclusive network. Surveys show that cloud computing also reduces the need for IT support.

 

CS: A candidate with a degree in Computer Science has a good understanding of the following: programming skills, information security, and cloud service providers

 

One can become a Cloud Engineer and focus on one of the following roles:

 

Cloud Developer – one who designs and develops cloud applications, services, and secure products

Cloud architect, a professional who creates the computing strategy of a company

Cloud Network engineer, one who ensures that multiple people are accessing shared resources in a safe and secure manner

Cloud Systems Engineer, one who deploys and supports the solutions at the data centers

Cloud security engineer, responsible for securing and protecting crucial information about the organization.

 

ME: On the surface, it may seem that mechanical engineering and cloud computing are like oil and water. Today, engineers utilize this technology to stay on top of their game. They can instantly access site maps, instruction manuals, and data sheets through cloud storage. They can monitor project work on-site, coordinate with the ground staff, track and order supplies even from a remote location. Hence smooth management of workflow is ensured.

9. Simulation modeling: Computer Science vs Mechanical Engineering

 

Simulation modeling is a way of running an actual or virtual process to find out or estimate the outcome. Real-time data represents the natural world in a simulation model, including humans, products, and machines. Operators can optimize the machine settings in this virtual simulation before implementing them in the actual physical world.

 

CS: While choosing suitable simulation software, the computer scientist ensures the following:

 

  1. Compatibility with the manufacturing process
  2. Consider unpredictable variations in the work environment
  3. Adjust for the scarcity of resources and accordingly gives solutions
  4. Analyze the bottlenecks in data communications, traffic, and transaction processing within the factory and
  5. manage data-flow smoothly

 

The software should aid organizations in managing their daily operations. Finally, the supervisors need to review and select the suggested alternatives.

 

ME: Any engineering design requires validation. Engineers make use of simulations to find flaws in structures. They also need to see what might happen if certain aspects of the plan were changed. The applications are countless:

 

  1. Assessing the turbulent flow of fluids through pipes in cars, ships, and airplanes
  2. Verifying mechanical assemblies like moving parts of an engine or testing a race car’s body in case of a crash
  3. Studying acoustics and their range of transmission in various mediums
  4. Overlook the functioning of complex automated manufacturing systems

 

10.Cybersecurity: Computer Science vs Mechanical Engineering

 

Cybersecurity is the practice of protecting computer servers, mobile devices, electronic systems, networks, and data from malicious attacks. The concept does not merely exist in virtual space. A company’s IT security solely relies on computers and networks alone. It includes several aspects, such as company personnel policies, building infrastructure, computer software, and computer hardware.

 

CS: To conduct a thorough assessment of the IT security systems, organizations have a ‘Red Team/Blue Team exercise’. No, it’s not a time manipulation maneuver as in Christopher Nolan’s ‘Tenet’, but like in the movie, the two teams have to work in good synchrony.

 

Based on military training exercises, ‘Red team/blue team’ is a cybersecurity evaluation tactic that evaluates the strength of the existing security capabilities and recognizes improvement areas.

 

Red teams usually constitute independent ethical hackers, who meticulously evaluate system security. Examples of red team activities are:

 

Penetration testing, aka ethical hacking – hackers gain access to a system using software tools.

 Phishing – these are the seemingly credible emails used to tempt staff members to enter a hacker’s website and provide their own credentials.

Hacking communication software tools:  For example, if attackers know a server was functioning on a Linux operating system, they would redirect their attacks to exploit its specific weaknesses.

Social engineering – a setup where the Red Team tricks staff members into giving access to restricted areas

 

The Blue team consists of security professionals who know the organization thoroughly. Their task is to fortify the security systems so that no intruder can take down the defenses. Examples of blue team activities are:

 

  • Conduct regular audits on domain name servers (DNS) to avoid downtime and prevent/reduce web attacks
  • Analyze digital footprints to chart out users’ activity and identify any potential threats
  • Install endpoint security software on employee laptops
  • Make sure that antivirus software is constantly updated
  • Review server logs and memory to pick up suspicious activities
  • Conduct vulnerability checks regularly

 

 ME: Each security analysis must begin with the physical structure’s strengths and weaknesses. While designing the office, the engineer focuses on the workplace’s structural layout. The following examples are a snapshot of the issues he needs to address:

 

  1. The office is not easily vulnerable to adverse climate conditions like heavy rains, fire, hurricanes, earthquakes, etc.
  2. In case of natural calamities, there must be provision for secured shelter for employees and the data.
  3. Correction of structural flaws like easily accessible windows, vents, basement, and parking space.
  4. Avoid placement of data servers near windows or vents
  5. Strategic positioning of security cameras
  6. Programming entry and exit of office personnel with unique employee key codes

 

Conclusion: Computer science vs Mechanical Engineering

 

As you can see with both specialties, the future possibilities are thrilling and endless. It mainly depends on what type of excitement you wish to pursue in your career. So the next time you get embroiled in a spirited debate of ‘Computer science vs Mechanical engineering’, do not feel bewildered. Hopefully, this article’s points have given you some clarity of thought. Choose well and shine!

 

Dr.Prathima Sivaguru is a Radiation Oncologist trained at the Adyar Cancer Institute, Chennai, and Yashoda Hospital, Secunderabad. She is currently a consultant with HCG Enterprises Ltd (HealthCare Global), a pan-India network of hospitals that focuses on comprehensive cancer care. Apart from oncology practice, she is actively involved in cancer screening camps and awareness talks – with special emphasis on gynecological cancers. During her spare time, she enjoys reading, writing, and upgrading her language skills.

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