How Digitisation Can Help Transform AM Post-Processing and QA Management

This is Part 3 of our series on MES software. Discover the rest of the articles in this series:

• The Beginner’s Guide to Additive Manufacturing Execution Systems (MES)
• How Can MES Software Transform Production Planning for Additive Manufacturing?

• 3 Ways Connectivity Will Enhance Your Additive Manufacturing Operations

 
Additive manufacturing is moving towards industrialisation. With 46% of companies planning to use AM for serial production within the next two years, post-processing and quality management are becoming critical for businesses looking to use 3D printing for production. 
 
And yet, managing post-processing and quality assurance is still a key challenge for the vast majority of companies. The manual nature of post-processing, coupled with the time needed to ensure parts are qualified for use, requires clear planning and coordination from the start.
 
In this article, we’ll be exploring why post-processing and quality management are crucial for AM, the challenges companies most commonly face in this area and how digitisation can help to overcome these bottlenecks. 
 

Why post-processing and quality management are essential steps in the additive manufacturing process

Often, discussions on using additive manufacturing for production tend to focus on the production process itself. 
 
However, the AM process isn’t completed once a part has been 3D printed, as the part will almost always need some form of post-processing in order to achieve its final properties. 
 
So as companies take steps to establish clear processes for production planning and workflow connectivity, it’s also vital to consider all of the steps that will be required after the part has been taken from the printer.
 
For end-part applications, this is even more important. As additive manufacturing transitions from prototyping and tooling to production applications, post-processing and quality management will become critical process steps. 
 
Some of these steps include:

• Identifying parts post-print
• Planning and coordinating post-processing tasks (e.g. sanding, beadblasting etc.)
• Conducting quality assurance checks to make that the part meets the required standards

To achieve optimal efficiency, each of these post-production steps will need to be managed and coordinated as part of an integrated production workflow. 
 

Common challenges with managing post-processing and quality assurance

Coordinating the post-processing workflow with different 3D printing technologies

Post-processing covers several different methods needed to get the final 3D-printed part, and different 3D printing technologies will require different types of post-processing. 
 
SLA parts, for example, will, at the very least, require support removal at the very least, while parts produced with SLS could require dyeing, metal plating or some other form of post-processing. Metal parts will also need extensive post-processing.
 
Additionally, some post-processing techniques, like bead blasting, can be done in batches, requiring a certain number of completed parts to begin the task. 
 
Since different technologies will require different post-processing methods, the level of workflow complexity will increase the more technologies there are in the workflow.
 

Time-consuming manual processes

While much is being done with hardware to automate post-processing, managing the post-processing and QA workflow is still very much a manual process for most companies. 
 
Often, this is because multiple people and process steps need to be coordinated at each stage. Not only this, but QA control requires documentation, to ensure that the part meets the right specification.
 
As a result, planning is essential — but not always straightforward. 
 
Using paper printouts and other manual systems to manage the post-processing and QA stage is highly inefficient in the long run, particularly as operations scale and more technologies are added to the workflow. 
 

Communicating effectively with suppliers

For most manufacturers, much of the post-processing tasks are outsourced instead of done in-house. This requires visibility across an OEM’s entire supply chain. 
 
And yet, achieving such a level of visibility is challenging without a digital system in place to track communications, job statuses and real-time actions. 
 

How digitisation can streamline post-processing and QA management

Digitisation integrates post-processing and quality management into the AM workflow

From a strategic perspective, post-processing and quality management should be considered as an integrated part of the AM workflow.
 
But very often, this stage is either overlooked or considered separate to the production process.
 
Digital transformation, through the use of MES software, overcomes this bottleneck by ensuring a seamless flow of data between the production and post-production stages. It allows you to establish a sequence of post-processing operations, so it’s clear what is meant to be done, when and by whom.
 
It also enables easier communication with external partners and suppliers. For example, MES software enables you to reroute work orders, including post-processing tasks, to a selected supplier in real-time.
 

Easier quality control documentation

As AM moves from prototyping into production, ensuring that parts meet the required standards is vital. 3D-printed parts will need to meet the same qualifications as traditional manufacturing processes – and quality criteria will differ from industry to industry.
 
Quality control is, therefore, an ongoing step at each point during the post-production stage. But due to the need to document key data and information, it can quickly become time-consuming.
 
If today, QA checks are manual, involving a fixed set of checkboxes or printouts, MES software can help to digitise this process. For example, this can include a 3D viewer that allows you to inspect the part and its properties more accurately.
 
AMFG’s MES software also allows for the import of reports from external data sources, like sensors and barcodes, offering a faster way to ensure that parts meet the required specifications.
 

Collect and centralise data 

Challenges around part qualification have been a key barrier to wider adoption of AM.
 
However, data is critical to ensuring part qualification and certification of parts.
 
Therefore, companies must consider the data management requirements that arise during the QA stage, as this requires a robust data management process.
 
To illustrate: one print build can potentially represent tens or even hundreds of terabytes.
 
Maintaining such a large amount of data in a way that is manageable is impossible to do manually. But a digital approach with MES software not only enables data to be stored, but also presents it in a way that enables actionable insights –  including a rich data history for each individual part.
 
When incorporated with data analytics, this information proves invaluable for maintaining visibility throughout your organisation and allows you to continue to optimise your entire AM operations.
 

Looking to the future: Digitising post-processing and QMS

As we’ve seen, managing the AM workflow shouldn’t stop at the production stage.
 
For companies looking to adopt additive manufacturing for production, considering the strategy for managing the post-processing and quality management is crucial.
 
Fortunately, digitalisation offers a valuable way to streamline this process. Using MES software will not only enable you to track all of the post-processing steps and QA documentation, but it also allows you to connect this critical stage to the entire AM workflow – and scale your operations.
 
Learn more about post-processing and QA management for additive manufacturing

If you’d like to learn more about best practices for managing your additive manufacturing operations, we recommend reading our new white paper, Additive Manufacturing MES Software: The Essential Guide.
 
As well as providing more insights into post-processing and QMS planning for AM, you’ll learn more about how to develop a comprehensive AM strategy and how you can use MES software to help you scale and expand your AM operations.