Artificial Intelligence Controls Automotive 4.0 Inspections

Artificial Intelligence Controls Automotive 4.0 Inspections

Advanced artificial intelligence, data analytics, robotics, and smart manufacturing are digitally transforming all of today’s manufacturing landscape. At this hi-tech stage industries such as automotive, agriculture, aerospace, and customized production are changing in exciting ways, employing superior tools to attain high-resolution measurement scanning to precise robotic laser welding systems. Engineers design applications to drive AI as a data analytic tool to create correlations designed to make predictions based on agile machine-learning algorithms.


Eines Vision Systems – Digital AI in automotive paint operations

Eines Vision Systems – Digital AI in automotive paint operations

The impact of AI is enormous to manufacturing. Only recently has the technology truly caught up with the promises. The bottleneck now is having the processing power and micro-controllers necessary to run complex AI algorithms efficiently and quickly. Whether it’s the measurement of automotive fit n finish, surface integrity, or color this new set of Big-Data can now be held inexpensively in cloud storage so much that computation engines are embedded to run the machine learning analysis.

In modern-day inspections, 3D modeling and computational analysis within an AI/ML intelligent system do the laborious scanning to identify vision camera images with nonconformance issues that flags out of specification data for more attention to downstream automation or repair personnel. For example, AI can measure scratches, dents, pinholes, and orange peel more accurately and consistently than most manual labor processes. One automotive manager commented, “The old way was labor-intensive with highly skilled technicians to achieve subjective results. Vision AI makes the results objective with a higher degree of accuracy.”

One key attribute of using vision AI within automated inspection systems is that it does a great job recognizing patterns and can process thousands of images in milliseconds. Within the Eines Flush n Gap system, the programs look at the results of measured sections more accurately than manual inspections. The digital vision AI programmed inspection systems maintain consistent performance whereby operators become fatigued and bored of examining thousands of dimensional outputs. Powerful data can not only be harnessed for machine learning of part specifications but also simultaneously computes with parallel algorithms for process specifications, performed to accelerate efforts to develop robust root-cause analysis controls leading to alternative improvements in upstream processes.

Poorly training or untrained AI algorithms is one limitation of AI-controlled automation enabled systems, thus resulting in machine learning data processed inaccurately. Impacts on outputs can hamper the ROI case for sophisticated customized-data-driven automation systems. In all new vision system installations, I make it a point to correlate the data with highly skilled programmers and back-test the results to the specifications to ensure the data analytics are robust and cost-effective.

Data analytics can uncover patterns of nonconformance as small as tenths of a millimeter and material degradation in automotive production, beginning with stamped parts through the body shop, paint shop, and final assembly. Wide use of AI in EV assembly is not just for the actual battery builds but also for the battery to carriage assembly. Formal traceability of sequence of operations, part presence, testing measurements, and overall takt time lead to comprehensive big-data accessed by engineers to validate a mistake-proof process. Automated inspection systems vary in price from low thousands of dollar applications to elaborate tens of millions of dollars. It is best to work with an experienced vendor capable of assessing the application and crafting a solution suitable for the needs.

Wide use of AI adoption in automated vision systems has rapidly been employed in hard inspect operations that once were yielding inconsistent and unreliable results. This use decreases labor costs, improves data analytics, and allows the production line to operate continuously without impacting overall operational throughput. Machine Vision detection and measurement are found not only on robotic systems but also in Moving Line Tunnel-Style applications, such as Eines ESFI® Paint Scanner and EIFIS® Gap N Flush Measurement.

Do you have an application needing an assessment or need ROI assistance? Please inquire about this on the contact page of this website to get more information on the prospects of using AI in automated machine vision quality inspection processes or to problem solve by developing an AI program using cutting-edge imaging IoT technology provided by Konica Minolta’s FORXAI®.

Hyperspectral imaging for art restoration

Behind the scenes scanning works of art

Preservation of cultural legacies like paintings, manuscripts, maps, and old photos through documenting and transforming in to digital formats for archives, research, and conservation or for display is increasingly important. Museum laboratories and university researchers are using a wider range of analytical instruments to study collections. There is need to study, materials like pigments, dyes, and binding media not only to observe possible degradation or changes due to age or environmental conditions, but also for to reveal the artist’s painting technique and methods used in creating the work of art.

Hyperspectral imaging (HSI) is gaining wide acceptance as a valuable optical tool for art archiving and restoration. HSI is an optical instrument used to measure the reflectance or transmittance of light by materials and the present the results in the form of spectral curves. HSI’s non-invasive and non-destructive imaging technique is safe for even the most fragile samples. Used remotely to scan all parts of the sample with high spatial resolution (down to 15-µm pixel size). HSI records both spatial and spectral information, for use in classifying chemical, physical and/or biological properties of the object.

In visible range, it gives improved precision in color measurement for recording pigment color-change, which is essential for conservation. In near infrared HSI can reveal information hidden behind the outer layer or written text that has deteriorated and faded under environmental conditions. Besides, fluorescence investigation are prone to highlight different solvent and binders.

Specim provides instrumentation for different spectral regions. Each spectral camera enables the user to emphasize different properties of the sample. Our art scanner can be equipped with VIS, VNIR, NIR or SWIR camera.

Success story: Composition by Henryk Stazewski, 1957, oil
For her doctoral thesis, Agata Warszewska-Kolodziej studied the oil painting “Composition” by the famous Avant-garde Polish painter Henryk Stazewski. An earlier X-ray scan showed that behind the visible painting a sketch or earlier painting existed. When measured using Specim’s spectral scanning instrument for SWIR region the painting revealed far more information on the underlying work. “We were able to exactly determine how the painted over composition looked like” says Agata.


Art analysis goes mobile

Analyzing and conserving art with the help of Specim IQ, the first portable hyperspectral imaging system. Marcello Picollo, Researcher from Nello Carrara, IFAC-CNR shows how it’s done using the Specim IQ.


Advanced Color and appearance control of electrical goods

We surround ourselves with electrical goods. We refer to large household appliances as white goods since, traditionally, most appliances have a white enamel finish. Black goods refer to TVs, cameras, and audio devices. Today, white and black predominance has given way to colorful and more sophisticated finishes. While classic colors like white and black continue to attract the most attention, newer shades created by metallic and stainless steel and chrome are gaining popularity. Combining shades with different textures such as high gloss or matt finishes add a hint of drama to a product’s aesthetic. Learn how to control these colors in our white paper.

Liquid Color Test With Spectrophotometer

Pharmaceutical Liquid Color Testing with a Spectrophotometer

The improvements made over the years to measuring liquid color have elevated visual-based methods to a markedly greater reliability level thanks to today’s advanced color measurement process. Where once an array of physical samples had to be prepared manually with differing levels of dilution and then compared against a set of standards via the human visual system, today’s spectrophotometers take the guesswork–and tedious preparation–out of the equation.

building with bright consistent color

Factors to Consider When Evaluating a Building's Quality

There are several factors to consider when evaluating the quality of a building. Color is one of the first things that a person sees, and mismatched colors can be quickly apparent. If two sides in the building do not match due to different paint batches, or the noticeable repainting of a side or part of the siding to cover a repair, quality becomes quickly suspect. With vinyl siding, even slightly out of specification colors can make a house look like a checkerboard; the seams become obvious everyone wants seamless color in the siding. Roof tiles should match even after replacement due to age or storm damage. The window frames and sashes need to match even if they come from different manufacturing lots. The same applies to glass office towners in the city, the windows must look the same if viewed close up or from a distance, and a slight color difference in a glass panel will be noticeable and degrade the appearance of the building.

The CM-5 spectrophotometer is the ideal instrument for measuring and analyzing color in building materials. The CM-5 can perform a wide range of measurements whether the material is solid, powder, paste, or liquid.

If you are measuring a solid material, place the sample on top of CM-5's measurement aperture, much like putting a sample on a scale to get its weight. If a sample is a grout or stucco in a paste form, use a petri dish. Fill the petri dish with the sample, place it on the measurement aperture, and take a measurement.

In addition, the CM-5 has transmission measurement capability for the measurement of liquid and transparent materials such as glass and films. Place a sample in the transmittance measurement chamber of the instrument to take measurements. Measurements are quick, with just a few seconds to output and save spectral data. For glass and other transparent material analysis, besides color data, the CM-5 provides valuable data such as spectral transparency, absorbance, and haze.

With broad measurement capability for various materials, The CM-5 is the must-have instrument for the color quality of building materials in your lab.

Why Use Machine Learning Vision for Part-In-Motion Quality Inspections

Why Use Machine Learning Vision for Part-In-Motion Quality Inspections

Quality and throughput have always guided manufacturers to invest in new processes and technology. The influx of advanced Industry 4.0 technology offers manufacturing leaders many choices—like 3D printing, artificial intelligence, and machine learning.

Machine Learning (ML) is gaining popularity across various industries and applications, such as automotive, aerospace, medical, and electronics. It exceeds operational needs and provides tangible benefits such as effective instantaneous inspections and traceability.

The design of Eines Vision System's digital software technology is explicitly for part-in-motion quality inspections. Through its advanced machine learning algorithms, Eines can intelligently perform part confirmations, calculations, and simulations of measurements. At the same time, the inspected surface remains moving, like parts that reside on a conveyor line, lifts, automated guided vehicles, and assembly belts.

There are three main types of error-proofing environments to apply advanced machine learning vision quality inspections common to automotive production: stop station scanning, place part-in-fixture scanning, and part-in-motion dynamic scanning measurements. Of the three, part-in-motion dynamic inspection delivers the most benefits, expanding past typical basic visual inspection to dynamic tracking of parts for critical measurements.

In final assembly vehicle manufacturing, there are three preeminent applications using best-practice vision technology for dynamic part-in-motion measurements: gap n flush measurements, surface coatings integrity inspections, and part present validation verifications.
Gap N Flush Measurements (sometimes referred to as fit n finish): gap n flush is the dimensional relationship between mating parts such as doors, trunks, fenders, liftgate, and hoods. Precise measurement is critical for line fitters performing operational alignment to reduce wind noise and improve vehicle aesthetics.

Surface/Coatings Inspections: automotive manufacturers have only seconds to inspect surface conditions for splits, cracks, scratches, dents, dirt, orange peel, fishers, and blisters. Once in the showroom, customers have hours to inspect surface integrity. Surface imperfections can cause future warranty issues; therefore, detection data metrics needs to be instant to perform sanding and polishing before final vehicle acceptance.

Part Present Verification: Commonly known as a Poka-yoke process designed to avoid manufacturing mistakes. Essential to best practices, advanced vision technology can detect missing clips, nuts, emblems, badges, match vehicle style, mirrors, bumper features, or color validation with customer orders.

Providing the line technicians' actionable data analytics generated from quality inspection metrics. The data dashboard consists of defects displayed within multiple digital visual feedback interfaces such as tablet-based, wearable, and fixed monitor-based displays.

gap n flush measurements

Some factories attempt to test and simulate process designs with digital twin models. The digital twin illustrates dynamic simulations of detections, what an operation would look like and how a worker should perform it. It allows for a complete look at processes and traceability to identify specific problems within the operation. It is also deployable on an enterprise level, easily interfacing with common cloud platforms to create custom dashboards and analytics.

Successful manufacturing processes can make every second and every penny count in their operations. Tunnel-style inspection systems harness the production line's speed and rapid data transfer to provide a minimal maintenance high throughput system. This system reduces the risk of downtime while operating very self-sufficient when integrated into existing plant power and communication networks.

For many years, part-in-motion dimensional control inspections have challenged the quality metrics for high production automotive operations. Eines' advanced vision software configured to the customer's specifications deployed through tunnel-style systems solves the problem of accurate error proofing for part-in-motion inspections.

To find out more about dynamic digital inspection systems, please contact our team or request an application assessment.

color formulation software colibri

Using Computer Software for Color Formulation

When creating or designing a new color, manufacturers will need to formulate the color for production. This color formulation process requires trial and error to achieve the ideal close match to the target color. This process, when done manually, could mean repeated efforts until you get satisfactory color.

Computer software for color formulation, such as Colibri®, will save quite a number of trial and error steps and closely match to new color with minimum attempts. The color formulation software saves time of color formulation and saves the cost of waste produced in the formulation process. It will be a significant saving in the process. A formulator needs to create samples of their product ingredients and measure them with the software for material characterization. In the coatings industry, samples are generally drawdowns (letdowns) of the pigments and base material at different concentrations.

At Konica Minolta, our application engineers work with customers to ensure they have the information to create these required samples for material characterization. This step is critical to the formulation process to calculate recipes to match the new color from the ingredients defined in the colorant set. Once developed, you can use the recipe to reproduce the color accurately whenever needed later.

Opacity is crucial to achieving good hiding power for a coating. In Colibri® ColorMatch, you can set a target opacity, and the software will generate recipes with the smallest pigment loading or pigment cost to achieve the hiding requirements. The color and opacity of translucent samples can also be calculated for different substrates, should the coating be designed specifically for a different material than a contrast card.

Colibri ColorMatch® characterizes the binder (base material) separately from other ingredients. Therefore, you only need to create calibration samples for the new binder with white pigment and black pigment to create effective recipes. Calibration samples for the other pigments are not required. This is a great time saving for paints and coatings applications when the resins are identical or similar and using different kinds and or amounts of additives to create other bases or product lines.

With the constant arrival of new paint colors and a wide variety of paint types to manage, paint material also needs to shift to meet the latest environmental requirement as paint-manufacturing technology evolves. An advanced color formulation software can benefit efficiency and stability to paint manufacturers.

The Steps to Consistent Color in Plastics

Expert color duplication at every stage of production is vital to quality control, cost, client satisfaction and retention. As with color measurement of all materials. accurate color control of plastics depends on precision and consistency. This is the process for achieving optimum color control...