Modernizing Technical Documentation for Industry 4.0: A Complete Guide

The manufacturing industry has undergone significant changes over the years, marked by several industrial revolutions. But as manufacturing has evolved, there are processes or activities that go with it that haven’t kept pace. Technical documentation is one of these. As we move deeper and faster into what we call “Industry 4.0,” or the 4th Industrial Revolution, we realize more than ever that the processes we need to create, manage, and deliver manufacturing documentation need to catch up fast.

Industrial revolutions are periods of significant industrialization and innovation. Just in case you aren’t up to date on the four industrial revolutions we’ve gone through, here’s a summary. 

• First Industrial Revolution: In the late 18th century, we saw the mechanization of manufacturing using water and steam power.
• Second Industrial Revolution: From the late 19th to early 20th century, there was the Technical revolution. During this period, machinery was widely used, the railroad expanded, and mass production and assembly lines were established. Electricity, oil, and gas were dominant.
• Third Industrial Revolution: Called the Digital Revolution, the mid-20th century saw the shift from mechanical and analog electronic technology to digital, including computers and automation. 
• Fourth Industrial Revolution: We’re in this one now. It started around the mid-2010s and is driving the dramatic transformation of manufacturing and other industrial sectors. We’re talking artificial intelligence, mass customization, IoT (the Internet of Things), robotics, and improved collaboration between machines and humans. 

We call the fourth industrial revolution Industry 4.0, and it’s never been more fascinating. A significant transformation is occurring in how manufacturing processes are conducted, starting with the integration of digital technologies: 

• IoT connects machines and equipment through sensors and networks, enabling the sharing of vast amounts of data that are collected and analyzed in real-time. 
• Big Data and analytics leverage all this data to improve decision-making and support predictive capabilities. 
• Artificial intelligence (AI) and machine learning (ML) help analyze data faster, predict issues before they arise, and automate tasks.
• Advanced robotics are being employed for repetitive tasks.
• The shift to cloud computing and cloud-based storage provides real-time access to data from anywhere and supports collaboration worldwide.

How do the advancements happening as part of Industry 4.0 affect the way technical documentation is created and managed? It’s forcing an equally important shift. 

Although we often discuss digitizing technical documentation and point to technologies such as component content management systems (CCMS) to manage it, many paper-based, manual processes are still used in manufacturing. Even companies beginning to use digital technologies to manage their documentation are struggling because they aren’t using the right ones. Many of the challenges come down to agility and speed.

There are many types of documentation created and used in manufacturing, including work instructions, standard operating procedures, manuals and operating instructions, troubleshooting guides, quality assurance documentation, and more. 

This documentation isn’t static; it changes constantly to keep up with product changes, new product development, and maintenance and repairs. As machinery is updated or manufacturing processes change, the corresponding documentation needs to be updated as well.

But that’s just the start of the documentation challenges in Industry 4.0. Mass customization is a major advancement that allows customers to request customizations to support specific requirements. With customized products comes the need for customized documentation that matches the exact specifications. 

And then there are the embedded sensors and interconnected machines. Sensors can detect problems with a machine and will need access to documentation to find details on the problem and how to fix it. All this happens without human intervention and requires documentation to be created in a way that machines can read.

We’re also seeing a greater need for technical documentation in different formats (e.g., visual, text, interactive) across different channels (e.g., web-based documentation portals, knowledge bases, downloadable PDFs) and in different languages. 

It’s clear that things need to evolve for documentation teams.

Technical writers in the manufacturing industry can adopt some of the practices of their peers in software documentation to help them succeed. 

A common approach for software documentation teams is to follow agile documentation practices. In agile software development, software is built in shorter, iterative cycles to deliver software sooner. As a result, their documentation teams have built a process that includes frequent updates and iterations of the content. By following a similar agile practice, manufacturing documentation teams can keep up with changes to manufacturing processes and products, ensuring the documentation is consistent and accurate.

Multichannel delivery is also key for software documentation teams because their documentation is provided in different formats, including manuals, in-app help content, customer portals, and more. The ability to use one tool to create and manage documentation published in different formats and channels is key to their success, and manufacturing teams that follow a similar strategy can meet the growing needs of their customers.

Software documentation teams often use Git for documentation version control, matching the software versions they deal with. They also collaborate closely with product teams to ensure the documentation is accurate and up to date. Manufacturing documentation teams can follow a similar approach using a CCMS (we’ll talk about this more in a bit). 

Software documentation focuses on user experience. Explaining information in a way that’s easy to understand and follow is essential for successfully using software. Manufacturing documentation should follow the same user-centric design. Documentation that is accessible and user-friendly, including the use of visuals like diagrams and schematics, can help operators who work with complex systems. 

The last one we’ll talk about is the use of metadata. Software documentation teams will apply tags and categories to their documentation to make it easier for end users to search and find the information they need to use the software. The application of metadata supports advanced search and filter functionality, including faceted and topic-based search. Manufacturing documentation teams can follow the same metadata strategy to help their users find information faster, but the same metadata is also used by smart sensors that don’t interact with humans at all to find information and apply solutions. 

If you are a documentation professional who wants to work in manufacturing, we have a few tips to help you succeed. 

Structured content is an approach to creating documentation that looks at content as discrete topics, not as an entire piece of documentation. You break documentation down into components, each standing independently with a specific type of information. There is a lot of reused information across documentation types in manufacturing, so instead of writing the same information over and over, you write it once, and then you can put together (reuse) the topics needed to create a specific type of documentation.

Although structured content models aren’t typically complex (or at least they shouldn’t be), it can take some time to understand the appropriate way to break down your documentation for it to be the most useful. So, learn how to create structured content and practice. Then, once you are ready, apply it to your documentation to see how much faster you can create your content following this reuse model.

To complement a structured content model, you need a taxonomy composed of categories, subcategories, and tags. Work with your team to define the taxonomy, but remember that it’s iterative, so you’ll need to plan for continually evaluating and changing it as new products are built and existing products are changed.  

There was a time when most technical content was text-based, but times have changed. End users expect documentation to be available in different formats. Some prefer videos or interactive guides, others want a lot of screenshots and diagrams, and others prefer clear text. Also, visual content, especially diagrams or screenshots, can get outdated much faster than text-based content, so be sure to plan to think about how you’ll need to manage changes.

Get familiar with your documentation end users and their expectations, and ensure you provide content in the formats they want.

Manufacturing documentation requires the input of many different teams or groups. Be sure to map out the workflow from starting a new piece of documentation to finalizing and publishing it. The workflow should include everyone involved and their roles and responsibilities.

As manufacturing systems become more interconnected, your ability to understand API (Application Programming Interfaces) documentation becomes critical. API documentation explains how different systems interact, giving you the context needed to write manufacturing documentation well. 

Generative AI (e.g., chatGPT, Claude, Microsoft Co-Pilot) can help speed up content creation, and it’s becoming a key feature of content management systems. Take the time to test it out and see how it can help you write technical documentation, whether building outlines, creating metadata, or writing the actual content. If it’s not part of your team’s process yet, it will be, so you need to understand how it impacts your work. At the same time, it’s critical to ensure that human review is a part of any process that uses generative AI. We are not at the stage where AI like this can be autonomous.