Connecting the Digital Thread: Scaling Additive Manufacturing with MES/Workflow Software
Manufacturing, like so many industries, is experiencing a digital transformation. Increasingly, manufacturers are investing in digitalisation, with 74% agreeing that they will need to adopt digital technologies in order to prosper. However, while most manufacturers recognise the need to invest in digital technologies, successfully implementing these technologies remains a key challenge.
Additive manufacturing (AM) is one of the technologies at the heart of this digital transformation. AM encompasses a broad range of processes that enable parts to be manufactured from a digital CAD file — and 80% of companies say that the technology is improving their ability to innovate faster.
However, investing in additive manufacturing is one thing; creating an AM facility that is both connected, in terms of hardware and systems, and scalable is quite another.
The latter enables companies to scale and expand their 3D printing volumes effectively, and requires more than simply investing in 3D printers and materials alone.
With data being the backbone of additive manufacturing, establishing a scalable process ultimately requires the right software infrastructure to provide the necessary level of data analytics, visibility and automation.
Data is at the heart of digital transformation
As seen above, the age of digital transformation has given rise to a number of technologies which have the potential to greatly improve efficiency and drive innovation for manufacturers.
Underpinning each of these technologies is data.
That is because at its core, digital transformation relies on the use of data to optimise processes, connect systems and increase efficiency. Ideally, this data is generated and analysed in real time, facilitating decision-making that is data-driven, as well as operational improvements.
Digital transformation: The integration of digital technologies into existing processes to optimise business and manufacturing operations.
Like other digital technologies, additive manufacturing generates large quantities of data.
Within any additive manufacturing operation, data is being generated at every stage, including:
- Machine data (e.g. technology, time to print, machine status and errors)
- File data (e.g. design changes, file format, material requirements)
- Operator actions (e.g. moving a part to the next stage of production)
- Material usage
The ability to not only collect but also utilise all of this data can help to 1) optimise the production process, 2) better track performance and key KPI’s and 3) expand operations over time.
Embracing digital transformation with additive manufacturing
For companies considering additive manufacturing, the technology offers four clear benefits:
- Faster innovation: In an increasingly competitive and consumer-driven landscape, companies must be able to innovate in order to differentiate. With AM, companies are able to take advantage of the design freedom the technology offers to innovate faster, rethink traditional go-to-market strategies and bring products to market more quickly.
- Design complexity: Additive manufacturing enables complex geometries and designs that would otherwise not be achievable with traditional methods. Enabling design complexity offers a wider scope for more applications, from optimised tooling, jigs and fixtures to innovative new end-part components.
- New business models: Additive manufacturing makes the concept of distributed manufacturing, where products can be produced on demand, close to or at the point of need, a reality. This new business model provides manufacturers and suppliers with greater agility and flexibility, with a new approach to managing supply chains.
- Competitive advantage: The combination of greater innovation, design complexity and new business models means that businesses have more opportunities to increase their competitive advantage.
Adopting 3D printing has become more accessible, with huge improvements in the capabilities of 3D printers and advancements in materials developing rapidly.
However, alongside the benefits of AM, companies must consider the realities of implementing the technology in-house.
What does additive manufacturing need to be scalable?
The ability to scale up your additive operations will become a key priority for companies going forward, particularly as the industry continues its transition towards end-part applications.
- Repeatability: Particularly for 3D-printed end parts and spare parts, ensuring that the same part is produced each and every time, and that quality standards are met consistently, is crucial. Ensuring that the same data, such as part orientation, is sent to the machine each time is therefore incredibly important.
- Traceability: Traceability ensures that each part can be tracked throughout its lifecycle. If a part fails, for example, the root cause will need to be identified. Having a system that allows operators to track the cause of a part failure is a fundamental example of traceability at work. Without the right data to hand, achieving this level of traceability is impossible.
- Connectivity: This includes the ability to connect machines, software systems (e.g. ERP, PLM and MES software) and other systems to ensure a seamless transfer of data at every stage of production.
- Automation: Surprisingly, much of the AM process remains manual, from tasks like production scheduling and build preparation, to post-processing. Automation allows for greater efficiency, thereby allowing operators and engineers to focus on higher-value tasks.
What are the challenges in achieving scalability for additive manufacturing?
Lack of connectivity
One of the biggest hurdles for companies wishing to scale their AM operations is a lack of connectivity, both between their machines and between software systems. This results in a lack of traceability, as key data points may be missed, particularly if a company’s AM activities operate in different locations.
On the machine side, it’s often the case that a company’s network of 3D printers are not connected or even connectable. In some cases, a number of manufacturers do not have open API’s for their machines, making the prospect of connectivity more difficult.
However, steps are being taken to address this, with several machine manufacturers ensuring that their machines can be connected to software. MES/workflow software solutions, like AMFG’s platform, can, therefore, allow companies to achieve a greater level of connectivity between their machines and between their software systems.
Legacy software solutions
Another challenge comes in the form of legacy IT or software systems, which are often not adapted to the unique requirements of additive manufacturing. Using a combination of different software ultimately results in a process that is fragmented and inefficient.
Since additive manufacturing differs extensively from traditional manufacturing methods, it will require a different type of software to manage the process, provide traceability and drive efficiency.
Expensive in-house software solutions
Developing a solution in-house has the benefit of being developed specifically to the needs of a business. However, as we’ve seen, AM generates large volumes of data, which will need to be carefully stored and analysed.
Additionally, any in-house solution must be able to handle each stage of the production process, from managing requests and scheduling production to tracking parts and executing QA checks.
Developing an in-house workflow solution to manage the entirety of the AM production process means sustained maintenance and updates, requiring both extensive financial and human resources, the expenditure for which many companies may not be able to justify.
How can manufacturers use workflow software to scale their additive manufacturing operations?
Due to the multitude of elements within the additive manufacturing process, scaling your operations can only be achieved effectively with the right software infrastructure in place.
A workflow (or MES) software platform consolidates all of the data originating from the different data sources, so that they can be analysed and tracked to optimise operations.
It provides a centralised platform from which all operations can be accessed, providing an additional layer of traceability throughout the process. Using workflow software, manufacturers are able to assess performance and make key data-driven decisions in real time.
To take AMFG as an example, some of the ways this would work includes:
- Calculating the cost per part, both to assess the cost of manufacturing part using AM and to compare this with traditional manufacturing methods,
- Standardising the order management process between departments and suppliers through an internal ordering portal,
- Estimating delivery times based on capabilities and availability,
- Scheduling production automatically, even across locations,
- Accessing live statutes and analytics for individual machines.
Managing these tasks with software allows for efficiency, visibility, greater throughput and, ultimately, scalability.
In today’s manufacturing landscape, embracing change in the form of digital transformation is vital for companies looking to remain competitive, agile and innovative.
Many have already embarked on this path through the adoption of additive manufacturing and other technologies.
However, digital transformation is much easier said than done. When deciding to invest in AM, or any other technology, companies must first develop a robust strategy with clear objectives in mind.
When it comes to additive, investing in workflow software is a vital part of that puzzle. This is not only to introduce a greater level of automation to previously manual processes, but also to be able to improve the quality of the data that is collected and acted upon at every stage of production.
That said, such an investment does not have to be made immediately. Small steps can be taken towards this goal, for example by investigating the possibility of conducting a trial or POC to determine whether a software provider fits your requirements.
Only with the right balance of hardware, materials and software, can companies establish an AM facility that is fully connected and, most importantly, scalable.