What is slowing down additive manufacturing growth in industry?

Additive Manufacturing (AM) is an exciting and promising technology providing new opportunities concerning product design or the individualization of products to match various consumer needs. Thus, it enhances product differentiation without the need for retooling or assembly. It provides an unprecedented flexibility in production with often incurring less effort than traditional manufacturing technologies. Nevertheless, its adoption for the manufacturing of parts or products is still sluggish.

According to Gartner 63% of enterprise AM users deploy the technology for prototyping only while 21% use it for production, mainly for parts that otherwise could not be manufactured.

The industrialization of AM lags behind expectations. If decreasing product lifecycles or saturated markets implying product innovation are factors supporting the growth, why is the adoption rate of AM in manufacturing still so low?

The industrialization of AM lags behind expectations. Why is the adoption rate in manufacturing still so low?

Obstacles to the widespread adoption of AM

What obstacles are in AM`s way? The answer to this question is not trivial given the fact that obstacles exist in many different domains. AM is still a young technology, when compared to traditional manufacturing technologies such as drilling or milling. This has an impact on assuring a constant product quality since generally accepted norms and standards are only slowly evolving. Other major challenges for the adoption of AM include product costs, personnel skill requirements, material constraints or the AM ecosystem itself:

  1. The cost especially of AM manufactured metal parts are higher compared to conventionally manufactured parts. This is caused by slow production speeds of 3D printers, high material cost and the need for manual post-processing of the parts in the aftermath of the printing process which requires manual work and skilled operators
  2. Material is still a bottleneck in the adoption of AM. Materials used are more costly than those used in traditional manufacturing. Furthermore, mass adoption will require the use of multiple materials, a capability, which is slowly evolving in AM
  3. Enterprises are still locked up in their traditional ways of R&D and production which is complicating the move from AM based prototyping to AM industrialization. In addition, the education of designers and engineers is not sufficient to meet the requirements of AM. AM is new technology that requires training on part selection, designing and manufacturing for AM
  4. Material chemistry, the lack of advanced process control in 3D printers and of standardized test methods and tools are causing the problem of quality variations in parts. Solutions that can assure quality in 3D printing and especially metal printing will become crucial for the widespread adoption of 3D printed parts e.g., in the aerospace industry
  5. Finally, there is a lack of software integration from design to post processing. We see siloed or inadequate solutions for the design of parts (CAD systems not suited for the design of AM parts), very little use of platforms to manage the AM eco-system including customers and third-party printing service providers

These barriers to AM mass adoption are responsible for the fact that according to USP (2020) only 0.4% of the global manufacturing market is represented by AM today. Researchers such as the Statista Research Department in the US expect the large-scale production of AM manufactured parts by only 2030. Thus, the question remains, what needs to be done to abolish the barriers to AM growth?

AM-oriented workflows and standards are the solution

Manufacturing companies will have to change their mindset towards AM. They need to get rid of applying product designs and workflows adequate for traditional manufacturing to AM. This process needs to start with an AM-oriented curriculum for engineers at university. AM is an area for generalists that take an overarching view and can combine different disciplines such as mechanical, fluid and material engineering. Operators in manufacturing plants also need to be trained to better understand the capabilities and characteristics of 3D printers. This will pave the way for better products with new features and less manufacturing or assembly effort needed.

An important field will be the automation and integration of the complete AM end-to-end process. CAD systems that are suitable to create AM related designs and that are integrated with platforms that manage the AM eco-system such as the Atos Additive Manufacturing Platform.

Furthermore, the quality of produced parts needs to be assured by monitoring the printing process. Solutions like the Atos Predictive Monitoring System help to predict porosity in metal parts and detect anomalies during the printing process enabling operators to take counteractions to assure quality and ease part certification.

Apart from that, the industry needs globally accepted standards regarding AM to enter into predictable investments. Organizations like ISO and ASTM International have started creating AM standards for some years now but will need to continue to do so. Printer manufacturers will also need to come to common connectivity standards for the integration of their printers with AM platforms and other control solutions. New printers will accelerate production speeds by employing multiple lasers instead of one to apply simultaneously 20 or 30 layers instead of one.

Finally, material manufacturers and their customers need to partner to create quality materials that will improve part quality, reduce post processing and material cost to the level of those for traditional manufacturing.

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About Stefan Zimmermann
Global Head of Incubator Portfolio Industry Manufacturing
Stefan Zimmermann is responsible for the innovation and portfolio development in Industry 4.0 at Global Atos B&PS. He aims at helping industrial companies to identify business opportunities enabled by Industry 4.0 during their digital transformation process, embracing the Industry 4.0 framework. He’s got a very strong industrial background, having worked for companies like Siemens (>10 years) and Rheinmetall Group and also comprehensive consulting skills gained when working for Roland Berger & Partner.

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