Data Science in Industrial Engineering

Data Science in Industrial Engineering

Industrial engineering (IE) is a field which has been around for a very long time and it’s a position which is exceptionally important when it comes to basically every different form of manufacturing.

In its simplest terms, IE is a profession concerned with optimizing complex processes and systems involved in major engineering and manufacturing. These engineers have to consider a variety of different factors when organizing these systems.

They have to utilize employees, money, information, materials, equipment and knowledge to ensure that every process involved in the particular area in which they are operating can achieve its full potential.

As you can probably imagine, covering all of these bases means dealing with a huge amount of data. And this means that in the last few decades, the significant changes in data science have led to changes in IE too.  To give a little bit more context for IE.

The role of Industrial Engineering in Data Science

An industrial engineer would be required to aid in optimizing the design and construction of buildings and other large scale infrastructure projects, as well as the development of ongoing projects more in the line of oil rigs and dock yards.

IE isn’t concerned with the development of anything specific such as a civil or electrical engineer, but instead covers a very broad scope and can be applied to any number of different kinds of processes.

As such, the engineers are required to develop a large number of different kinds of skills, including things like diplomacy, leadership, negotiation and time management. Keeping that in mind, let’s consider data science in its current form.

What is Data Science?

Data Science is a science which, like IE, has been around for a very long time. The term was first used in the 1980’s, though it did technically exist before that because the processes involved have been around as long as data has been. 

Data science aims to extract valuable and usable insights from both structured and unstructured data. It’s an interdisciplinary field which uses statistics and informatics to understand a variety of different things.

It can be used to develop a better understanding of business trends, it can be used to analyze astronomical phenomena, the advancement and effectiveness of medical technology and of machinery and artificial intelligence.

Perhaps the biggest development in data science recently has been the rise of big data. Considering how much technology has advanced even just in the last few decades, big data was an inevitability.

What it refers to are data sets which are too large or complex to be dealt with by traditional data-processing software. Big data has become more prominent now since we have the capacity for massive amounts of digital storage.

It encompasses things like audio, video, spreadsheets, text and various other datasets. When you think about just how much data you have access to even just from your own personal computer, big data might sound like something that’s impossible to control and utilize.

But it’s actually the most important aspect of data science present in IE today, on account of just how much relevant information can actually be extracted through it. Let’s take a look at how it’s used. 

Data Science Usage in Industrial Engineering

In order to extract information from big data, there is a common process known as ‘mining’. This basically just means sifting through huge amounts of data, and these days it often requires the usage of artificial intelligence. 

Industrial engineers can garner huge insights through data mining which will be very valuable when perfecting a complex process. It’s especially useful for the discovery of defects and inconsistencies in manufacturing.

Problems would have often flown under the radar due to the fact that developing a very complex system generates a massive amount of data and outdated systems wouldn’t be up to the task of processing it all.

So things would have been missed. There’s also transparency to consider here, because IE involves the organization of manpower too as well as ensuring that everyone important involved in a particular project has access to as much information as they need.

It can be difficult to maintain a level of transparency and ensure that everybody can be content in the knowledge that they can trust each other. If you make it clear that big data mining will be a part of your process, then stakeholders can be confident that their access to data won’t be limited.

As an example, take a look at Vista Projects approach to data in an age of digital transformation, with particular focus on what they describe as a ‘single-source of truth’. This is essentially a database which can be set up for a specific process, through which you can grant access for relevant information to those who are entitled to it.

Data Science and Industrial Engineering

Data science in IE also ensures that every single detail of a manufacturing process can be tracked and this helps to minimize waste and project future trends related to the project. 

More about What Data Science Actually Means To Manufacturing

Without data science, IE in 2021 would be a very restricted field. We can be confident that the future of the industry is brighter than ever now that we have learned more about how to mine data that seemed so difficult to handle in the past.

 

About the Author

This article was written by Andy Schmidt. Andy has been in the online content world for over 10 years as a freelance copywriter, technical writer and translator, covering different topics – finance, energy and also sustainability. What is he doing when not writing? Andy learned how to enjoy long walks, play chess, and finally – how to sleep at night.