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Dec. 15, 2021 – Supply chain disruptions, chip shortages and the rising cost of raw materials continue to bedevil the machine vision industry. System integrators are confronted with an experience once rare: no stock available at distributors, and no idea when cameras, frame grabbers, computers and other necessary accessories will come in.
 
Bucking this trend is BitFlow, Inc., a global manufacturer of CoaXPress and Camera Link frame grabbers headquartered outside Boston. At the onset of the pandemic, the company’s management began to take steps to mitigate the impact of shortages on production. BitFlow’s close relationships with its trusted suppliers and partners of over 25 years enabled it to build in-house stock when shortages started becoming apparent. For example, Altera FPGAs (Field Programmable Gate Array) are key components of its cards. An FPGA is an integrated circuit with modifiable logic and memory blocks configurable in the field that help BitFlow customers reduce cost and improve design cycle times. To ensure a steady supply of FPGAs, BitFlow met with Altera to establish forecasting and lead times, ultimately resulting in purchasing additional stock.
 
Donal Waide, director of sales for BitFlow, notes that the company is experiencing stronger than expected demand yet has continued to reliably deliver its industry-leading products. “In the short term, lead times may, in some cases, be longer than we would like. For the most part, however, we have boards on hand and are able to go into new projects, whereas many of our competitors are struggling to meet their production goals.”
 
Although there are no silver bullets, Waide points to several steps BitFlow took to stay ahead of supply chain disruptions:

• ​Source alternative suppliers, and review your existing suppliers for common components.
• Increase collaboration and visibility with suppliers to determine their technology roadmaps so you can evolve product designs accordingly. Suppliers may drop the mature, less-profitable components used in your legacy products in favor of newer technologies with higher margins.
• When reviewing suppliers, consider their global footprint and their ability to mitigate disruptions in one region with manufacturing capabilities in another.
• Remember that during shortages, suppliers determine who to support, not the other way around, underscoring the importance of strong relationships.
• If possible, move away from single-sourced parts. 

Ironically, strained global supply chains have led to heightened demand for machine vision systems as manufacturers struggle to maximize yield from scarce components. Manufacturers are turning to machine vision to track goods throughout the production process with quality control measures that minimize waste and ensure compliance with customer and regulatory standards. In addition, with both parts and labor in short supply, plant maintenance is another area where machine vision is adding value, in particular when combined with AI. Cameras can be used to identify vibration issues before a failure occurs, for instance, or to detect wear on conveyor belts or leakage in remote pipes. Monitoring can be performed without service personnel shutting down a production line, and opening cabinets or enclosures to check mechanical parts for wear. Keeping lines running yields an immediate production increase.

WOBURN, MA, SEPTEMBER 21, 2021 — Smoltification is a complex series of physiological changes that allow young Atlantic salmon to adapt from living in fresh water to living in seawater. In salmon farming, this transition from “parr” to “smolt” is controlled using lights or functional feed to ensure a continuous and predictable supply of fish to grocery stores, restaurants and other seafood markets.

Scientists at SINTEF, one of Europe’s largest independent research institutes located in Trondheim, Norway, recently developed a hyperspectral imaging (HSI) system¹ to study the vital aspects in detecting smoltification, relying in part upon a BitFlow Camera Link frame grabber to grab high-speed video frames for analysis at more than 100 frames-per-second.

The ability to verify smoltification is critical since incomplete seawater adaptation may result in poor animal welfare and increased mortality. Animal welfare is of increasing importance in salmon farming, as the industry is under pressure to improve production and farming operations due to ethical concerns. Conventional smoltification assessments measure chloride content in blood samples after exposing fish to saline water, or by detecting the presence of ion-transporting enzymes through analysis of tissue samples from gills. These methods are time-consuming so only a few salmon are typically tested from populations of several hundreds of thousands of fish.

To evaluate the robustness of its HSI approach, SINTEF placed emphasis on collecting diverse data with variations in fish color, patterning, size, and shape using three different salmon farming sites. Data were collected weekly in synchronization with the sites’ respective production and testing schedules. A Shuttle SH110G computer with Intel i7 processor had the BitFlow frame grabber installed to grab frames from a Specim® FX10 hyperspectral camera (Figure 1) equipped with a 23 mm/f.2.4 (OLE23) lens. Exposure settings were regularly adjusted depending on local conditions and the state of the fish. And because smolt transition involves salmon becoming more reflective, shutter speed was adjusted to keep the exposure within the sensor’s dynamic range. To make all data sets comparable, despite differences in ambient lighting conditions and exposure settings, all were normalized for comparison using white and dark reference images.

The raw data obtained from HSI were multidimensional images of individual fish, including their background. Each layer of this multidimensional image represented a single gray-scale image corresponding to the intensity of the reflectance measurement at a specific wavelength. When stacked, all the layers and reflectance measurements represented a 3D cube (Figure 2). A step-wise procedure was used to process and analyze the data so the low-dimensional spectral characteristics could be observed, and classification of parr or smolt made possible. Wavelengths were optimized by factoring in water temperature, dissolved oxygen, water opacity, and color, as well as lighting and feeding regimes.

Upon conclusion of its study, SINTEF demonstrated a HSI system where only three wavelengths are needed to identify smoltification status of Atlantic salmon, and that this system could serve either as a supplementary or free-standing verification tool in fish production. In doing so, the researchers also laid a pathway to manufacturing low-cost HSI instruments for use in production tanks or integrated in existing sorting and vaccination systems for faster, wider and more cost-effective population sampling of Atlantic salmon.

WOBURN, MA, SEPTEMBER 15, 2021 — BitFlow, a leading innovator in frame grabbers for industrial and commercial imaging applications, today announced details of its in-person participation in VISION, the world’s leading trade fair for machine vision, to be held in Stuttgart, Germany, October 5 to 7, 2021. BitFlow encourages VISION attendees to visit booth #10H46 to engage with its trained engineers and see firsthand its newest CoaXPress and Camera Link frame grabbers.

Because VISION could not be held last year due to the pandemic, its relaunch is a positive signal to the international machine vision market. More than 250 companies will take part in VISION, providing visitors with a current overview of the wide range of machine vision products, software and services now available, together with global insights into future technologies.

“Coronavirus halted VISION and other industry events in 2020, making us all acutely aware of the value of face-to-face, in-person business meetings,” said Donal Waide, Director of Sales, BitFlow, Inc. “Keeping connected and moving forward with events like VISION is critically important for economic recovery. We are very excited to get back on the road to meet with our customers, colleagues and distribution partners.”

BitFlow will showcase at VISION its entire portfolio designed to meet the most demanding imaging needs within diverse industries such as machine vision, quality control, defense, medical research and robotics. In addition, BitFlow will join with several of its camera partners to present live demonstrations of its high-speed frame grabbers, including the new line of fan-cooled Cyton CXP4-V CoaXPress models engineered for use with small form-factor fanless computers, like the NVIDIA® Jetson Xavier Developer Kit.

WOBURN, MA, JULY 16, 2021 — Research scientists with the Energy Materials Telecommunications Center, National Institute for Scientific Research in Quebec, Canada, have developed a groundbreaking technique to acquire 3D images at over 1000 frames per second with resolution as high as 1180 x 860 — far beyond the capabilities of available systems today — by eliminating information redundancy in data acquisition. Certain to open new opportunities for 3D applications, the dual-view band-limited illumination profilometry (BLIP) with temporally interlaced acquisition (TIA) system or simply BLIP-TIA, relies upon the BitFlow Cyton-CXP CoaXPress frame grabber to transmit images from two CMOS cameras to a computer for processing at rates surpassing 12.5 Gb/S.

Existing 3D systems based on the widely used technique of Fringe Projection Profilometry (FPP) have two main limitations. First, each camera captures the full sequence of fringe patterns, therefore imposing redundancy in data acquisition that ultimately clamps the systems’ imaging speeds. Second, the cameras are placed on different sides of a projector. This arrangement often induces a large intensity difference from the directional scattering light and the shadow effect from the occlusion by local surface features, both of which reduce the reconstruction accuracy.

To overcome these limitations, the scientists developed BLIP-TIA with a new algorithm for coordinate-based 3D point matching from different views. Implemented with two cameras from Optronis placed side-by-side and the BitFlow Cyton-CXP frame grabber, it allows each camera to capture half of the sequence of the phase-shifted patterns, reducing the individual camera’s data transfer load by 50%, and freeing up capacity to transfer data from more pixels on each camera’s sensor or to support higher frame rates.

Besides its high-speed data transfer, the Cyton-CXP two-channel frame grabber incorporates the Gen 2.0 x8 PCI Express bus interface on its back-end for high speed access to host memory in multi-camera systems such as the BLIP-TIA. It also allows control commands, triggers and power to be sent to and from cameras over the same coaxial cable to simplify overall design.

To verify high-speed 3D surface profilometry, the researchers used BLIP-TIA in a number of tests including recording non-repeatable 3D dynamics by imaging the process of glass breaking while being struck by a hammer. The growth of cracks and the burst of fragments with different shapes and sizes were clearly shown in the reconstructed 3D images.

Besides technical improvements, researchers are now exploring new applications for BLIP-TIA. For example, it could be integrated into structure illumination microscopy, frequency-resolved multidimensional imaging, dynamic characterization of glass in its interaction with the external forces, recognizing hand gestures for human–computer interaction, in robotics for object tracking and reaction guidance, vibration monitoring in rotating machinery, and for behavior quantification in biological science.

BitFlow will be exhibiting at Vision 2018 in Stuttgart, Germany from November 6th through the 8th.  Come see us in Hall 1 at Booth# A06 to see our latest offerings!