Automate image-based inspection with artificial intelligence.

High demands on products as well as high time and cost pressure are decisive competitive factors across all industries and sectors. Whether in the food or automotive industry quality, safety and speed are today more than ever before factors that determine the success of a company.

Zero-defect production is the goal. But how can it be guaranteed that only flawless products leave the production line? In order to make quality inspection as efficient, simple, reliable and cost-effective as possible, the German company sentin GmbH develops solutions that use deep learning and industrial cameras from IDS to enable fast and robust error detection. A sentin VISION system uses AI-based recognition software and can be trained using a few sample images. Together with a GigE Vision CMOS industrial camera from IDS and an evaluation unit, it can be easily embedded in existing processes.

High demands on products as well as high time and cost pressure are decisive competitive factors across all industries and sectors. Whether in the food or automotive industry – quality, safety and speed are today more than ever before factors that determine the success of a company. Zero-defect production is the goal. But how can it be guaranteed that only flawless products leave the production line? How can faulty quality decisions, which lead to high costs, be avoided? In order to test this reliably, a wide variety of methods are used in quality assurance.

A visual inspection with the human eye is possible, but it is often error-prone and expensive: the eye tires and working time is costly. A mechanical test, on the other hand, is usually accompanied by complex calibration, i.e. setting up and adjusting all parameters of both software and hardware in order to detect every error. In addition, product or material changes require recalibration. Furthermore, with the classic, rule-based approach, a programmer or image processor must program rules specifically for the system to explain to the system how to detect the errors. This is complex and with a very high variance of errors often a hardly solvable Herculean task. All this can cost disproportionately much time and money.

In order to make quality inspection as efficient, simple, reliable and cost-effective as possible, sentin GmbH uses IDS industrial cameras and deep learning to develop solutions that enable fast and robust error detection. This is because, in contrast to conventional image processing, a neural network learns to recognize the features on the basis of images themselves. This is exactly the approach of the intelligent sentin VISION system. It uses an AI-based recognition software and can be trained on the basis of a few sample images. Together with a GigE Vision CMOS industrial camera from IDS and an evaluation unit, it can be easily embedded in existing processes.

Application
The system is capable of segmenting objects, patterns and even defects. Even surfaces that are difficult to detect cannot stop the system. Classical applications can be found, for example, in the automotive industry (defect detection on metallic surfaces) or in the ceramics industry (defect detection by making dents visible on reflecting and mirroring surfaces), but also in the food industry (object and pattern recognition).

Depending on the application, the AI is trained to detect errors or anomalies. With the latter, the system learns to distinguish good from bad parts. If, for example, a surface structure is inspected, see metal part in the automotive industry or ceramic part, errors are detected by Artificial Intelligence as deviations from a comparison with reference images. By using anomaly detection and pre-trained models the system can detect defects based on just a few sample images of good parts.

The hardware setup required for the training and evaluation consists of an IDS industrial camera and appropriate lighting. The recognition models used are trained using reference images. For example, a system and AI model was configured for the error-prone inspection of fabric webs in the textile industry. A difficult task, as mistakes can be very subjective and very small. The system camera for optimum image material of textiles and web materials was selected together with IDS on the basis of specific customer requirements. A GigE Vision CMOS camera (GV-5880CP) was selected, which provides high-resolution data, triggered with precise timing, for accurate image evaluation.

The system learns what constitutes a “good” fabric structure and knows already from a few shots of the fabric what a clean and flawless product looks like. For quality inspection, the image captured by the IDS Vision CP camera is then forwarded via GigE interface to an evaluation computer and processed with the recognition model. This computer can then reliably distinguish good/bad parts and highlight deviations. It gives an output signal when an error is found. In this way, slippage and pseudo rejects can be reduced quickly and easily.

Slippage is the proportion of products that do not meet the standard but are overlooked and therefore not sorted out, often leading to complaints. Pseudo rejects, on the other hand, are those products that meet the quality standard but are nevertheless incorrectly sorted out.

Both hardware and software of the system are flexible: For multiple or wider webs, additional cameras can easily be integrated into the setup. If necessary, the software also allows for re-training of the AI models. “Experience simply shows that a certain amount of night training is always necessary due to small individual circumstances. With pre-trained models from our portfolio, you need fewer reference images for individualization and post training,” explains Christian Els, CEO and co-founder of sentin. In this case, the images show the structured surface of a fabric and a small anomaly on it, which was filtered out in the image on the right:

Anomaly extracted from a recording of a substance (sentin GmbH)

Camera
Extremely accurate image acquisition and precise image evaluation are among the most important requirements for the camera used. Perfectly suitable: The GigE Vision CMOS camera GV-5880CP. The model has a 1/1.8″ rolling shutter CMOS sensor Sony IMX178, which enables a very high resolution of 6.4 MP (3088 x 2076 px, aspect ratio 3:2). It delivers frame rates of up to 18 fps at full resolution and is therefore ideal for visualization tasks in quality control. The sensor from the Sony STARVIS series features BSI technology (“back-side-illumination”) and is one of the most light-sensitive sensors with a low dark current close to the SCMOS range (Scientific CMOS). It ensures impressive results even under very low light conditions. Thanks to the sensor size of 1/1.8″, a wide range of C-Mount lenses is available for the GigE Vision camera model GV-5880CP. “In addition to resolution and frame rate, the interface and the price were decisive factors in the decision for the camera. The direct exchange with the IDS development department has helped us to reduce the time needed for camera integration,” says Arkadius Gombos, Technical Manager at sentin. The integration into the sentin VISION system is done via GenTL and a Python interface.

The GigE Vision camera GV-5880CP from IDS ensures precise image acquisition and accurate image evaluation when inspecting fabric webs. (sentin GmbH)

Conclusion
Automated, image-based quality control with Artificial Intelligence offers many advantages over human visual inspection or conventional machine vision applications. “In AI-based image interpretation, the aim is to create images on which humans can see the error, because then the AI model can do it too,” concludes Christian Els. The system learns to recognize the requirements of the product similar to a human being. But the human brain is beaten at any time by an artificial intelligence in terms of consistency and reliability. Even if the brain is capable of remarkable peak performance, an AI can recognize much more complex error patterns. The human eye, on the other hand, cannot stand up to any camera in terms of fatigue and vision. In combination with deep-learning recognition software, the image processing system therefore enables particularly fast and accurate inspection. Depending on the application, image acquisition and evaluation can take place in just a few milliseconds.

The system can also be applied to other areas such as surface testing. Similar applications are e.g. the testing of matte metal/coatings surfaces (automotive interior), natural materials (stone, wood) or technical textiles such as leather. Scratches, cracks and other defects on consumer goods can thus be detected and the respective products sorted out. Exclude quality defects and produce only “good stuff” – an indispensable process within the framework of quality assurance. IDS cameras in combination with the deep learning supported software of sentin GmbH significantly optimize the detection of defects and objects in quality control. This allows the personnel and time expenditure for complaints and rework, as well as pseudo rejects, to be significantly reduced in a wide range of industries and areas.

• See information on other IDS Imaging products. – published on the Read-out Signpost.

@sentin_ai @IDS_Imaging #mepaxIntPR #PAuto #Food

Checking organic carbon content.

Methods for checking water quality are an incredibly important part of the many processes involved in ensuring we have access to safe drinking water. However, as contaminants can come from many different sources, finding a general solution for contaminant identification and removal can be difficult.

Purification processes for water treatment include removal of undesirable chemicals, bacteria, solid waste and gases and can be very costly. Utility companies in England and Wales invested £2.1 billion (€2.44b) between 2013 and 2014 into infrastructure and assorted costs to ensure safe drinking water.¹

One of the most widely used measures for assessing whether water is safe for consumption or not is the analysis of the organic carbon (TOC) content. Dissolved organic carbon content is a measure of how much carbon is found in the water as part of organic compounds, as opposed to inorganic sources such as carbon dioxide and carbonic acid salts.²   It has been a popular approach since the 1970s for both assessment of drinking water and checking wastewater has been sufficiently purified.

The proportion of organic carbon in water is a good proxy for water quality as high organic carbon levels indicate a high level of organisms in the water or, contamination by organic compounds such as herbicides and insecticides. High levels of microorganisms can arise for a variety of reasons but are often a sign of contamination from a wastewater source.

Testing TOC
Water therefore needs to be continually monitored for signs of change in the TOC content to check it is safe for consumption. While many countries do not specifically regulate for TOC levels, the concentrations of specific volatile organic compounds are covered by legislation and recommended levels of TOC are 0.05 ml/l or less.³

There are a variety of approaches for testing water for organic carbon. One approach is to measure the entire carbon content (organic and inorganic) and then subtract any carbon dioxide detected (as it is considered inorganic carbon) and any other carbon from inorganic sources. Another is to use chemical oxidation or even high temperature so that all the organic compounds in the sample will be oxidized to carbon dioxide, and measuring the carbon dioxide levels, therefore, acts as a proxy for the TOC concentration.

For wastewater plants, being able to perform online, real-time analysis of water content is key and measurements must be sensitive and accurate enough to pick up small changes in even low concentrations of chemical species. British legislation also makes it an offense to supply drinking water which does not adhere to legislation⁴, with several water suppliers being fined over a hundred million pounds for recent discharges of contaminated waters.⁵

Vigilant Monitors
One of the advantages of using carbon dioxide levels as a proxy for TOC content is that carbon dioxide absorbs infrared light very strongly. This means using nondispersive infrared (NDIR) detectors provide a very sensitive way of detecting even trace amounts of carbon dioxide.

Edinburgh Sensors are one of the world leaders in NDIR sensor production and offer a range of NDIR-based gas detectors suitable for TOC measurements of water.⁶ Of these, for easy, quick and reliable TOC measurements, the Gascard NG is an excellent device for quantifying carbon dioxide levels.⁷

Gascard NG
The Gascard NG is well-suited to continual carbon dioxide monitoring for several reasons. First, the device is capable of detecting a wide range of carbon dioxide concentrations, from 0 – 5000 ppm, maintaining a ± 2 % accuracy over the full detection range. This is important so that the sensor has the sensitivity required for checking TOC levels are sufficiently low to be safe for drinking water but means it is also capable of operating under conditions where TOC levels may be very high, for example in the wastewater purification process.

As it can come with built-in true RS232 communications for both control and data logging, the Gascard NG can be used to constantly monitor carbon dioxide levels as well as be integrated into feedback systems, such as for water purification, to change treatment approaches if the TOC content gets too high. UK legislation also requires some level of record-keeping for water quality levels, which can also be automated in a straightforward way with the Gascard.4

The Gascard NG is capable of self-correcting measurements over a range of humidity conditions (0 – 95 %) and the readings can be pressure-corrected with on-board electronics between 800 to 1150 mbar. Temperature compensation is also featured between 0 to 45ºC to ensure reliable measurements, over a wide range of environmental conditions.

Designed to be robust, maintenance-free and fail-safe, the Gascard NG also comes with several customizable options. The expansion port can be used for small graphical display modules for in-situ observable readings and TCP/IP communications can also be included if it’s necessary to have communications over standard networks. In conjunction with Edinburgh Sensor’s expertise and pre- and post-sales support, this means that the Gascard NG can easily be integrated into existing TOC measurement systems to ensure fast and accurate monitoring at all times.

NOTES

1. Water and Treated Water (2019),
2. Volk, C., Wood, L., Johnson, B., Robinson, J., Zhu, H. W., & Kaplan, L. (2002). Monitoring dissolved organic carbon in surface and drinking waters. Journal of Environmental Monitoring, 4(1), 43–47.
3. DEFRA (2019)
4. Water Legislation (2019),
5. Water Companies Watchdog (2019)
6. Edinburgh Sensors (2019),
7. Gascard NG, (2019),

#Pauto @Edinst

Non-destructive testing – a food waste reduction opportunity?

Food waste reduction is a key objective for consumers, businesses and governments seeking to save money, improve food production efficiency, lower greenhouse gas emissions, reduce packaging waste and protect the environment. Such issues have enjoyed a high profile in recent years but in this article Dr Abdel Ezbiri from the technology company Cerulean discusses the waste that results from the temperature testing of fresh and chilled foods, and outline the success that some food processors have achieved in adopting non-destructive testing (NDT) technology.

Background
Under food hygiene regulations, the safety of a wide variety of foods is dependent upon the maintenance of correct temperature conditions in compliance with the principles of Hazard Analysis and Critical Control Point (HACCP). Generally, temperature is the main factor affecting the prevention of microbial food spoilage. In addition to temperature and storage time, the speed and extent of spoilage is affected by the type of food product, its composition, methods used during processing, contamination during processing and the nature of packaging. Temperature testing therefore performs a vital role in the protection of consumers and in compliance with food hygiene regulations relating to sandwiches, snacks, ready meals, prepared foods, and both chilled and frozen foods.

Temperature testing techniques
Traditional methods involve the insertion of a metal probe into the food product in order to determine the temperature of the food; usually at the probe’s tip. In order to check the temperature of a food product, the probe is inserted so that the tip is in the centre of the food (or the thickest part) and left in place until the reading stabilises. After the reading is taken, the probe must be thoroughly cleaned and disinfected to avoid cross-contamination between samples.

Crucially, if the food sample is affected by the testing process (for example, if the packaging seal has been broken) it is no longer suitable for consumption and must be discarded.

There are two main types of non-destructive testing methods – remote infrared cameras and microwave thermometry. Infrared cameras are able to accurately measure the surface temperature of objects remotely. Their advantages are that they are non-destructive and fast, but their main disadvantage is that they measure the surface temperature, which is not necessarily the true temperature of the food, especially if the sample is within packaging.

Instruments that employ microwave thermometry have the major advantage of testing the whole product, producing an average temperature for the entire sample, quickly and accurately. Cerulean is the only manufacturer of commercially available instruments employing this technique for food testing, and the feedback from users of this equipment (Celsius range) is provided in the case studies below. New versions of this technology are being developed to improve efficiency and reduce payback periods even further.

Waste from invasive temperature testing
The amount of waste resulting from invasive temperature testing depends on a number of factors. Firstly, the volume of food products being tested will vary according to the type of food and the individual process. Operators will need to be able to demonstrate that the frequency of testing is appropriate and that the samples being tested are representative of a batch. Consequently, the proportion of food going to waste following temperature testing varies considerably between different processing plants.

Once a tested food product is discarded it can be dealt with in a number of ways. It may go to landfill or incineration, or the food may be manually separated from its packaging and used as animal feed or in the generation of energy by anaerobic digestion. However, all options are detrimental from both financial and environmental perspectives, so many food producers are now moving to NDT methods.

Case study:
Labeyrie Fine Foods
Labeyrie Fine Foods produces a range of products for some of the largest supermarkets in the UK. The company began NDT food testing with a Celsius in early 2017 and now tests a wide range of products, including raw, hot smoked and smoked salmon in a range of forms from fillets to sliced and flaked products. Technical & Quality Systems Auditor Stephen Bradbury says: “This technology enables us to ensure that all chilled products are between zero and four degrees centigrade, quickly analysing the temperature of any given product to ensure that the correct controls are in place.”

Staff at the company’s site at Duns in the Scottish Borders (GB) regularly conduct around 50 tests each day. During peak times this can increase to 70 tests per day. Before 2017, the temperature probe method was employed at the site which meant that an extra packet had to be created for each destructive test. There were also occasions when additional checks were required, which led to further packs being tested and then wasted. Following delivery of the NDT machine, the tests for both methods were run in tandem for a month to check the performance of the Celsius, but thereafter all tests have been undertaken by the faster non-destructive method.

The Celsius was purchased for both commercial and environmental reasons. Stephen says: “It helps us guarantee that the entire product within the outer case is at the correct temperature before it is sent to the customer, and as a non-destructive method it enables us to test as many product cases as required.

“From an environmental perspective, the machine helps us to achieve fish and packaging waste reduction every day.”

Stephen has calculated that the company is completing an average of 47 daily checks using the Celsius machine. “This equates to a waste prevention rate of 282 packs per week including 8.4 kg of packaging every week. Annually, this represents 14,664 packs and 437 kg of waste packaging saved.

“Financially, this means there is a product saving of around £564 (€651) per week plus a packaging cost saving of £50.76 (€59) per week, which delivers a total average annual saving of £31,967 (€36,897), before the added cost of waste removal.”

Concluding Stephen says: “There is a calibration cost of £1,000 (€1154) per year and the machine cost £30,000 (€34,620) to purchase. However, the average savings made in year one have covered the cost and we have reduced the average packaging waste by 437 kg annually and food waste by 1,672 kg. We therefore believe that the machine is both economically and environmentally the right choice for Labeyrie.”

Case study:
Joubere
Joubere is a manufacturer of chilled and ambient foods for the retail and food service sectors. The company’s products include stocks, gravies, soups and porridge, which have been tested non-destructively since the purchase of a Celsius machine in late 2017.

Many of the company’s products are sold in pots so the previous probe test method resulted in the wastage of between 2 and 3% of production. Joubere produces around 25 tonnes of food products per day, so this waste represented around 750 kg of food and containers per day. As a result, the payback for the cost of the machine was less than 2 months.

Joubere’s Andy Milne says: “The non-destructive method is faster than the older probe method because we do not have to wait for the probe to equilibrate, but with the dramatic cost and waste savings that we are making, the advantages of this method are clear.”

Summary
Commenting on behalf of WRAP (Waste and Resources Action Programme), Andrew Parry, Special Advisor Food & Drink, says: “WRAP estimates that food worth £1.4 billion ends up as waste from UK manufacturers each year. Together with the IGD we launched the ‘Food Waste Reduction Roadmap’ last year, to encourage more businesses to Target, Measure and Act on food waste – with the aim of helping the UK achieve Sustainable Development Goal 12.3. NDT appears to have the potential to be a significant part of the ‘toolkit’ manufacturers will need to deliver the challenging food waste reduction targets.”

The greatest opportunity in food waste reduction is to find ways for consumers to throw away less waste, but with a fast payback, investment in NDT temperature testing offers an opportunity for the food production and processing industry to avoid the needless waste of food when it is tested.

#cerulean #NDT @_Enviro_News #Food

Quality fresh fruit and veg!

Creating Gaseous Micro Environments for Packaged Produce to Maintain the Quality of Fresh Fruits and Vegetables.

Food has often had a long and arduous journey before it reaches our plates. In the United States, it is estimated that food typically travels between 1500 and 2500 miles¹ between the farms where it is produced and the dinner table where it is ultimately consumed. What we think of as ‘fresh’ fruit and vegetables may also have been in storage or travelling for much longer than we think, potentially up to four weeks in the case of lettuce.²

Even for locally-sourced produced with reduced food miles, it is important for suppliers to ensure the maximum quality and freshness for their produce. This is because without careful storage for transportation, the vitamin content of fresh foods can deteriorate³ as well as the appearance of the produce, making it more difficult to sell to consumers.

One very successful approach to preserving food quality during transportation and storage is the use of gaseous microenvironments in food packaging and storage. This is known as modified atmospheric packaging (MAP), or atmospherically modified package (AMP), where the foods are packed in containers with an environment of carefully-controlled gas concentrations.⁴ A huge number of the foods we buy make use of MAP to enhance their freshness and shelf lives without the need to add preservatives or modify the food itself in any way.

A Fresh Environment
Transportation of fruit and vegetables is usually performed under refrigerated conditions, regardless of the means of transport, typically around 5°C with carefully controlled humidity.⁵The chilled conditions help to slow the growth of any microorganisms and extent the lifetime of the food, in conjunction with the use of MAP.

Despite the undoubted effectiveness of MAP in preserving produce quality⁶, optimal gas mixtures for MAP vary from produce to produce. For example, for most plant-based produce, some O₂ content in the atmosphere helps the plant to respire, but these needs to be balanced with increased CO₂ concentrations to slow the rate of respiration sufficiently to increase the produce lifetime.^{7, 8} However, there can be subtle differences between the optimum conditions for different types of fruit and vegetables, such as citric fruits which can only tolerate a lower limit of a 5 % O₂ concentration, unlike apples and pears that can cope with O₂ concentrations down to 1 %.⁹

Such careful control of the environmental conditions for optimum fruit and vegetable preservation during transportation relies then on highly-sensitive gas sensors capable of distinguishing the smallest of changes in gas concentration. The typical gases used in MAP for fresh fruit and vegetable preservation are CO₂, O₂ and sometimes N₂.

Precision for Freshness
Edinburgh Sensors offers a range of gas monitoring options well-suited to ensuring optimum gas conditions during fresh food transportation. Their range of CO₂ online monitoring sensors includes the Guardian NG¹⁰, Gascard NG¹¹, the IRgaskiT¹² and the Gascheck¹³, will cover most customer needs for food transport applications.

Where low-cost, highly-robust gas monitors are desirable, the Gascheck is an ideal option. Capable of detecting CO₂ concentrations in the 0-3000 ppm range, with a zero-stability of ± 3 % over 12-months and an accuracy of ± 3 % over the full detection range. Depending on the particular version of the Gascheck, the response time can be as low as 30 seconds, with an initial warm-up time of 5 minutes.

Where higher accuracy is desirable, the Guardian NG comes in a range of options with an accuracy of ± 2 %. The Guardian NG also has a convenient interface which displays true volume % readout over a wide range of pressures as well as being capable of displaying historical graphical information over a user-defined period. If necessary, there are built-in alarm systems to warn if gas concentrations deviate too much or the possibly to connect and interfacing with external logging devices.

The Gascard NG comes now in two versions, either as the stand-alone card, or as the Boxed Gascard¹⁴ to minimise installation and set-up time. The Gascard is capable of detecting CO₂ concentrations in the range of 0 – 5000 ppm and, like the other Edinburgh Sensors products, can also operate in humidity conditions spanning 0 – 95 %. By using RS232 communications the Gascard can be integrated with other control or data logging devices, also with the option for on-board LAN support where required.

Better Produce
Edinburgh Sensor’s full range of instruments comes with both pre- and post-sales technical support and these devices build on their nearly 40 years of expertise in a range of gas sensor technologies. Most of these products are based upon infra-red detection, which facilitates their very high sensitivities for gases such as CO₂ or other hydrocarbon species like methane and in systems like the Boxed Gascard, the infrared source is field-replaceable.

Online monitoring of gas concentrations for MAP applications allows maintenance of optimum conditions for fresh fruit and vegetable preservation, which is highly beneficial not just for ensuring better quality produce, but also ensuring less food spoilage and wastage and the cost-savings associated with this.

@edinsensors #Food

References

1. B. Halweil, Home Grown: The Case for Local Food in a Global Market, World Watch Institute, 2002
2. How old are the ‘fresh’ fruit and vegetables we eat, https://www.theguardian.com/lifeandstyle/2003/jul/13/foodanddrink.features18, (accessed February 2019)
3. M. I. Gil, F. Ferreres and F. A. Tomás-Barberán, J. Agric. Food Chem., 1999, 47, 2213–2217.
4. B. Ooraikul, Modified Atmosphere Packaging of Food, Springer, 1991
5. Packing Fresh Fruit and Vegetables, https://www.modifiedatmospherepackaging.com/~/media/Modifiedatmospherepackaging/Pictures/Guide%20%20%20Packaging%20of%20Fresh%20Fruit%20and%20Vegetables%20%20%20PDF%20file.ashx, (accessed February 2019)
6. E. M. Yahia , Modified and Controlled Atmospheres for the Storage, Transportation, and Packaging of Horticultural Commodities, Taylor and Francis Group, USA, 2009
7. Modified Atmospheric Packaging Poster, https://modifiedatmospherepackaging.com/~/media/Modifiedatmospherepackaging/Brochures/MAP-Poster-Guide-2014.ashx, (accessed February 2019)
8. S. Mangaraj and T. K. Goswami, Fresh Prod., 2009, 3, 1–33.
9. A. A. Kader, D. Zagory and E. L. Kerbel, Crit. Rev. Food Sci. Nutr., 1989, 28, 1–28.
10. Guardian NG, https://edinburghsensors.com/products/gas-monitors/guardian-ng/, (accessed February 2019)
11. Gascard NG, https://edinburghsensors.com/products/oem/gascard-ng/, (accessed February 2019)
12. IRgaskiT, https://edinburghsensors.com/products/oem/irgaskit/, (accessed February 2019)
13. Gascheck, https://edinburghsensors.com/products/oem/gascheck/, (accessed February 2019)
14. Boxed Gascard, https://edinburghsensors.com/products/oem/boxed-gascard/, (accessed February 2019)

The world of virtual commissioning.

Robert Glass, global food and beverage communications manager at ABB explores the concept of virtual commissioning and how system testing can benefit the food industry.

In 1895, pioneer of astronautic theory, Konstantin Tsiolkovsky, developed the concept of the space elevator, a transportation system that would allow vehicles to travel along a cable from the Earth’s surface directly into space. While early incarnations have proven unsuccessful, scientists are still virtually testing new concepts.

Industry 4.0 continues to open up new opportunities across food and beverage manufacturing. In particular, these technologies help improve manufacturing flexibility and the speed and cost at which manufacturers are able to adapt their production to new product variations. Virtual commissioning is one of these key technologies.

What is virtual commissioning?
Virtual commissioning is the creation of a digital replica of a physical manufacturing environment. For example, a robotic picking and packing cell can be modeled on a computer, along with its automation control systems, which include robotic control systems, PLCs, variable speed drives, motors, and even safety products. This “virtual” model of the robot cell can be modified according to the new process requirements and product specifications. Once the model is programmed, every step of that cell’s operation can be tested and verified in the virtual world. If there are changes that are needed in the process automation or robot movement, these can be made on the same computer, allowing the robot to be reprogrammed, orchanges made to the variable speed drives and PLC programming. The ABB Ability™ RobotStudio is one tool that enables this type of virtual commissioning.

Once reprogrammed, the system is tested again and if it passes, it’s ready for physical deployment. This is where the real benefits become tangible. By using virtual commissioning to program and test ahead of time, less process downtime is required and manufacturers can reduce the changeover risks.

Automation programming and software errors in a system can be incredibly difficult and costly to rectify, particularly if they are found later on in the production process. Research by Austrian software testing frim Tricentis, estimated that software bugs, glitches and security failures cost businesses across the world $1.1 trillion.

To achieve the full potential of virtual commissioning, the simulation must be integrated across the entire plant process, including both the planning and engineering phase. Known as simulation-based engineering, this step is integral for the installation of reliable systems. The use of simulations in a plant is not a new concept, in fact virtual commissioning has been researched for more than a decade.

The benefits
The implementation of virtual commissioning brings with it a number of benefits. The ‘try before you buy’ concept allows plant managers to model and test the behavior of a line before making any physical changes. This saves time as the user can program the system’s automation while testing and fixing errors. The use of a digital model can also reduce risk when changing or adding processes.

One company which has seen significant improvements in production since investing in virtual commissioning is Comau, a supplier of automotive body and powertrain manufacturing and assembly technologies. Comau’s head of engineering and automation systems, Franceso Matergia, said: “We were able to reprogram 200 robots in just three days using virtual commissioning as opposed to roughly 10 weekends had the work been done on the factory floor.”

Just as you wouldn’t build a space elevator without meticulous planning and years of small scale prototyping, it’s very cost and time beneficial to build and test in a virtual environment where you can find the bugs and discover the unforeseen challenges and mitigate them without added downtime or loss of production. It’s much better to discover that bug while on the ground versus at 100,000 feet midway between the surface of the earth and that penthouse in space.

@ABBgroupnews #PAuto @StoneJunctionPR

Blockchain: the future of food traceability?

Shan Zhan, global business manager at ABB’s food and beverage business, looks at how blockchain* can be used to enhance food traceability.

“The Blockchain, can change…well everything.” That was the prediction of Goldman Sachs in 2015. There has been a lot of talk in the media recently about Blockchain, particularly around Bitcoin and other cryptocurrencies, but just as the investment bank giant predicted, the technology is starting to have more wide-reaching impacts on other sectors.

A report from research consultancy Kairos Future describes blockchain as a founding block for the digitalization of society. With multinationals such as IBM and Walmart driving a pilot project using blockchain technology for traceability, the food and beverage industry needs to look at the need for the protection of traceability data.

The United Nations recognizes food security as a key priority, especially in developing countries. While most countries must abide by strict traceability regulations, which are particularly strong in the EU, other regions may not have the same standards or the data may be at risk of fraud.

Food fraud is described by the Food Safety Net Services (FSNS) as the act of purposely altering, misrepresenting, mislabeling, substituting or tampering with any food product at any point along the farm-to-table food supply chain. Since the thirteenth century, laws have existed to protect consumers against harm from this. The first instance recorded of these laws was during the reign of English monarch King John, when England introduced laws against diluting wine with water or packing flour with chalk.

The crime still exists to this day. While malicious contamination intended to damage public health is a significant concern, a bigger problem is the mislabeling of food for financial gain. The biggest areas of risk are bulk commodities such as coffee and tea, composite meat products and Marine Stewardship Council (MSC) labelled fish. For example, lower-cost types of rice such as long-grain are sometimes mixed with a small amount of higher-priced basmati rice and sold as the latter. By using blockchain technology in their traceability records, food manufacturers can prevent this from happening.

Blockchain is a type of distributed ledger technology that keeps a digital record of all transactions. The records are broadcasted to a peer-to-peer (P2P) network consisting of computers known as nodes. Once a new transaction is verified, it is added as a new block to the blockchain and cannot be altered. And as the authors of Blockchain Revolution explain, “the blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value”.

When records of suppliers and customers are collected manually, to ensure the end manufacturer can trace the entire process, this does not protect the confidential data of suppliers. Blockchain technology anonymizes the data but it is still sufficient to ensure that the supply chain is up to standard.

In the case of mislabeled basmati rice, blockchain technology would prevent food fraud as the amount of each ingredient going into the supply chain cannot be lower than the volume going out. This would flag the product as a fraudulent product.

Not only can it help to monitor food ingredients, it can also monitor the conditions at the production facility. These are often very difficult to verify and, even if records are taken, they can be falsified. A photo or digital file can be taken to record the situation, such as a fish being caught, to show that it complies with the MSC’s regulations on sustainably caught seafood.

The blockchain will then create a secure digital fingerprint for this image that is recorded in the blockchain, known as a hash. The time and location of the photograph will be encrypted as part of this hash, so it cannot be manipulated. The next supplier in the blockchain will then have a key to this hash and will be able to see that their product has met the regulations.

Food and beverage manufacturers can also use blockchain to ensure that conditions at their production facilities are being met, or any other data that needs to be securely transferred along the production line. While we are not yet advanced enough with this technology to implement across all food and beverage supply chains, increased digitalization and being at the forefront of investment into these technologies will help plant managers to prepare their supply chain against the food fraud threat.

* The Wikipedia entry on Blockchain!

@ABBgroupnews #PAuto #Food @FSNSLABS @MSCecolabel

Simulating agricultural climate change scenarios.

Extreme weather, believed to result from climate change and increased atmospheric CO₂ levels, is a concern for many. And beyond extreme events, global warming is also expected to impact agriculture.(Charlotte Observer, 7 Sept 2017)

Although it is expected that climate change will significantly affect agriculture and cause decreases in crop yields, the full effects of climate change on agriculture and human food supplies are not yet understood. (1, 2 & 3 below)

Simulating a Changing Climate
To fully understand the effects that changes in temperature, CO₂, and water availability caused by climate change may have on crop growth and food availability, scientists often employ controlled growth chambers to grow plants in conditions that simulate the expected atmospheric conditions at the end of the century. Growth chambers enable precise control of CO₂ levels, temperature, water availability, humidity, soil quality and light quality, enabling researchers to study how plant growth changes in elevated CO₂ levels, elevated temperatures, and altered water availability.

However, plant behavior in the field often differs significantly from in growth chambers. Due to differences in light quality, light intensity, temperature fluctuations, evaporative demand, and other biotic and abiotic stress factors, the growth of plants in small, controlled growth chambers doesn’t always adequately reflect plant growth in the field and the less realistic the experimental conditions used during climate change simulation experiments, the less likely the resultant predictions will reflect reality.³

Over the past 30 years, there have been several attempts to more closely simulate climate change growing scenarios including open top chambers, free air CO₂ enrichment, temperature gradient tunnels and free air temperature increases, though each of these methods has significant drawbacks.

For example, chamber-less CO₂ exposure systems do not allow rigorous control of gas concentrations, while other systems suffer from “chamber effects” included changes in wind velocity, humidity, temperature, light quality and soil quality.^3,4

Recently, researchers in Spain have reported growth chamber greenhouses and temperature gradient greenhouses, designed to remove some of the disadvantages of simulating the effects of climate change on crop growth in growth chambers. A paper reporting their methodology was published in Plant Science in 2014 and describes how they used growth chamber greenhouses and temperature gradient greenhouses to simulate climate change scenarios and investigate plant responses.³

Choosing the Right Growth Chamber
Growth chamber and temperature gradient greenhouses offer increased working area compared with traditional growth chambers, enabling them to work as greenhouses without the need for isolation panels, while still enabling precise control of CO₂ concentration, temperature, water availability, and other environmental factors.

Such greenhouses have been used to study the potential effects of climate change on the growth of lettuce, alfalfa, and grapevine.

CO2 Sensors for Climate Change Research
For researchers to study the effects of climate change on plant growth using growth chambers or greenhouses, highly accurate CO2 measurements are required.

The Spanish team used the Edinburgh Sensors Guardian sensor in their greenhouses to provide precise, reliable CO2 measurements. Edinburg Sensors is a customer-focused provider of high-quality gas sensing solutions that have been providing gas sensors to the research community since the 1980s.^3,5

The Guardian NG from Edinburgh Sensors provides accurate CO₂ measurements in research greenhouses mimicking climate change scenarios. The Edinburgh Sensors Guardian NG provides near-analyzer quality continuous measurement of CO₂ concentrations. The CO₂ detection range is 0-3000 ppm, and the sensor can operate in 0-95% relative humidity and temperatures of 0-45 °C, making it ideal for use in greenhouses with conditions intended to mimic climate change scenarios.

Furthermore, the Guardian NG is easy to install as a stand-alone product in greenhouses to measure CO₂, or in combination with CO₂ controllers as done by the Spanish team in their growth control and temperature gradient greenhouses.^4,6 Conclusions Simulating climate change scenarios in with elevated CO₂ concentrations is essential for understanding the potential effects of climate change on plant growth and crop yields. Accurate CO₂ concentration measurements are essential for such studies, and the Edinburgh Sensors Guardian NG is an excellent option for researchers building research greenhouses for climate change simulation.

References

1. Walthall CL, Hatfield J, Backlund P, et al. ‘Climate Change and Agriculture in the United States: Effects and Adaptation.’ USDA Technical Bulletin 1935, 2012. Available from: http://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1000&context=ge_at_reports
2. https://www.co2.earth/2100-projections Accessed September 7th, 2017.
3. Morales F, Pascual I, Sánchez-Díaz M, Aguirreolea J, Irigoyen JJ, Goicoechea N Antolín MC, Oyarzun M, Urdiain A, ‘Methodological advances: Using greenhouses to simulate climate change scenarios’ Plant Science 226:30-40, 2014.
4. Aguirreolea J, Irigoyen JJ, Perez P, Martinez-Carrasco R, Sánchez-Díaz M, ‘The use of temperature gradient tunnels for studying the combined effect of CO2, temperature and water availability in N2 fixing alfalfa plants’ Annals of Applied Biology, 146:51-60, 2005.
5. https://edinburghsensors.com/products/gas-monitors/guardian-ng/ Accessed September 7th, 2017.

@Edinst #PAuto #Food

Measuring CO2 to optimise bulk storage of food.

Meeting the food requirements of a growing global population is becoming increasingly difficult. Despite the need for additional food, it is estimated that 50-60% of grain is lost after harvesting, at a cost of about $1 trillion per year. (See note 1 below)

One of the major reasons for lost grain is spoilage due to mould or insect infestation during storage.² To provide a constant supply of grain year-round, after grains are harvested they are often kept in long term storage. Maintaining the quality of stored grain is crucial, both to ensure the quality of the final food products, and to prevent economic losses for farmers.

Edinburgh Sensors GascardNG Sensor

Insects and moulds can grow in stored grain, and their ability to flourish depends on the temperature and moisture of the stored grain. Moulds are the most common cause of grain spoilage and can cause changes in the appearance and quality of stored grains. Some moulds can release toxic chemicals called mycotoxins which can suppress the immune system, reduce nutrient absorption, cause cancer, and even be lethal in high doses. It is therefore crucially important to prevent the presence of mycotoxins in food products.²

Monitoring Stored Grain
Farmers are advised to check their stored grain weekly for signs of spoilage.³ Traditionally, grains are checked visually and by odour. Grain sampling can allow earlier detection of insects and moulds, but these methods can be tedious and time-consuming. Rapid, simple methods are needed for early detection of spoilage and to prevent grain losses.²

When moulds and insects grow, and respire, they produce CO₂, moisture and heat. Temperature sensors detect increases in temperature caused by mould growth or insect infestation, therefore indicating the presence of grain spoilage. However, they are not able to detect temperature increases caused by infestation unless the infestation is within a few meters of the sensors. CO₂ sensors can detect the CO₂ produced by moulds and insects during respiration. As the CO₂ gas moves with air currents, CO₂ sensors can detect infestations that are located further away from the sensor than temperature sensors. CO₂ measurements are therefore an important part of the toolkit needed to monitor stored grain quality.²

Using CO₂ Measurements to Detect Spoilage
CO₂ monitoring can be used for early detection of spoilage in stored grains, and to monitor the quality of stored grains. Safe grain storage usually results in CO₂ concentrations below 600 ppm, while concentrations of 600-1500 ppm indicate the onset of mould growth. CO₂ concentrations above 1500 ppm indicate severe infestations and could represent the presence of mycotoxins.⁴

CO₂ measurements can be taken easily, quickly and can detect infestations 3-5 weeks earlier than temperature monitoring. Once spoilage is detected, the manager of the storage facility can address the problem by aerating, turning, or selling the grain. Furthermore, CO₂ measurements can aid in deciding which storage structure should be unloaded first.²

Research published by Purdue University and Kansas State University have confirmed that high CO₂ levels detected by stationary and portable devices are associated with high levels of spoilage and the presence of mycotoxins.^4,5 Furthermore, they compared the ability of temperature sensors and CO2 sensors in a storage unit filled with grain to detect the presence of a simulated ‘hot spot’ created using a water drip to encourage mould growth.

The CO₂ concentration in the headspace of the storage unit showed a strong correlation with the temperature at the core of the hot spot, and the CO₂ sensors were, therefore, able to detect biological activity. The temperature sensors were not able to detect the mould growth, despite being placed within 0.3-1 m of the hotspot.⁶

To enable efficient monitoring of grain spoilage accurate, reliable and simple to use CO₂ detectors are required. Gascard NG Gas Detector from Edinburgh Sensors provide accurate CO₂ measurements along with atmospheric data, enabling grain storage managers to make decisions with confidence.

The Gascard NG Gas Detector uses a proprietary dual wavelength infrared sensor to enable the long term, reliable measurement of CO₂ over a wide range of concentrations and in temperatures ranging from 0-45 °C. Measurements are unaffected by humidity (0-95% relative humidity) and the onboard pressure and temperature sensors provide real-time environmental compensation, resulting in the most accurate CO2 concentration readings.

Conclusion
Easy, fast, and accurate CO₂ concentration monitoring during grain storage can provide early detection of grain spoilage, resulting in reduced grain losses, higher quality stored grain, and lower mycotoxin levels. CO₂ monitoring could save millions of dollars annually in the grain production industry.⁴

---

References

1. Kumar D, Kalita P, Reducing Postharvest Losses during Storage of Grain Crops to Strengthen Food Security in Developing Countries. Foods 6(1):8, 2017.
2. http://www.world-grain.com/Departments/Grain-Operations/2016/7/Monitoring-CO2-in-stored-grain.aspx?cck=1 Accessed May 25th, 2017.
3. HGCA Grain storage guide for cereals and oilseeds, third edition, available from: https://cereals.ahdb.org.uk/media/490264/g52-grain-storage-guide-3rd-edition.pdf Accessed May 25th, 2017.
4. Maier DE, Channaiah LH, Martinez-Kawas, A, Lawrence JS, Chaves EV, Coradi PC, Fromme GA, Monitoring carbon dioxide concentration for early detection of spoilage in stored grain. Proceedings of the 10th International Working Conference on Stored Product Protection, 425, 2010.
5. Maier DE, Hulasare R, Qian B, Armstrong P, Monitoring carbon dioxide levels for early detection of spoilage and pests in stored grain. Proceedings of the 9th International Working Conference on Stored Product Protection PS10-6160, 2006.
6. Ileleji KE, Maier DE, Bhat C, Woloshuk CP, Detection of a Developing Hot Spot in Stored Corn with a CO2 Sensor. Applied Engineering in Agriculture 22(2):275-289, 2006.

 

Continuous compliance with PLM.

Adam Bannaghan, technical director of Design Rule, discusses the growing role of PLM in managing quality and compliance.

The advantages of product lifecycle management (PLM) software are widely understood; improved product quality, lower development costs, valuable design data and a significant reduction in waste. However, one benefit that does not get as much attention is PLM’s support of regulatory compliance.

Nobody would dispute the necessity of regulatory compliance, but in the product development realm it certainly isn’t the most interesting topic. Regardless of its lack of glamour, failure to comply with industry regulations can render the more exciting advantages of PLM redundant.

From a product designer’s perspective, compliance through PLM delivers notable strategic advantages. Achieving compliance in the initial design stage can save time and reduce engineering changes in the long run. What is more, this design-for-compliance approach sets the bar for quality product development, creating a unified standard to which the entire workforce can adhere. What is more, the support of a PLM platform significantly simplifies the compliance process, especially for businesses operating in sectors with fast-changing or complicated regulations.

For example, AS/EN 9100, is a series of quality management guidelines for the aerospace sector, which are globally recognised, but set to change later this year. December 2016 is the target date for companies to achieve these new standards – a fast transition for those managing compliance without the help of dedicated software.

Similarly, the defence industry has its own standards to follow. ITAR (International Traffic in Arms Regulations) and EAR (Export Administration Regulations) are notoriously strict exporting standards, delivering both civil and criminal penalties to companies that fail to comply.

“Fines for ITAR violations in recent years have ranged from several hundred thousand to $100 million,” explained Kay Georgi, an import/export compliance attorney and partner at law firm Arent Fox LLP in Washington. “Wilful violations can be penalised by criminal fines, debarment, both of the export and government contracting varieties, and jail time for individuals.”

PLM across sectors
The strict nature of all these regulations is not limited to aerospace and defence however. Electrical, food and beverage, pharmaceutical and consumer goods are also subject to different, but equally stern, compliance rules.

Despite varying requirements across industries, there are a number of PLM options that support compliance on an industry-specific basis. Dassault Systèmes ENOVIA platform, for example, allows businesses to input compliance definition directly into the program. This ensures that, depending on the industry, the product is able to meet the necessary standards. As an intelligent PLM platform, ENOVIA delivers full traceability of the product development process, from conception right through to manufacturing.

For those in charge of managing compliance, access to this data is incredibly valuable, for both auditing and providing evidence to regulatory panels. By acquiring industry-specific modules, businesses can rest assured that their compliance is being managed appropriately for their sector – avoiding nasty surprises or unsuccessful compliance.

For some industry sectors, failure to comply can cause momentous damage, beyond the obvious financial difficulties and time-to-market delays you might expect. For sensitive markets, like pharmaceutical or food and beverage, regulatory failure can wreak havoc on a brand’s reputation. What’s more, if the uncompliant product is subject to a recall, or the company is issued with a newsworthy penalty charge, the reputational damage can be irreparable.

PLM software is widely regarded as an effective tool to simplify product design. However, by providing a single source of truth for the entire development process, the potential of PLM surpasses this basic function. Using PLM for compliance equips manufacturers with complete data traceability, from the initial stages of design, right through to product launch. What’s more, industry-specific applications are dramatically simplifying the entire compliance process by guaranteeing businesses can meet particular regulations from the very outset.

Meeting regulatory standards is an undisputed obligation for product designers. However, as the strategic and product quality benefits of design-for-compliance become more apparent, it is likely that complying through PLM will become standard practice in the near future.

#PLM @designruleltd #PAuto #Pharma #Food @StoneJunctionPR

Application for Mass flow measurements for those over 18 years old!

When thinking of alcoholic products that are produced in Britain, a fine malt Whiskey may spring to mind or perhaps beer brewed in one of the numerous breweries that can be found dotted around the country. How many people however, would immediately think of Vodka?

Well, nestled in the Herefordshire countryside, the family run Chase distillery (entry only to over 18 year olds!) thinks a lot about Vodka, in fact it produces the award winning Chase Vodka which is the World’s first super premium English potato Vodka.

The entire process from seed to bottle takes place on the Chase estate ensuring that a close eye can be kept on all stages from growing the potatoes to distilling and bottling. It was at the distilling stage that Chase was looking for a flowmeter that was capable of measuring the flow rate of fermented potato mash. After careful consideration, they decided on Krohne’s OPTIMASS 1300 Coriolis mass flowmeter.

The fermentation process is started with the mashing of potatoes and the addition of a brewer’s yeast. After about a week, the fermented potato mash is distilled four times in a bespoke copper batch pot and then twice more in a rectification column. It is here that the OPTIMASS 1300 is installed in a vertical pipe run feeding the distillation column. The density of the medium going through the meter can vary from 0.95 to 1.1kg/litre and flows at a rate of 2000 l/hr with pressure of 1BarG at a temperature of 30⁰C.

With the available space being limited, Chase required a meter that had a small installation envelope, but could still measure accurately and was capable of being CIP cleaned at 65⁰C. The OPTIMASS 1300 has a dual straight tube design which makes it ideal for use in hygienic applications as there are no crevices or bends for bacteria to gather and the meter can be easily drained and cleaned. Due to the hygienic nature of the application the OPTIMASS 1300 was supplied with hygienic fittings and also has all of the necessary hygienic industry approvals.

Prior to installing the OPTIMASS 1300, Chase used a manual method to monitor the flow of fermented potato mash into the distillation column, however they were looking for a mass flow meter to automate the process. The OPTIMASS 1300 has enabled Chase to monitor the feedstock to finished product ratio accurately and since installation it has also reduced production time by highlighting an underperforming feed pump that was increasing the mash charging time which in turn lengthened the production time.

Tim Nolan, engineering manager at Chase is very pleased with the performance of the OPTIMASS 1300, “Installing the KROHNE meter has meant that we can automate the process and ultimately reduce production time.  It also allows us increased flexibility as we can install the meter on other parts of the process to verify efficiency,” he continues, “KROHNE have supplied us with a meter that complies to our hygienic requirements and has proved to be very reliable.”

Initially, the OPTIMASS 1300 will be used with a local display, however in the future it is planned to interface the meter with the PLC using mA outputs to measure volumetric flow, density and temperature.