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The Digital Disruption in Mechanical Engineering

Posted By Prof Wikus van Niekerk, Tuesday, 18 September 2018

The Fourth Industrial Revolution is fundamentally changing the world of work for which we are preparing our students and where mechanical engineers are applying their trade. At the same time the students who enter university programmes are much better prepared for the Digital World than they were in the past, expect for those students, in the South African context, who come from disadvantaged environments. 

Universities tend to be slow to react to changes in the environment and therefore all these factors put together result in a significant challenge for the development and implementation of Engineering Programmes. 

Over the last three decades most universities were quick to introduce computer programming in their programmes, as engineers had a strong vested interest in this field and always had a significant  requirement for fast and accurate computing.

The integration of fast computing, big data and machine learning enable engineers to be significantly more productive than in the past by speeding up and integrating processes, from design to manufacture, implementation and commissioning. This new approach is also blurring the boundaries between disciplines forcing mechanical engineers to work collectively in multi-disciplinary teams with other professionals. It also poses new challenges such as mastering software suites and manipulating complex digital models of physical systems.

Digital moods
“Multiphysics” refers to digital models that can simultaneously solve multiple physical phenomena. These models speed up the design processes and deliver large amounts of data that need to be analysed. It is now possible to simultaneously model and compute the fluid-dynamics over the wing of an aircraft as well as the forces and deflections (stresses and strains) the varying pressure profile will induce in the structure.

This is of course a very powerful “tool” that can be used to optimise the aerodynamics and structural elements of the wing in a very short time. 

Big data

Where we may have not been at the forefront is in the use of Big Data. These very large data sets have been available for many years in the Financial and Health sectors where. Colleagues working in the maintenance field, and especially the condition monitoring of mechanical and electrical plant, have had access to larger data sets but mostly used deterministic and statistical models to analyse the data.

The challenge we face going forward is that modern technology, including the Internet of Things, will make large data sets more readily available and we will need to understand how to handle and analyse the data. Data need to be prepared by cleaning it up, verifying and calibrating it, collating from different sources and then storing the data in a format accessible for the various algorithm that can be used to discover the embedded knowledge.

This new approach is also blurring the boundaries between disciplines forcing mechanical engineers to work collectively in multi-disciplinary teams with other professionals.

There are a host of methods available to analyse the data, extract information and discover the knowledge. Many of the new methods make use of artificial intelligence and machine learning where the algorithms, with minimal human input, can analyse data and discover new phenomena that
were not previously known. 

Reality check
The old saying “garbage in – garbage out” still holds and we will always need the fast and multi-processing skills of the human brain to look at the outcome and do a “reality check.” Recent experiences on the highly-automated Tesla assembly lines with the lack of humans on the line were identified as a key contributor to their not achieving the volumes and level of quality they desired.

Therefore, digital disruption in the world of mechanical engineering will indeed bring additional challenges to our fraternity. We will have to equip our new as well as experienced engineers with the necessary skills and understanding of modern data science but at the same time we must always ensure that these mechanical engineers have the required fundamental knowledge and experience to ensure that the new methods provide useful and technically valid results.

Yours in Mechanical Engineering,

Prof Wikus van Niekerk
SAIMechE Council Member

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