In industrial manufacturing, the precision of the scanner of 3d printer and print fit control production efficiency. The EinScan HX (0.04mm precision, $9,800 cost) was utilized by Tesla to scan Model Y doorknobs reverse engineering (±0.05mm tolerance) from the normal 16-day mold-making process down to 3 days, cutting costs by 72% and saving $2.1 million per year in mold cost. According to MarketsandMarkets data in 2023, scanning and printing integrated closed-loop systems have a penetration rate of 39% in the automotive parts market with a median return on investment (ROI) of 1:6.4.
In medical customization, the hardware and software of 3d printer scanner work together to improve treatment accuracy. Align Technology’s iTero Element 5D (0.05 SEC/frame scan speed), and the Formlabs Form 3B printer, reduces the production time of concealed braces from 3 weeks to 4 hours, and reduces patient re-visits by 42%. 2023 revenue increased 31% to $1.32 billion. Shanghai Ninth Hospital used Shining 3D FreeScan UE Pro (accuracy 0.02mm) to scan jaw defects, and the matching rate of 3D printed implants reached a record 99.7%, reducing the operation time by 1.8 hours and saving surgical consumables by 1.8 million yuan a year. According to the FDA, 92 percent of customized orthopedic surgery relies on scanning-print closed-loop procedures, and the median error rate fell to 0.09 percent from 3.2 percent.
In educational innovation, the ease of use of scanner for 3d printer accelerates teaching experiments. STEM school Magic Makers bought 25 Creality CR-Scan LIZards (cost $499, accuracy 0.3mm), and the student project completion rate for scanning palms and printing engineering devices rose from 48% to 91%, and design iteration speed by four times. In 2023, Tsinghua University added the combined usage of Revopoint POP3 (scanning range 0.3-2 meters) and Prusa i3 MK3S+, increasing model preparation efficiency for experiments by 600% (1 hour from 6 hours), and equipment usage was 97%. By HolonIQ, global scanning-printing equipment purchase by schools will grow 35% in 2023, driven by beginner equipment (< $1,000) at 78%.
In the cost-effectiveness aspect, the incorporation of scanner for 3d printer significantly decreased the overall cost. A mold factory in Dongguan used the EinScan SE ($2,500) to access inkjet paper to scan into the Creality K1 Max printer, which reduced the cost of a single reverse engineering product from 300 yuan to 45 yuan, and saved 12.75 million yuan every year by handling 50,000 orders. According to Forrester research, with the use of scanning-print closed-loop approach, 65% reduction in average prototype development cycle and marginal order costs in small lots by 41% are realized. Open source technologies such as OpenScan ($230 of hardware cost) and Ender-3 V3 printers have reduced first-year operational expenditures of makers to 17% of the cost of conventional outsourcing.
Technology innovation continuously optimizes integration efficiency. Artec Eva X3 (precision: 0.05mm, speed: 100 frames/SEC) in 2024 had a real-time data calibration algorithm, which reduces the assembly time of a model when it scans car turbine blades (radius of curvature: 0.8mm) to 5 minutes from 30 minutes, and the error ratio was less than 0.03%. Prusa offers the XL Printer+Artec Micro (micron accuracy) package, reducing the scan-print cycle from 8 hours to 1.5 hours with adaptive slicing technology, which increases the efficiency of generation of intricate structural support by 12 times. In 2023, customers of integrated devices will be able to bring their products to market 3.5 times quicker and double their start-up survival rate by 28%, according to 3D Hubs.
According to market statistics, global shipments of 3d printer scanners will amount to 680,000 units in 2023 (CONTEXT report), of which 37% will be industrial precision (0.01-0.05mm) and 52% will be consumer precision (0.1-0.5mm) devices. Shining 3D, Revopoint and Formlabs provide bundled solutions that support 89% of the leading 3D printer models, with education, healthcare and manufacturing average payback periods of 10 months, 14 months and 8 months, respectively. The Tesla, Johnson & Johnson and Tsinghua University experience proves that multi-material compatible, open apis and high-precision devices have emerged as the go-to tools utilized for scanning and printing ecological optimization.