5 Reasons to Automate Your Post-Production Planning for Additive Manufacturing15 September 2021
When talking about workflow management for additive manufacturing, it’s quite typical to think solely in terms of the production steps: scheduling incoming requests and preparing machines, for example. But what about managing the stage after production?
Surprisingly, post-production management is a frequently overlooked part of the additive manufacturing process. Many companies remain unsure as to how to most effectively manage this stage and ensure a seamless flow between production stages. Read on for more about post-production management – and how workflow management software can help to streamline and automate this stage of production.
What is post-production management?
For additive manufacturing, post-production management refers to the process of planning and coordinating all of the required actions once a print run has been completed. This includes, although isn’t limited to:
- Planning post-processing tasks
- Conducting quality assurance (QA) checks
- Managing logistics
Post-production management: manual vs. automated
Today, the vast majority of manufacturers use manual processes to plan and execute their post-production tasks. Let’s take the process of identifying parts post-build as an example.
Each completed build is made up of several parts that will need to be unpacked, identified and inspected before being moved to the next stage — for example, post-processing. However, to identify a part, a production engineer will more often than not need to refer back to a printed job sheet, essentially matching a 2D image to its physical counterpart and checking off requirements manually.
In this example, such a process has two clear drawbacks: it takes a significant amount of time, and there is a lack of workflow visibility.
These are key disadvantages of any manual process, since data needs to be passed physically from one task owner to the next. If we’re thinking of additive manufacturing in terms of its potential for mass production, it’s clear that this way of managing the post-production process is not scalable for manufacturers in the long term.
On the other hand, automated processes usually involve digital-based data and communication. This presents key opportunities to streamline the entire post-production planning stage. With the right workflow software, automated processes can help to reduce the chance of human error and provide a centralised platform for users to easily communicate across all areas of production.
5 perfect use cases for automating post-production management
#1 Post-processing planning
As a significant part of the additive manufacturing process, post-processing is one of the first things that comes to mind when thinking about the post-production stage.
Depending on the 3D printing technology used, 3D-printed parts will require different types of post-processing. SLA parts, for example, will require support removal at the very least. Parts produced with SLS could require dyeing, metal plating or other post-processing methods. Some post-processing techniques, like bead blasting, can be done in batches, requiring a certain number of completed parts before the task can be undertaken.
From this alone, it’s clear that post-processing planning can easily become a logistical headache, especially if you’re dealing with hundreds of projects and several different machines. Among other things, resources need to be allocated and task owners assigned for each project.
If we add to the mix the fact that the post-processing stage currently accounts for 30-60% of the additive manufacturing process, using manual processes to manage and coordinate this step only serves to prolong the process. For maximum efficiency, it, therefore, makes sense to automate the task of planning your post-processing activities wherever possible.
Workflow management software comes into its own by helping to automate this process. For example, AMFG’s Post-Processing Scheduling system, can be used to allocate the correct post-processing tasks and establish the right sequence of actions to be undertaken.
#2 Faster part identification
Here’s a scenario that any production engineer may recognise: you have a completed build on your hands with parts that now need to be identified and assigned, typically to the post-processing stage.
Identifying your parts after production is a crucial part of the process. Before quality assurance can be conducted or post-processing completed, parts will first need to be identified. However, for the vast majority of additive manufacturing departments, identifying and tracking parts is a completely manual process. Printed job sheets are often used to compare the 2D image with the physical part.
Using workflow management software to automate this process can go a long way to simplifying the part identification stage. With part data and specifications already logged in the system, it’s simply a question of checking in which build a part is located using the software. The software can also display 3D CAD models which can be used to enrich the inspecting process.
#3 Enhanced quality assurance
As additive manufacturing moves from prototyping into production, ensuring that parts meet the required standards is key. Quality assurance (QA) control is, therefore, an ongoing step at each point during the post-production stage.
If today QA checks are manual and involve a fixed set of checkboxes, workflow management software can help to digitise this process.
For example, this can include a 3D viewer, complete with data, allowing you to inspect the part and its properties more accurately. Such systems can also import reports from external data sources, like sensors and barcodes, giving you a faster way to ensure that your parts meet the required specifications.
#4 Robust data management
Process repeatability is a crucial criterion for manufacturers, although this has historically been one of the factors hindering the wider adoption of 3D printing technologies. However, managing data correctly is one of the keys to achieving a repeatable additive manufacturing process.
Manufacturers need to consider the data management requirements that arise during the post-production stage.
Let’s take quality assurance as an example. QA for additive manufacturing is an area that requires a robust data management process, as one build can represent a huge amount of data: potentially tens or hundreds of terabytes.
Not only this, but key part information will need to be stored, updated and in all cases maintained.
Maintaining mountains of data in a digestible way is virtually impossible to do manually. But with dedicated workflow management software, the digital approach enables the storage of data, 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 post-production planning and wider production processes.
#5 Integrated communication tools
If you’re running several machines and producing hundreds of thousands of parts, traceability will be key to ensuring a successful additive manufacturing operation. And this can most effectively be achieved through workflow management software.
Another real-life scenario: an engineer may require an update as to the status of their requested prototype.
With a traditional process, the rapid prototyping facility, which is perhaps located elsewhere, will need to check through a spreadsheet system to find the part and email a response.
Multiply this by a factor of ten and more, and this leads to significant back and forth emailing and a lot of effort spent chasing up the status of projects.
Now, let’s replace this workflow management software. The AM department can now easily find the project within the system, complete with project information, deadline and expected delivery date and other required information, in a matter of seconds.
Alternatively, assuming that the appropriate user permissions have been set, the engineer could verify this themselves within the system, checking the project status without having to contact the RP department.
This example illustrates the way workflow management software can help to facilitate communication between the design, planning and production teams, ensuring that everyone is up to speed.
Automation: the future of post-production management
As we’ve seen, workflow management software shouldn’t stop at the production stage. For manufacturers seeking a workflow management solution, key criteria to look for is how well the software can connect post-production planning to the rest of the additive manufacturing workflow, including:
- Part identification
- Post-processing scheduling
- Communication between planning and production
For OEMs seeking the best way to adopt additive manufacturing, it’s not enough to look solely to the hardware or materials to facilitate this. If you’re looking to create a scalable production operation, it’s also a question of adopting the right software infrastructure to support this.
Discover how AMFG can help you set up scalable infrastructure for your AM operations
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