Bright Machines was founded in the year 2018 with a motive of utilizing the opportunity to revamp manufacturing by picking software-first approach to create products. Industrial machines get eyes, brains, and can feel the touch by adapting software, machine learning, and computer vision to factories.
The company is headquartered in San Francisco with R&D centers in the US and Israel, and field operations in US, Mexico, China, and Poland, today its team supports a wide range of manufacturers with innovation, passion, and expertise.
Bright Machines is a technology firm which builds digital infrastructure for present day manufacturing. The organization changes the scalability, resiliency, and economics of the industry by utilizing computer vision, machine learning, simulation, and adaptive robotics to the factory floor.
Today the company is completely focused on the back end of production including assembly, testing, and inspection. But its ambition is to apply data and algorithms to a broader range of factory operations, making them smarter over time. Partnering with industry pioneers, it’s excited to advance digital manufacturing and helps accelerate the development of intelligent factories.
Why use Microfactories?
A combination of intelligent software & adaptive hardware, Bright Machines Microfactories automate repetitive assembly & inspection tasks. With predictable output, you’ll increase capacity and improve OEE. Microfactories are ideal for implementing assembly and inspection to get your products to market faster.
Case studies to prove the efficiency
A manufacturer of electronics for a global telecommunications company faced challenges scaling production due to the labor-intensive process involved with the assembly of radio frequency filters. The company selected Bright Machines’ smart automation solution to boost productivity and scale production.
A manufacturing line in Europe that produces electronics for a leading global telecommunication company was facing productivity issues in the assembly and inspection of the company’s radio frequency filters. The assembly process, including tuning, screwing, soldering and dispensing, was manual and labor-intensive, relying on up to 28 human operators per day to produce a filter. Additionally, many of the tasks were difficult for human hands to complete accurately and quickly.
In this mode, scaling production was challenging. The company needed a way to improve the productivity line rate and take more control over their manufacturing processes.
The company implemented a Bright Machines Microfactory with Bright Robotic Cells to automate and manage tedious assembly processes, including screwing, labeling, glue dispensing and more.
Depending on the filter design, assembly operations can typically be done only once and if done improperly, the entire unit must be scrapped. Leveraging computer vision, the Bright Machines solution ensured accuracy of placement and dispensing as well as visual verification after each operation, therefore preventing costly scrap.
Through data collection, increased process control repeatability, ensuring radio frequency filters assembled correctly for higher yield. By introducing automation to these heavily manual processes, the company removed the need for human operators and implemented a more viable and effective solution to boost the production of electronics products.
A North American manufacturing line produces critical and complex electronic assemblies for a major automotive manufacturer, but the line was highly manual and labor intensive, and required dozens of human touch points. The company selected Bright Machines Microfactories to speed up production and improve product quality.
A major automotive company relies on a North American EMS assembly and inspection line for their infotainment electronics consoles – vehicle systems that enable radio, navigation, telematics, multimedia and internet-based applications to be centrally controlled. Prior to Bright Machines, the line relied on manual labor and had 58 touch points that made it challenging to maintain continuity. That much human interaction meant that outcomes were largely dependent on the expertise and ability of the operator on-shift, which can decline as the shift goes on and operators become fatigued. The emphasis on manual labor limited units produced per hour and had little ability to monitor performance in real time, ensure consistent quality, and identify and resolve any issues on the line and adjust quickly.
With labor costs, quality, traceability of materials and processes important metrics of their success, this business realized they needed to rethink their automation strategy. Turning to Bright Machines, the manufacturer replaced a manual assembly process with an automated, software-defined Bright Machines Microfactory to produce infotainment electronics consoles faster, with better yield and reduced defect rates. Their solution involves three Bright Robotics Cells performing pick and place, screwing processes, as well as final label application.
The Bright Machines Microfactory allows the line to maintain the same rate of production hour by hour, without having to rely on the consistency of a human operator working a long shift. It also meant that the manufacturer eliminated the need to train operators to perform specific tasks, thus minimizing expertise required for employees on the line while still meeting the extremely high-quality demands of the end customer.
With the deployment of their microfactory, this automotive manufacturer was able to dramatically increase yield and quality while reducing headcount and defect rates.
And these results are only representative of their North American manufacturing line. Because the Bright Machines Microfactory is so easily scaled, it has since implemented additional lines for this same customer, reusing the same solution in other geographies.
Amar Hanspal, CEO and Co-Founder
Amar is a senior business leader with 30+ years of experience driving business and technology transformation. Prior to joining Bright Machines in 2018, he was at Autodesk, where he drove the transformation of the design software leader’s product portfolio from on-premise to SaaS and its business model from one based on perpetual licenses to subscription. He led Autodesk into the cloud and enabled the company’s 12 million customers to access their designs on nearly any device. As Autodesk’s co-CEO and chief product officer, Amar oversaw the company’s entire software portfolio, including its innovative manufacturing and construction applications.
In addition to sitting on Bright Machine’s board, Amar also sits on the boards of eSilicon Corporation and Aspen Technology, and advises early stage venture companies. He holds a bachelor’s degree in mechanical engineering from Bombay University and a master’s in mechanical engineering from State University New York, and he has completed the executive managerial program at Stanford University.