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User Story

Medical Device Company Achieves Design-at-Scale of Additive Implants with Batch Processing

An established medical device company used nTopology to develop medical implants with novel osseointegrative lattice structures.

After the R&D team created a mature design workflow that defined all technical parameters of their design, a key challenge still remained. How could they apply this new lattice to their whole range of 100+ implantable orthopedic devices? Manual data processing would be time-consuming and prone to errors.

To automate this step they used batch processing with nTopCL. With a simple script, they applied the new lattice design to the whole product family in just under 6 non-business hours.

This repeatable process enabled the team to create design workflows that are traceable and easy to maintain and saved thousands of dollars in operational costs for their business.

Key Takeaways

  • Develop lattice structures for additively manufactured implantable orthopedic devices that promote osseointegration
  • Create standardized, traceable, and controlled processes by packaging key design parameters in reusable workflows
  • Batch process a whole product family of medical implants using a simple Python script in nTopCL

Business Value

  • Time advantage: Generate complex lattices 3x to 10x faster than with any other design software to launch products faster
  • Reduced operational risk: Eliminate error-prone data input steps from your design workflows and ensure traceability
  • Better product development: Maintain 1 design workflow instead of 100 design files and focus on value-generating aspects of product design

Key Statistics

Number of parts in product family

100+

Total processing time with automation

6 non-business hours

Invested engineering time savings

90%

Computational time savings

50%

Operational cost savings per batch processing

$1000+

Operational risk of automation

Close to 0%

Developing Lattices that Promote Osseointegration

Lattice structures that improve osseointegration of orthopedic implants are one of the most prominent medical applications of Additive Manufacturing today. But, even if you overcome the initial barrier of developing a lattice that yields consistent results and is submission-ready, there is one more operational caveat; scaling up the design processes using traditional tools can be time-consuming and prone to errors.

To tackle this challenge, an established company in the area of orthopedic devices used nTopology developed and automated its design workflows. With a simple script, they automatically applied their standardized osseointegrative structure to a product line of more than 100 parts overnight. Using batch processing, they saved valuable engineering time and thousands of dollars in operational costs.

This user story highlights an example from the medical device industry. Yet, the benefits of batch processing are universal. The same process can be easily replicated in any industry vertical and any product line that has a large number of part numbers.

From R&D to a Standardized & Controlled Process

During the development phase, the design engineers of the orthopedic device company focused on fully defining every parameter of the osseointegrative lattice. The goal was to create a structure that could fulfill all design requirements and still be manufactured in a repeatable way.

With nTopology, they explored multiple design variations of a highly-porous trabecular structure. By adjusting key parameters of their workflow, they controlled every aspect of the lattice beams, including beam thickness and the pore size. They also introduced gradients to create a smooth transition between the highly porous lattice and the structurally-critical solid regions of the implant.


Overview of the basic steps of the design workflow during the development phase.

The next step was to prove that their workflow could produce consistent results independent of the geometry of the imported CAD part, the computer that was used, or the version of the software. This way they could confidently reuse the same workflow on a whole product family.

One way to achieve this goal is by generating a traceability report. Using a few simple blocks, they enhanced their existing workflow with a reporting functionality that documented critical design outputs in a text file. They recorded important lattice properties, such as its mass and surface area as well as the characteristics of the mesh. This functionality can be built into any workflow to keep your design process traceable and your QA team satisfied.

At this stage, their design process was mature and almost ready for production. The final step was to package the workflow into a single, custom nTop block. Custom blocks expose only the necessary inputs and outputs to the user, ensuring that critical design parameters remain unchanged. This way you can share your design workflows with other nTopology users and create revision-controlled processes to ensure transparency and traceability.


Once the design workflow is mature, it can be packaged as a revision-control custom block.

Design at Scale with Batch Processing

The classic approach to using nTopology is to import a CAD file, convert it into nTop’s lightweight and powerful native data model, generate intricate geometry using advanced design operations, and finally create a manufacturable output — for example, an STL file. Once the design workflow is mature, not only can it be reused on every unique part of a product family, but it can also be scaled across the entire organization.

In this example, the design engineers automated the process of applying their standardized osseointegration lattice structure to their entire product line through batch processing. Using nTopology’s Command Line Interface (nTopCL), they created a short Python script to batch process the entire product family.


Batch processing with nTopCL automates the time-consuming step of manual data processing.

In total, it took approximately 1 hour of invested engineering time to create the script and prepare the CAD data for processing and 6 hours of unsupervised computing time to execute it on more than 100 unique part configurations — averaging 3-4 minutes per part.

For comparison, executing the same process in nTopology by hand required 12 hours of dedicated engineering time. This is, of course, on top of the speed and design benefits that nTopology offers over traditional CAD software (3x to 10x faster based on user benchmarks).

The Benefits of Design Automation

To make the benefits of design automation tangible, here are the results of the benchmarking test that the engineers of the medical devices company performed. The goal was to compare the speed, accuracy, and cost of using an automated versus a manual process.

Time Savings

  • From 1.5 days to 6 non-business hours
  • 50% reduction in computational processing time

With automated batch processing, the engineer does not need to input data manually. This eliminates a repetitive and time-consuming step and cuts in half the total time required to process 100 unique part configurations. Moreover, the script can be run overnight, essentially reducing the waiting time to zero.

Reduced Operational Risk

  • From manual data entry to automated data processing
  • 100% overlap between manual and automated results

Manual data entry is prone to user error. By automating this step, the operational risk is essentially reduced to zero. The benchmarking results show 100% accuracy between the outputs of the manual process and automated results produced with different machines and software versions. This increased the confidence of the engineers to the batch processing outputs.

Business Value

  • From 12 invested engineering hours down to 1 hour
  • 90% reduction to operational costs

From an overhead perspective, by automating the process the invested engineering time is reduced from 12 hours down to 1 hour. This means that every time an engineer creates and runs this or a similar script, the company can save $1000+ dollars in operating costs (calculated based on the average biomedical engineer salary).

Better Product Development

  • Implement changes to 1 design workflow instead of 100 design files
  • Time and labor constraints are no longer a design bottleneck

The engineering time that would have been allocated to repetitive tasks, can now be re-allocated to other value-generating parts of the business. This enables the design of overall better products and services. With the increased efficiency and flexibility that design automation brings, your engineers’ time can be used to explore more design options. This gives you more opportunities to create unique and higher-performing products.

Removing Bottlenecks in Product Development

Design automation is not the only way to use nTopology. The engineers of this orthopedic device company generated great value for their organization by taking advantage of the advanced modeling capabilities of nTopology to design unique geometries and by standardizing their design workflows.

Design automation opens up new ways to think about product development. It can fundamentally change the approach to engineering design and opens up new possibilities for innovation.

The goal is not to overhaul the way the industry chooses to develop and validate their medical devices. The goal is to remove the bottlenecks that currently exist in the product development process.

The Next Steps

Moving forward, the engineers of the orthopedic device company are transitioning from designing products to designing engineering workflows. Design automation and batch processing will play an important role in this goal and will continue to provide tangible benefits and costs savings.

If you would like to see for yourself how design automation with nTopology can benefit your organization and why leading companies in the aerospace, automotive, medical, and consumer goods industries rely on it, request a demo.

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