Connect with us

Technology

How Natural Language Processing helps the Manufacturing Industry in 2021 [Best Practices]

Published

on

Without a doubt, natural language processing is one of the most advanced and useful applications of AI in a number of industries, including manufacturing. How can you use NLP in manufacturing? What are the examples of natural language processing? And what natural language processing techniques are currently in use? Let’s take a closer look at these questions.

Nowadays, NLP engineers create devices and systems that understand human language. They break language down into shorter, more basic structures, work to understand relationships between various structures, and analyze how structural elements work together to create meaning. NLP engineers use language tools to design algorithms and applications that perform useful tasks using human language.

Companies typically hire NLP engineers to carry out tasks such as:

  • Constructing devices capable of understanding human language and performing appropriate actions on this basis.
  • Developing algorithms that can analyze and generate human languages and are equipped with speech functions.
  • Developing computer programs and applications to understand spoken/written language.

NLP in Manufacturing

When it comes to the manufacturing world, there are several interesting best practices and solutions you can use to improve your everyday work:

OPTIMIZE EFFICIENCY

Thanks to NLP in manufacturing, you can streamline the manufacturing pipeline. For starters, your NLP applications can be used to analyze shipment and production (such as bills of materials) documents to accelerate the whole process. Moreover, NLP algorithms can help you compare different data sources, e.g., concerning transportation rates or resources’ prices. This way, you can optimize your supply chains and identify areas where financial or time savings are possible.

SUPERVISE OPERATIONS

Many people don’t know that, but you can use NLP in manufacturing to keep all operations taking place within your plant under control. NLP algorithms can spot potential discrepancies and alert your employees if needed. All that happens automatically, without the need to hire or engage additional specialists. As a result, your production processes remain intact, and production can continue without any glitches or delays.

PROCESS AUTOMATION

Here, we have to mention two major natural language processing techniques: Classification and extraction. NLP comes in handy not just in the factory itself but also in your office, enhancing several back-office processes. For example, with text classification, you can automate understanding, processing, and categorization of unstructured text. This way, you can facilitate your accounting processes, manage purchase records more effectively, and keep all the HR documentation fully organized. Moreover, if you decide to go with business intelligence one day, NLP algorithms will help you prepare your data for BI purposes.

And what about text extraction? This natural language processing technique will help you digitize old documents and manufacturing records and easily convert printed documents into editable PDF files. With these natural language processing techniques, your paperwork and report analysis can be limited to a minimum, primarily because all the mundane, repetitive tasks can be automated, and your employees can focus on more important, strategic work.

INVENTORY MANAGEMENT

Finally, the manufacturing sector can benefit from natural language processing when it comes to analyzing and gathering your inventory data. This way, you can monitor your inventory more effectively, spot potential discrepancies, and deal with the so-called dead stock issue.

Natural Language Processing Examples

Now, we want to show you a couple of examples of how can NLP in manufacturing be used in real life:

  • IBM Watson offers intelligent manufacturing operations. For instance, IBM’s solution combines artificial intelligence and analytical software to help manufacturing companies analyze even large volumes of unstructured data. IBM Watson uses not just machine and deep learning but also natural language processing to analyze and present data most effectively. Watson offers quality assurance features, production optimization, and energy efficiency enhancements.
  • Manufacturing companies can implement NLP-based solutions to get a more thorough insight into both in-house and market data. Here, we have to mention Deeper Insights, which is a British NLP and machine learning company. They help businesses, including manufacturing ones, make more accurate decisions through data and AI. Today, their greatest invention is the so-called skim engine that allows manufacturing companies to monitor their competitors’ activity, gather and analyze data about their clients, and even monitor specific markets. Their skim engine is essentially a web scraping tool that is trained to make huge data feeds more manageable. Their engine filters out unnecessary information and looks for specific content according to the client’s requirements.

Of course, there are many more examples of companies and applications based on AI and NLP. However, the goal is usually the same–to make your work more effective and facilitated.

If you’d like to know something more about implementing NLP in your manufacturing company, you’re in the right place! Addepto is an experienced AI consulting company. NLP is one of our crucial areas of expertise. See our NLP solutions and make the most of data in your manufacturing company. If you want to know more, drop us a line for details! The Addepto Team is at your service!

The Blogger Scientist is a "Medical Physiologist" and a "Financial Asset" Content Creator who aims at enlightening web reader on varying Financial Assets such as Stocks, FX, Crypto, MLM,. HYIP among others.

Advertisement
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *