Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on solutions for the manufacturing sector. As there are a lot of such startups working on various different applications, we want to share our insights with you. Today, we take a look at 5 promising computer-aided manufacturing startups.
Heat Map: 5 Top Computer-Aided Manufacturing Startups
For our 5 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 486 relevant solutions. Depending on your specific needs, your top picks might look entirely different.
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Sienci Labs – Affordable Computer Numerical Control Routing
Computer Numerical Control (CNC) routers are computer-aided cutting machines that minimize errors and wastage of raw materials. They make precise and repeated cuts on a wide variety of materials, including wood, plastics, soft metal, foams, and waxes. However, CNC routers are prohibitively expensive, which poses a challenge for new startups working in the area.
Canadian startup Science Labs produces a low-cost desktop milling machine. Their benchtop CNC, LongMill, features an aluminum router mount, high power NEMA 23 motors, and a Steel Z-axis motor mount plate, combined with multi-platform CAM software. It is more affordable than conventional options and brings the power of industrial CNC routing to artisans, artists, and educators.
Additive Care – Anatomically Accurate Manufacturing
Most applications of computer-aided manufacturing (CAM) in healthcare benefit from additive manufacturing. Through this technology, we can create customized implants, dental restorations, scaffolds for tissue engineering, and anatomically accurate models of organs. These model organs mirror the patient’s actual organs and facilitate personalized healthcare.
The US-based startup Additive Care develops rapid manufacturing solutions for the healthcare industry. The startup combines machine learning and 3D printing to create patient-specific organ models. These models provide with surgeons far better insights as compared to medical scan images, and, additionally, improve pre-operative planning.
Cloud NC – Automated Machining
Computer numerical control systems manage industrial machines according to specific instructions in computer-aided manufacturing. They provide greater consistency than manually operated machines and need fewer machinists to operate. However, CNC systems require complex code programming and need a few hours to a few days to reprogram.
CloudNC is a UK-based startup that develops a software solution to automate machining tasks. It uses artificial intelligence (AI) to determine the optimal fixturing, toolpath strategies, cutting parameters, and other variables for each component. The solution also identifies and analyzes millions of possible machining strategies to discover the most effective one, without loss of precision or accuracy.
Entekra – Off-Site Manufacturing
The construction industry makes extensive use of design software in computer-aided design (CAD), computer-aided manufacturing, and computer-aided engineering (CAE). However, on-site variables such as weather conditions often cause deviations from the plan. Moving the manufacturing process to a controlled off-site environment addresses this issue.
Entekra is a US-based startup that offers a fully-integrated off-site solution (FIOSS) for the construction industry. Their platform takes detailed CAD files and turns them into a fully-automated manufacturing program. Thereby it produces wall panels, floor panels, and roof trusses that are easily assembled on-site into a structural shell.
Pixel – Quality Inspection
Conventional inspection systems usually utilize fixed algorithms to detect defects in manufactured products. Therefore, they do not account for novel defects. Machine learning-based solutions learn from experience and detect new anomalies without the need to reprogram them. They also allow startups to integrate quality inspection with CAM in computer-aided quality control (CAQC).
Pixel is a South Korean startup that develops solutions to automate the inspection process in computer-aided manufacturing. Their deep learning solutions enhance both the speed and accuracy of inspections. The startup also eliminates the need for a human operator to verify false alarms.
What About The Other 481 Solutions?
While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 computer-aided manufacturing startups showcased above are promising examples out of 486 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.
