Category: Clear Intelligence

By employing a visual inspection system for quality check of its products, a food company not only reduces the losses, but also substantially decreases the chance of a quality-related scandal.

The following contains excerpts from FoodQualitySafety.com on Making the Case for Automated Visual Inspection 

What is Automated Visual Inspection?

An AVI system usually consists of image-capturing equipment and image-analysis software. AVI is based on the technology that is called machine vision because it allows machines to “see” and analyze real-world objects. An AVI system always includes a lighting source, a camera or another sensor (depending on the spectral range), and a processing unit. The software part is a set of image analysis algorithms that sift an image in order to detect any defects or deviations in the product’s appearance.

It is worth noting that all this happens within seconds or even fractions of a second. This processing speed is one of the major reasons why AVI is considered more efficient than any manual inspection technique. Other reasons include the properties of software—it’s tireless, consistent, unbiased, and accurate. Besides that, the “visible spectrum” of machine vision is five times broader than that of a human and includes infrared, X-ray, and UV ranges.

We have found use cases for Visual Inspection and quality assurance across many manufacturing and distribution industries. This particular article calls out specific uses for the food industry.

A Real-world Example

On April 17, 2017, a family from Virginia found an unappetizing item in their bagged ready-to-eat salad. On the bottom of a plastic bag, they discovered a chopped-up corpse of a mouse stacked between savoy cabbage leaves and carrot slices. Shocked and outraged, the family sued both the food company responsible for rodent-contaminated salad production and the retailer distributing this product.

This is only one albeit a very impressive example of what can happen if food contaminants haven’t been detected and eliminated timely. According to the statistics, microbiological and physical contamination together are responsible for 54 percent of recalls in the food industry. And, while a recall is somewhat better than a lawsuit, it still causes losses, so it is essential to detect and discard contaminated products as early as possible.

What can food companies do to detect foreign objects in their products at different production stages? One of the most reliable options is automated visual inspection (AVI) of food.

In the Food Industry

AVI is used in many industries, and the simpler and more standardized an inspected object is, the more inspection accuracy can be achieved. In the food industry, it assures that the product meets certain quality criteria: size, shape, freshness (in some cases), absence of surface defects, and, of course, absence of foreign objects. Besides simple quality assurance (pass/fail test), an AVI system can grade the products and sort them into several classes depending on their quality.

Looking for Foreign Objects

Depending on the inspected product, physical food contaminants can be detected either by optical inspection (in the visible light) or by X-ray examination. Optical inspection detects foreign objects among fruits, vegetables, berries, nuts, and grains. It can also estimate fecal contamination of poultry and thus indirectly assess its microbiological contamination. X-ray examination is used to detect foreign objects in packaged products, for example, parasites in fruits and vegetables, bone fragments left behind in the de-boning process in poultry, etc.

In the dead mouse case described above, an AVI system could have detected foreign parts among the leaves and vegetables before they were packed. Alternatively, an X-ray-based system could have inspected already sealed plastic bags, although at this stage the scrap cost would be higher. Nevertheless, a fully automated food production process would have benefited from equally automated quality inspection.

Properly Manage Your Data

Data growth is rapidly increasing, even as budgets are either static or decreasing. The combination of expansive data and constrictive budgets presents a hefty challenge to businesses and IT leaders. In order to avoid unnecessary and emergency storage purchases, it’s essential that IT leaders know their key storage data metrics to understand not only how quickly their storage is growing, but where that growth is happening. With the right tools, insight, and intelligence, IT leaders can uncover opportunities for operational efficiencies, cost savings, and infrastructure planning.

IT leaders must know their key storage data metrics to understand not only how quickly their storage is growing, but where that growth is happening. It’s important to create an infrastructure system that focuses on improved data visibility, improved operations, and understanding data categorizations.

Contact us today!

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Transcript:

It can be difficult to navigate what is real, what is possible, and what is just buzz when it comes to applying Artificial Intelligence and machine learning to everyday business challenges.

At Clear Intelligence, we are focused on helping organizations improve quality by using AI and machine learning for visual inspection.

More manufacturing companies are adopting AI and Machine Learning to reduce overall cost of production, improve employee safety and increase the quality of their products.

For example, a current project in the rail car manufacturing business applies AI Vision to inspect the quality of welds. Adding AI Vision to their process removed manual inconsistencies, accuracy errors, and top down pressures to increase output.

Clear Intelligence has created the solution to visually detect weld discontinuities in real time as the rail car moves through the welding process.

As each piece of the rail car is being welded together, there is a camera and inkjet sprayer attached to the gantry about 300 degrees from the start of the weld. This camera visually detects any discontinuities in the weld, and simultaneously the ink jet sprayer marks the tank for rework. This means once the tank is done being welded, it is also done being inspected; saving time in the production process, increasing accuracy of the data, and generating more throughput.

Clear’s AI Vision solution helps manufacturing industries increase production throughput by reducing delays and bottlenecks while safely ensuring the best product quality for their customers.

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It can be difficult to navigate what is real, what is possible, and what is just buzz when to comes to applying Artificial Intelligence to everyday business problems.  We want to help you discover what is possible for AI in your business.

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Vision in Action

In this video you will see an example of how a camera, backed by AI software, can identify discontinuities in steel plates.

There are three steel plates – one with no discontinuities and two with different variations. We set up the model to use live inferencing on the camera attached to the robot arm. The camera, for this case, only took a picture once it sensed the robot arm stopped moving for a predefined amount of time.

The software then runs inference on the image, and boxes each location it thinks it has found a defect. It then marks the plate as good or defective, and displays it to our user interface

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Our AI Vision Solution

AI Vision provides a platform and framework that can help drive process, efficiency, accuracy, and speed across areas such as – product defect detection, operational asset inspection, personnel safety, and security. We helps companies produce better products safely while increasing asset life – thereby driving lower cost of quality and operations and increased employee safety.

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Discover the Possible

With a business-first approach, we take the time to understand your key challenges and/or potential opportunities and deliver unprecedented solutions, always keeping your P&L at the forefront of our thinking. Contact us today to get started.

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Properly Manage Your Data

Data growth is rapidly increasing, even as budgets are either static or decreasing. The combination of expansive data and constrictive budgets presents a hefty challenge to businesses and IT leaders. In order to avoid unnecessary and emergency storage purchases, it’s essential that IT leaders know their key storage data metrics to understand not only how quickly their storage is growing, but where that growth is happening. With the right tools, insight, and intelligence, IT leaders can uncover opportunities for operational efficiencies, cost savings, and infrastructure planning.

IT leaders must know their key storage data metrics to understand not only how quickly their storage is growing, but where that growth is happening. It’s important to create an infrastructure system that focuses on improved data visibility, improved operations, and understanding data categorizations.

Contact us today!

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radial_direction=”center center” linear_angle=”180″ background_color=”” background_image=”” background_position=”left top” background_repeat=”no-repeat” background_blend_mode=”none” animation_type=”” animation_direction=”left” animation_speed=”0.3″ animation_offset=”” filter_type=”regular” filter_hue=”0″ filter_saturation=”100″ filter_brightness=”100″ filter_contrast=”100″ filter_invert=”0″ filter_sepia=”0″ filter_opacity=”100″ filter_blur=”0″ filter_hue_hover=”0″ filter_saturation_hover=”100″ filter_brightness_hover=”100″ filter_contrast_hover=”100″ filter_invert_hover=”0″ filter_sepia_hover=”0″ filter_opacity_hover=”100″ filter_blur_hover=”0″ last=”no” border_position=”all”][fusion_text columns=”” column_min_width=”” column_spacing=”” rule_style=”default” rule_size=”” rule_color=”” content_alignment_medium=”” content_alignment_small=”” content_alignment=”” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” class=”” id=”” font_size=”” 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With the threat of COVID-19 still present, many companies are mobilizing solutions to help prevent spread in the workplace while inspiring a strong compliance and safety culture and positive work environment.

IT is tasked with creating systems that are secure, cost effective, and aligned to new organizational safety goals in the post-pandemic work environment.

In this virtual event, attendees hear about the non-invasive and privacy-protected methods Hitachi offers to help organizations:

• Proactively identify potential risks
• Monitor adherence to safety guidelines
• Form data-driven policies and develop future crisis response plans

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Former Clear Intelligence CIO, Brian Murphy, presented at CIO America in Chicago earlier this year on The Art of The Possible: Using AI-Based Vision and Acoustic solutions.  In this video Brian discusses facts, trends, and use cases for AI vision and acoustic based solutions to improve business models  in the modern world.

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The following contains excerpts from “The Artificial Intelligence Effect On Industrial Products” by IBM

A small group of out performers in the industrial products industry is using AI/cognitive to help deliver on the promise of Industry 4.0.

Using AI to unlock the hidden insights in industrial products data

The industrial products industry is awash with data. Instrumentation, sensors, machinery, automation systems, production and operation, maintenance records, and health and safety applications collectively produce a constant flow of data. Industrial products enterprises need technology that supports the vertical delivery of insightful data throughout the organization, both to meet consumer needs and to aim for continuous process improvement. In this report, financial outperformers share their AI successes.

The global industrial products challenge

Organizations in the global industrial products industry face significant cost pressures, increased regulations, disruptive technologies, and the increasingly costly delivery of raw resources.

High volatility in commodity prices has put severe pressure on company margins and can quickly expose inefficient operations. Processes, workflows, and the understanding of performance are dramatically changing. Operations can no longer work in linear execution, or in isolation of other functional work streams such as engineering, maintenance, and planning. Instead, the value chain needs to perform as an integrated whole to support the fluctuating demand cycles and higher cost supply activities.

New AI technologies have the capacity to make sense of the abundance of data through systems that can adapt and learn. By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive greater innovation, and better operational and financial decisions.

To understand how organizations can better plan for AI adoption, the IBM Institute for Business Value (IBV), in collaboration with Oxford Economics, surveyed more than 6,000 C-suite members and heads of functions worldwide—including 300 industrial products respondents. The goal was to better understand their considerations, expectations, and objectives in applying AI solutions to the most pressing business challenges and opportunities.

This report explores how industrial products executives perceive the readiness of the technology, the industry, and their organizations for AI adoption. It identifies how companies are currently applying AI and their plans in the next few years. We also identified a select group of outperformers that are ahead of others in AI adoption and examined what they’re doing differently compared to similar organizations.

Why AI and why now?

AI enables organizations to synthesize vast amounts of structured and unstructured data, query results in natural language, and apply machine-learning capabilities to data analysis. Together, these capabilities can significantly enhance insights, efficiency, and speed. Industrial products companies are at a critical inflection point in their adoption of AI. Surveyed executives recognize that the technology is market-ready, and well over half say the industry and organizations are ready to adopt it.

So where do industrial products organizations specifically want to invest in AI? Each of these three priorities presents significant opportunities to improve efficiency and decision making.

• For quality control, AI systems can analyze data from raw materials, production lines, finished products, maintenance records, and customer complaints to identify causal factors that led to quality problems.

• In production operations, AI systems can continuously learn from process data and actions taken by top-line operators. Similarly, it helps predict and identify impacts and recommend actions to improve production.

• For machine maintenance, AI can identify anomalies, assess their criticality, determine the root cause, and help maintenance technicians correctly perform the repair the first time.

Industrial products leaders gain value from AI

How can enterprises capitalize on new AI capabilities? To help answer this question, we analyzed the survey responses and identified a small group of industrial products outperformers, consisting of 12 percent of our study.

This group self-reported that it significantly outperformed revenue compared to competitors over the past three years, and was significantly more efficient and profitable.

What do these outperformers do differently?

They use data to glean insight, and are confident their organizations are ready for an AI future. Over seven out of ten of these leaders strongly agree that their organization is ready to adopt AI, compared to two out of ten of all other respondents.

Given the potential benefits, not surprisingly, a number of industrial products outperformers have already begun to adopt AI—nearly two thirds (64 percent) versus only 32 percent of all others surveyed.

By examining these leaders, other organizations can understand the need to take action in the AI era. They can then begin to:

• Build an AI data foundation

• Focus on new skills

• Create a new level of intelligence

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