Artificial intelligence (AI) is gaining momentum across a vast array of fields. Nearly everyone has tried or actively uses a form of AI, whether for personal or professional purposes. Many are finding benefits of the technology in industries that use large amounts of data that must be analyzed, consolidated, or organized.

Two sectors in particular that meet these criteria but might not be at the top of your mind when imagining the beneficial applications of AI are engineering and manufacturing.

For centuries, engineers relied on manual, handwritten designs as the blueprints for their creations and subsequent manufacturing processes. Countless times, these designs were the only thing used to re-create a tool or machine part.

Today, engineers and manufacturers are looking to AI and digital solutions as a means to preserve these valuable designs and continue to build upon the wealth of knowledge preserved in their libraries of manual drawings. As we explore the applications of AI and knowledge-preservation solutions regarding hand-drawn designs, we’ll realize that solutions to this longstanding problem are available and that the question is more about the speed of adoption.

The challenge of legacy designs and techniques

Manufacturing drawings are specific diagrams that depict the exact dimensions and proportions of a product, part, machine, layout, or other technical item. Similar to architectural blueprints in their level of detail, these drawings are tailored for items that will be produced by machine shops. They contain all the information required to make the depicted product.

Engineering is a millennia-old profession; understandably, designs had to be drawn out on physical material and preserved. Not only were designs drawn on material that could degrade over time, but any adjustments or modifications to the original design were made directly on the same material. This resulted in a high degradation rate of design drawings, especially intricate notes and specs, creating a pressing need to preserve their critical information as efficiently as possible.

Capturing the various modifications made to legacy designs also proved difficult, given that multiple people were sometimes involved in the iterative process over multiple decades.

As machine-part design became digital during the late 1950s, converting older handwritten designs, known as legacy designs, into digital format remained a challenge. MIT researcher Douglas Ross was the first to introduce the term “computer-aided design,” but design software remained limited through the 1960s, only able to create digital drawings, not convert existing legacy drawings into digital counterparts.

Capturing the various modifications made to legacy designs also proved difficult, given that multiple people were sometimes involved in the iterative process over multiple decades. Furthermore, engineers and manufacturers often had vast libraries of physical legacy designs, with a select few individuals knowing where a particular drawing was located or having knowledge of similar drawings that could benefit the current project. All these factors contribute to inefficiencies affecting everything from initial design to procurement.

A limited shift to digital

As the design process progressed into the digital realm, tools emerged that could digitize legacy drawings and organize them into digital libraries. This was a significant milestone because engineering libraries were often preciously guarded assets, and technology was advanced enough to accurately convert all the information on the legacy design into a digital file. However, the problem of organizing these digital libraries and making their contents readily accessible to engineering teams persisted.

It’s hard to imagine just how extensive engineering libraries can be. Converting an entire library of legacy designs into digital assets could entail scanning and inputting tens of thousands of drawings, each containing ample information. The industry needed a solution to help organize and sort the massive amount of digital assets to make them easily accessible and allow separate departments to collaborate seamlessly on modifications to a legacy design. This is where AI-powered software shines as an appropriate solution.

The new era of manufacturing drawings

Today, software solutions are available that can digitize and automatically index all of your manufacturing drawings and make them searchable and sortable with all the information in them. Cutting-edge, AI-powered solutions allow you to search a library by sketching a part you’re looking for or uploading a similar drawing. This instantly finds all the drawings that overlap in dimensions, features, and more.

On top of that, data in title blocks can be turned into true searchable assets. Older drawing digitization software required you to enter information in these blocks manually—a process that was tedious, often inconsistent, and sometimes outright skipped. Now, technology can automatically parse them into sortable, filterable, and searchable fields.

You can save hours searching for old drawings to make new designs faster and better.

You can save hours searching for old drawings to make new designs faster and better. Once you find the drawings you need, every related piece of data about each design, from order history to quality rates to sales quotes, can be compiled to enhance decision-making.

AI preserves and enhances the value of legacy designs

Over the past eight years, advancements in AI-powered software have made it easy to preserve, digitize, and access legacy designs. Solutions providers can now help engineers and manufacturers digitize all legacy drawings and deploy an AI-powered solution to organize, analyze, and sort them via their contents. These AI-powered solutions can perform pattern recognition on all converted legacy drawings, allowing search functionality and quotation price consolidation, overcoming the challenges of knowledge preservation and creating continued value on legacy designs.

With these solutions, legacy drawings can continue to provide value for engineers and manufacturers and can be further enhanced while preserving the content of the original design.