🚀 Shaping the Future - Issue 58
In 2024, a joint survey by RAeS and Protolabs revisited the aerospace manufacturing landscape, revealing significant shifts and concerns within the industry.
🚨 Advancing Digital Transformation
The Manufacturing X.0 agenda has practical, tried, and tested, examples of digital transformation MX.0 Midwest showcases regional and national manufacturing excellence in building for manufacturers of different sizes, at different points in their implementation journey.
📚What we’ve read this week
Aerospace Manufacturing in 2024 [Protolabs]
In 2024, a joint survey by RAeS and Protolabs revisited the aerospace manufacturing landscape, revealing significant shifts and concerns within the industry. Some key highlights from the survey include:
Technologically, 3D printing dominated (74.09%), surpassing CNC machining and robotic manufacturing. This shift suggests 3D printing's integration into mainstream aerospace manufacturing beyond rapid prototyping.
The survey also noted a decline in in-house manufacturing (29.59% producing 25-50%), indicating a trend towards outsourcing initial production runs to focus on R&D. Concerns over project costs and lack of expertise remained high, reflecting challenges in adopting digital manufacturing.
Quality emerged as the paramount factor (94.22%) in parts design and manufacturing, up from 64% in 2023, underscoring heightened industry scrutiny post-scandals and safety issues.
Certification's importance soared, with 76.12% rating it 'very important' in 2024, emphasizing enhanced regulatory focus. Future industry focus shifted towards new technologies (63.36%), aligning with sustainability goals through efficiency and innovation.
AI's role in advanced manufacturing and digital design garnered optimism, with 48.65% considering it 'important' and 32.61% 'very important', highlighting expectations for AI-driven advancements in aerospace.
Shaking Up the Factory Floor with Digital and AI [BCG]
A BCG global survey of almost 1,800 manufacturing executives across seven industries found that 89% of companies plan to implement AI in their production networks, and 68% have already started implementing AI solutions. Yet only 16% of companies have achieved their AI-related targets. To successfully integrate digital and AI technologies at scale, manufacturers must prioritize people and processes alongside technology and algorithms. Lean principles serve as a foundational framework, enhancing productivity, quality, and engagement. However, traditional lean methods face challenges with the complexity of modern equipment and evolving workforce expectations. A strategic approach involves developing a clear vision of the future factory and integrating standardized processes into a cohesive technology stack. Successfully scaling these initiatives requires addressing challenges such as change resistance and digital literacy gaps. Emphasizing a human-centric transformation approach—allocating 70% effort to people and process transformation, 20% to data infrastructure, and 10% to algorithms—facilitates smoother integration.
Digital Twins Help Scientists Run The World’s Most Complex Experiments [MIT Tech Review]
In January 2022, NASA's James Webb Space Telescope (JWST), a $10 billion project, faced a critical phase as it neared its orbital destination one million miles from Earth. Its deployment required intricate maneuvers, including unfolding a tennis-court-sized sun shield and assembling an 18-piece hexagonal mirror, crucial for its observation capabilities. Engineers from Raytheon, responsible for the telescope's software and flight operations, monitored these operations remotely using a "digital twin." The digital twin, tracking 800 million data points daily, enabled engineers to simulate and monitor JWST's actions, predict outcomes of software updates, and train operators. Beyond JWST, digital twins are transforming scientific instruments like the Curiosity rover and aiding projects at facilities like CERN and the Gran Telescopio Canarias. These models, integrating IoT, AI, and cloud computing, enhance operational efficiency and predictive capabilities across diverse applications. As digital twins become ubiquitous, their role in optimizing complex systems and advancing scientific understanding continues to expand, bridging the gap between industry innovation and scientific discovery.
The Solar Breakthrough That Could Help the U.S. Compete With China [WSJ]
An Israeli startup, Lumet, has developed a new technology set to revolutionize solar panel manufacturing. Founded by Benny Landa, Lumet aims to simplify the metallization step in solar panel production, cutting down the amount of silver required to capture sunlight. South Korea's Hanwha Group, through its Qcells unit, plans to be the first to adopt Lumet's technology, contributing to its multibillion-dollar solar supply chain in Georgia. Lumet's technology offers thinner and more efficient silver fingers, crucial for cost reduction as silver prices surge. The process involves coating plastic films with silver paste, which is then transferred to solar cells, eliminating the need for bulky equipment and streamlining production. While Qcells has been testing Lumet's technology for nine months, specifics regarding deployment timelines and cost reductions remain undisclosed. Nevertheless, Qcells' Georgia supply-chain project is progressing, with module assembly already underway and further production stages expected to commence soon.
The Economics of Additive Manufacturing are Broken [TCT Opinion]
The Op-Ed discusses the challenges facing industrial 3D printing (additive manufacturing or AM) and proposes solutions to unlock its potential for widespread adoption. Currently, industrial 3D printing remains limited to boutique manufacturing and prototyping, lacking urgency due to the minimal incentive to invest in it and the complexity of designing for AM. Two main challenges hinder its advancement: the lack of understanding among engineers on how to design for AM and the prohibitive production costs despite designing for it. Despite the inherent flexibility of AM, it is currently one of the most expensive manufacturing processes due to high production costs and expensive consumables, which perpetuates a self-perpetuating cycle of high costs and limited market adoption. To address these challenges, industrial 3D printer companies should invest in automating their manufacturing processes to reduce costs and increase production efficiency, and AM should be integrated into more industrial workflows to drive down costs and enable broader adoption. Service providers could adopt pricing models based on machine utilization to make AM more economically viable for end-use parts. China's example of offering lower costs and more competitive pricing with industrial 3D printers drives faster adoption within China, highlighting the need for strategic investments in AM infrastructure and automation to unlock its potential for widespread impact on global manufacturing.
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