Additive manufacturing (AM), also known as 3D printing, is a hot topic. Although the technology was invented in the 1980s, only now is it getting industry traction. In fact, in 2017 Gartner’s famous hype cycle predicted that additive manufacturing is moving past disillusionment and into real product applications. Many predict AM will cause massive industry disruption. Not only for manufacturers but also for everyone involved in the manufacturing supply chain. This includes transportation and logistics companies, retailers, and many others. In a 2017 study by PwC, 74% of participants agreed that companies investing in 3D printing today will have a significant competitive advantage.
There are many reasons for the rapid growth and interest in 3D printing for manufacturers. For example, the actual printing process is getting faster. CAD software providers are providing feature-rich solutions explicitly for this purpose, and there are viable use cases beyond prototyping or home use. But there is one huge obstacle to adoption in the largest, most productive use cases – quality.
A killer 3D printing use case – spare parts
Take the example of spare parts. Most asset-intensive businesses aggressively manage spare parts inventories. This is not only because they tie up capital but also because a failure to have a spare part available in a crisis can derail operations. 3D printing is viewed by many as a game-changing solution to spare parts problems – just print what you need, just in time. In the same PWC study, only 10% of German industrial firms surveyed use additive manufacturing for spare parts currently. However, 85% expect to do so within 5 years.
Under traditional operating models, quality is inherent in the manufacturing of spare parts. But quality of spare parts produced by 3D printing is anything but certain. For spare part 3D printing to be considered reliable, the quality must be:
Proven and repeatable under stable production processes – similar printers, materials, operators, etc.
Consistent across locations and operations, under any conditions
Guaranteed without input from the part’s designer
This isn’t easy for companies whose core business may have nothing to do with manufacturing. Here are 3 risks when an asset-intensive business shifts from spare part procurement and management to manufacturing parts themselves.
Quality of source materials
Process manufacturers understand that quality in equals quality out. Often relationships with materials providers are closely guarded or even contractually protected. Because many 3D printing equipment and solutions vendors have little to no experience with manufacturing, the burden for sourcing materials for additive manufacturing falls on the business producing spare parts with their printers. Unknown quality source materials present a large potential operational risk. This is especially true if the parts are used in mission-critical equipment or have a role in the production of quality-sensitive products such as medical devices, food products, and many others.
Quality in the manufacturing process
Ensuring that a specific manufacturing process produces quality parts is a science. It is a combination of advanced engineering, materials science, and flawless operational execution. For spare parts manufacturers, providing 3D printing solutions with consistent quality standards may be a disruptive model for supply chains and solve many operational challenges. But for spare part users, manufacturing on their own may be constrained – at least for the near future – to a fraction of their spare parts inventory that isn’t mission critical. In a model where parts manufacturers provide a blueprint for companies to print on their own, ensuring quality in the manufacturing process is essentially impossible. Even if 3D printing is consistently producing parts, ensuring quality requires insights from the OEM/blueprint designer. On its own, this isn’t a scalable model.
Every traditional manufacturing process has quality control built into it, that vary from manual inspection to the application of artificial intelligence and machine learning to advanced manufacturing operations. But since 3D printing is a constant, linear process, it tends to lack rigor with quality control (QC). Because the industry is just emerging, there are no clear solutions to QC. One emerging idea is to apply visual inspection to the 3D printing process. This option is fairly cheap if done at scale. It can be done at the printing site– it only relies on software and a high-definition camera. But it does require the parts designer to train the machine learning algorithms.
In the coming years, we will surely see QC solutions come to market designed specifically for additive manufacturing.
Additive manufacturing is shifting from a promising technology to a powerful disruptor, and its gaining momentum with complex ties to many adjacent transformative technology movements such as the ubiquity of the Internet of Things, the industrial use of digital twins, and the public and private investments in Industry 4.0 transformations. IDC forecasts that in 2018, worldwide spending on 3D printing will be nearly $12 Billion. Every manufacturer should think about its additive manufacturing strategy. But at the same time, responsible large-scale adoption must be done with an eye towards quality.
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