Researchers at NOVA College of Lisbon have developed a brand new method to evaluating additive manufacturing (AM) maturity, providing a extra exact method for corporations to evaluate their progress.
Having utilized fuzzy logic, the researchers created a mannequin that captures the nuances of AM adoption, addressing the gaps in conventional maturity fashions that always fail to account for real-world complexities.
Whereas AM has turn out to be a key a part of Trade 4.0, seamlessly integrating it into manufacturing workflows is much from simple. Many organizations discover themselves in a transitional section, the place AM is getting used to some extent however hasn’t but turn out to be a core a part of manufacturing.
Conventional maturity fashions usually categorize corporations too rigidly, making it tough to determine particular areas for enchancment. To handle this limitation, the fuzzy AM maturity mannequin (Fuzzy AMMM) presents a extra versatile evaluation that accounts for human judgment and the uncertainties inherent in technological adoption.
Evaluating AM maturity throughout technique, workforce, and know-how
Printed in Procedia Laptop Science journal, the mannequin evaluates AM maturity throughout three key areas: organizational, cultural, and technological. Organizational maturity seems to be at whether or not AM is built-in into an organization’s technique, how dedicated management is, and the extent of funding in AM tasks.
Cultural maturity assesses workforce readiness, worker expertise, and openness to AM adoption, whereas technological maturity focuses on how properly AM is carried out in manufacturing processes, together with CAD software program use and half manufacturing.
To place the mannequin to the check, the researchers carried out a case research at an undisclosed automotive provider that has been utilizing AM for 5 to 10 years.
The evaluation concerned a mix of surveys and interviews with firm representatives, together with an operations supervisor with experience in mechanical engineering. Outcomes indicated an general AM maturity degree of three, putting the corporate at an intermediate stage the place AM is in use however has but to considerably affect manufacturing.
A better have a look at the scores revealed a robust efficiency in organizational and technological maturity, each rating at 4.68, suggesting that the corporate has built-in AM into its technique and manufacturing workflow. Nonetheless, cultural maturity lagged at 3.00, pointing to a niche in workforce coaching.
Workers confirmed proficiency in CAD software program, design for additive manufacturing (DFAM), and slicing software program, however there was a noticeable lack of personnel with management expertise to supervise AM operations. Moreover, whereas some exterior coaching initiatives exist, there isn’t any structured inner competency growth program, limiting long-term progress.
One of many research’s key findings was a disconnect between management’s dedication to AM and worker readiness. The corporate had made substantial monetary investments and tailored its processes, however with out devoted AM specialists and structured coaching packages, it confronted challenges in maximizing AM’s potential.
This underscores a broader problem seen throughout industries, having the best know-how in place is barely a part of the equation. With out the required expertise and experience amongst staff, full integration stays out of attain.
By making use of fuzzy logic, the researchers have been capable of seize a extra correct and reasonable image of AM maturity in comparison with typical fashions, which are likely to oversimplify the evaluation course of. In line with the researchers, the Fuzzy AMMM not solely helps organizations decide the place they stand but additionally highlights the precise areas that want enchancment.
Future analysis goals to increase the mannequin’s utility throughout a number of industries, refining its framework to help organizations as they navigate their AM journey. With clearer insights, companies could make extra knowledgeable selections, making certain that AM integration turns into not only a technical improve, however a strategic benefit.
Novel approaches to assessing AM maturity
Including to this yr’s knowledgeable predictions, Paul Gradl, Principal Engineer at NASA Marshall Area Flight Heart, acknowledged that creating an AM maturity mannequin might assist standardize processes and refine materials properties, contributing to the way forward for 3D printing.
At Formnext 2023, business gamers together with Siemens, DyeMansion, Ahead AM, EOS, and HP launched the Additive Manufacturing Industrialization Navigator (AM I Navigator) initiative. Designed to handle industrial 3D printing challenges, the initiative outlines a structured maturity mannequin to assist corporations combine AM into conventional workflows.
By means of this instrument, corporations can consider their AM maturity by a Maturity Verify, primarily based on Siemens’ Digital Manufacturing Excellence framework, to determine gaps and obtain suggestions for enchancment. The aim is to help a transition from handbook to completely autonomous AM manufacturing whereas optimizing course of coordination.
Whereas structured maturity fashions present a roadmap for AM adoption, some corporations take a extra direct method by specializing in high quality assurance. Components sourcing AM platform MakerVerse and ZEISS showcased a spread of dimensional, floor, and materials property evaluation options, enabling corporations to systematically consider the reliability of their AM elements.
By means of Optical 3D Scanning, Tactile CMM, Floor Roughness measurements, and Industrial CT/X-ray inspections, this platform presents a data-driven method to AM maturity, making certain that printed elements meet certification requirements and are appropriate for full-scale manufacturing.
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Featured picture reveals the Fuzzy AMMM growth methodology. Picture by way of NOVA College of Lisbon.
