Machine vision is one of the enablers of Industry 4.0 with increased integration in production lines, especially in the quality control of products and processes. In recent years, a real revolution is taking place in this field with the integration of Artificial Intelligence in image processing, with a potential yet to be discovered. Despite the limitations of Artificial Intelligence in terms of reliability, results are being obtained in industry that were previously unthinkable using traditional machine vision.
The purpose of this post is not to talk about the possibilities of Artificial Intelligence, as there are many blogs that deal with this task, the purpose is to highlight the potential of traditional machine vision when you have experience and develop good ideas.
Machine vision is not just a set of algorithms that are applied directly to images obtained by high-performance cameras. When we develop a machine vision system, we do so to detect a variety of defects or product characteristics. Our task is to select the most appropriate technology and generate the optimal conditions in the scene in order to extract the required information from the physical world from the captured images. There are many variables to consider in this task: the characteristics of the lighting used in the scene; the relative position between the acquisition equipment, the lighting system and the object to be analysed; the characteristics of the inspection area; the configuration and sensitivity of the acquisition systems, etc.
As a representative anecdote of the importance of experience, I would like to highlight a case that was given to us in an automative components factory.
The company had installed a high-performance commercial vision system whose objective was to identify various parts based on colour. After several failures, we were asked to help configure the equipment, but instead of acting on these devices, we worked on changing the lighting conditions of the scene and simply turned the spotlights around and placed panels to obtain diffuse lighting instead of direct lighting. This solved the problem and the vision reached the level of reliability required by the client.
In this post, I would like to highlight an important case of success in the automative industry that has had a relevant impact on its production process, this is the SIVAM5 vision system developed by CARTIF and integrated in cold drawing lines of laminated sheet metal.
As we all know, the surface quality of the vehicle´s exterior is key for users, which is why companies in the automotive sector have to make a significant effort to detect and correct the presence of defects in the bodywork of their vehicles. Most of these defects occur at the stamping stage, but considering the inconsistency of the colour of the sheet metal and the generation of diffuse reflections, in some cases these defects go unnoticed to the body assembly stage and then to the painting stage, after which they become noticeable. This means that a small defect not detected in time translates into a large cost for the production of the vehicle.
To detect these defects at an early stage, we have developed an innovative machine vision system to detect the micro-cracks and pores that are generated in the cold stamping process of rolled sheet metal. This is a clear example of a robust solution based on a simple idea, “the passage of light through the pores of the sheet metal”, but where a great technological effort has been made to implement the idea in the production line. To this end, various optical technologies have been combined with the development of complex mechanical systems, resulting in a high -performance technological solution, capable of carrying out an exhaustive inspection of the critical points of the sheets in 100% of the production and without penalising the short cadence times that characterise press lines.
Thanks to its excellent resistance to vibrations and impacts, its great adptability for the integration of new references and its reliability in the detection of defects, a robust, flexible and reliable solution has been obtained. Based on a simple idea, a robust solution has been implemented in the production process of large companies in the automotive sector, such as Renault and Gestamp, where it has been operating without updates for more than 20 years, working day and night.
Water is essential for human survival and well-being and plays an important role for many economic sectors. However, water resources are unevenly distributed in space and time, and are under pressure from human activity and economic development.
In addition to water for irrigation and food production which puts one of the greatest pressures on freshwater resources, industry is also a major water consumer, accounting for between 10% (Asia) and 57% (Europe) of total water consumption, either for the production of its products, and/or for the maintenance of its materials and equipment. All industrial sectors make use of water for industrial processes, ranging from those that manufacture foodstuffs to those that manufacture electronic devices.
Wastewater management is also one of the most important environmental problems facing society today, and is therefore an issue that transcends purely industrial activities, since as a vital substance, water is an ecosystem service that is transversal to most human activities, and whose traceability is heavily regulated by governmental and environmental agencies.
The possibility of reusing industrial water, regardless of whether the intention is to increase water supply or to manage nutrients in treated effluents (also a factor leading to water reuse), has positive benefits that are also the main motivators for the implementation of reuse programmes in companies.
Water Consumption in Industry – Management and Saving Plan
Industries can make better use of water, machinery, processes, services and accessories that demand large quantities of this resource that can be reduced with efficient use techniques.
For each type of industry, water is essential to satisfy different needs, and it is common to prioritise water consumption for cleaning and disinfection of products or installations and equipment. In these cleaning and disinfection tasks, the volume of water consumed varies according to the size, equipment and facilities, and the potential for savings is significant.
Therefore, water reuse should be examined from a circular economy perspective and the opportunities and risks of water reuse in the transition to a circular economy should be investigated for each type of industry.
The objectives of creating a water consumption management and saving plan in companies are:
Define methods to find out the water consumption in the facilities.
Identify strategies and points for improvement in the water consumption actions of the facilities and assess their feasibility.
To implement an effective system to reduce and control this water consumption.
Promote the participation of workers.
Water use in industry
The integral water cycle in industry
The transition to a circular economy encourages more efficient water use and, together with incentives for innovation, can improve an economy’s ability to cope with the demands of the growing imbalance between water supply and demand.
From a circular economy perspective, water reuse is a win-win option. The full cycle of wastewater management is a key component of the cycle, from source, through distribution, collection (sewerage and sanitation systems) and treatment to disposal and reuse, including water, nutrient and energy recovery. Circular economy initiatives aim to close resource loops and extend the useful life of resources and materials through longer use, reuse and remanufacturing.
The selective segregation-correction of segregated effluents from the different industrial activities (process water, cleaning, cooling, boilers, sanitary, etc.) favours the recirculation of water and the reuse of the company’s own treated water, as well as the reuse of grey water. It also minimises water consumption, reduces the final volume of water to be treated or managed and increases the efficiency of the final treatment process.
In general, water reuse requires physico-chemical treatment processes, connections, waste disposal mechanisms and other systems. The level of treatment will depend on the quality of water required for the proposed use.
The implementation of water management and water savings to be optimised is described by means of the 9 elements that make up the integral water cycle in industry:
Supply sources: distribution network, own wells, rainwater, etc.
Specific treatment depending on the quality requirements for the different types and uses of water.
Piping to the facilities.
Uses in the process (supply to product, reaction medium, dilution, etc.) and auxiliary activities (cooling towers, steam boilers, cleaning of equipment and facilities).
Effluent drainage.
Recirculation.
Purification (own or external WWTP).
Internal reuse.
Discharge of wastewater, quality requirement limited by the competent environmental authority.
Water consumption in industry can be rationalised and minimised through various improvements in the production process and auxiliary activities, taking as a reference the application of BATs (Best Available Techniques in relation to integrated environmental authorisations in industrial activities).
As a rule, general actions concern the modification of open cooling circuits into closed ones, the avoidance of losses in steam systems, the improvement of inlet water conditioning systems and production means, and the optimisation of cleaning operations of equipment and installations.
Recirculation is considered if water treatment is not necessary or is very simple, as it involves the successive use of a flow of water in the same process, consuming a small percentage of flow renewal in each cycle.
Internal reuse is the use of water already used in the industry itself, treated by a specific treatment, for other uses that are less demanding in terms of quality or sensitivity.
Non-conventional resources such, as rainwater harvesting, are an easy way to obtain water and do not require purification, but depends on the amount of precipitation in each location. It offers advantages such as high physico-chemical water quality without the need for purification and a simple infrastructure.
The reuse of greywater from showers and toilets with a low level of contamination can be treated into clean, non-potable water.
Operational methodology for optimising water consumption and management
The procedure is summarised as follows:
STEP 1
Data collection and analysis. Request for previous documentation and data necessary for the evaluation of water management.
STEP 2
Visit to the company to recognise “in situ” the corresponding characteristics of the production processes developed, as well as the use of water in the plant.
STEP 3
General description of the production processes and auxiliary activities, identifying the different operations: process line, water line, treatment lines and auxiliary activities (refrigeration, steam boiler, cleaning of equipment and containers and storage).
Diagram/plan of water use in the company.
Substances involved, raw materials, reagents, by-products.
Inventory and description of ancillary activities.
Inventory, origin, handling and destination of effluents, wastes and emissions.
STEP 4
Report writing:
Diagnosis of minimisation of water consumption and proposal for improvement.
Prioritisation of actions according to their performance.
Essentially, the fundamental strategy for the optimisation of water management is the global characterisation of water use, the application of selective segregation-correction of process effluents and the analysis of the possible recovery and utilisation of these effluents.
Optimising water management in industry can achieve savings of 40-50%. This can reduce costs and protect natural resources. Companies should be aware that this increases the social prestige of the company with an economic benefit and promotes sustainability.
For many science fiction fans, quantum computers are those gadgets than can make everything and that they are installed as on-board computers in spacecrafts or they appear as laptops of reduced size and sophisticated aesthetics. For many of those that aren´t fans of the genre, quantum computers don´t even ring a bell. In any case, common to both groups is that mostly didn´t think this computers are real.
Reality is that quantum computers exist and they are in use. It is true that this computers are far from being the all-powerful machines science fiction portraits, and even less are tiny and portable devices that we can use in our day a day.
Nowadays quantum computers are freezers of an adult size that hang up from the laboratories roof, with a eye-catching appearance: horizontal platforms with a lot of gold cables. The reason of its curious design is the instability of these computers. Due to their quantum nature, these computers are affected by all type of disturbances, from little seismic movements to electromagnetic waves such as radio waves or of telephones. Moreover, these computers function well only when they work at almost 0 kelvin, with just enough energy for a single electron to be able to move per quantum chip.
The characteristics of these computers, joint with a huge investment in their construction, makes very difficult that nowadays we have an own Personal Quantum Computer as we have PC´s. But far from discouraging, even with these disadvantages, quantum computers are in use thanks to remote control platforms. They exist software development kits1 with repository of algorithms (between them, machine learning algorithms and solvers of optimization problems), development tools of quantum circuits/algorithms, quantum simulators and access to quantum computers of different characteristics. In addition, bibliography and tutorials for the use of these tools are even increasingly prolific.
The increase of the use of quantum computing is due to the increase of public and private financing in sectors such as telecommunications, mobility, banking, cryptography or the science of life2. From the European Commission , is expected and investment of a billion euros dedicated to research projects in this field for the years 2018-2028. Until mid-2021, they have been supported more than 20 projects with a financing of 132 millions 3.
In particular, in Spain, the Council of Ministers approved a grant of 22 millions of euros to boost the field of quantum computing in 2021 with the project Quantum Spain, project with an estimated investment of 60 millions to 3 years. In addition, it arrives to Barcelona the first quantum computer in our country.
Although the order should have be the other way round, after all these figures of investment in the development of this technology, we wonder why there is so much interest in quantum computing. The answer is that these computers allows the resolution of impossible problems to solve for traditional computers. Moreover, due to their different functioning, they are able to perform operations in a much faster and efficient manner.
Do you know that all current cryptography is based on the inability of today´s computers to solve some mathematical problems? On the other hand, a quantum computer completely developed it wouldn´t have those problem. It could, for example, decode your bank account number and access to your savings. Or also enter into the pentagon and decode all type of secret documents. But don´t worry, for better or worse, quantum computers are yet far from this development level.
Another example of its usefulness would be the control of the switches of an electric network, when you want to determine the configuration that provides minimum losses together with a guaranteed supply of all loads in the network.
In general, quantum computers are useful in any control and logistic problem with binary and large variables.
It is clear that far from being science fiction, quantum computing is a reality that is becoming increasingly evident in academic and professional circles. Far from being the on-board computers of a spacecraft or the processing core of a laptop or similar, its presence has increased tremendously in recent years, and is expected to increase even more in the next 10 years. It is therefore important for researchers and scientist to become familiar with these new technologies as soon as possible.
Each landscape makes specific, different, unique feelings. When contemplating a meadow dotted with trees, we do feel something totally different from what we feel looking at a desert area. This also happens when facing cultural landscapes1. A Romanesque church does not make the same sensations as the ones perceived when contemplating cave paintings.
Numerous investigations conclude that there is a significant correlation between our personality and the landscape preferences. Other research argues that the human-landscape relationship has an “innate” basis, dating back to the survival needs of primitive humans, whose environment demanded perceptual abilities and predispositions, which today- at a psichological level- are still functioning. This explains why we still prefer open and slightly flat landscapes (watching predators), in addition to vegetation and good access to water (covering vital needs).
Then, it could be argued that the affective system brought into ply in landscape appraisal is a consequence of wider individual strategies concerning the personality, innate factors and the individual´s attitude towards the world (enhanced by their experiences and the society where they live).
In other words, the landscape assessment depends on factors that are totally subjective and, therefore, difficult to quantify. So what should I do if I want to measure “what we like” about a certain type of cultural landscape?
This is where the so-called “Affective Computing” pops up, which consists on the study and development of systems and devices able to recognize, interpret and process human emotions.
CARTIF, withinSRURAL project, is applying this set of techniques to obtain the “affection value” of any cultural landscape (“measuring how much you like the landscape”). To this ends, a cognitive system is being developed that on the one hand uses verbal language and facial expressions as input, and on the other hand, certain physiological signals (heart rate, sweating and body temperature while you are immersed into the landscape via virtual reality glasses)
All these inputs are introduced into a neural network previously trained by means of Deep Learning2 techniques to obtain the landscape´s “affection value” as useful output.
The “affection value” is very useful for decision-making by territory managers, for instance, to guide tourism promotion campaigns towards high affection values areas, but with no significant visits number. Also for profiling and segmenting tourists according to the type o landscapes they are most likely to visit, and thus to carry out targeted and more effective promotional campaigns.
It can also be used to know when it is necessary to take corrective measures or at least carry out a stud of causes in case of a tourist interesting area with a large number of visitors has a relative low affection value.
Since the decision-makers need few but very relevant information, as much graphical as possible, all kind of useful data is displayed in the most user-friendly for them y means of geolocated interfaces. Therefore, the system under development incorporates specific modules to show the information already processed, just ready to draw conclusions, which will quickly lead them to objective data-driven decisions upon Data Mining and Big Data techniques.
1 Is the landscape combining natural and cultural heritage. It has been modified by humans to be adapted to people´s needs according to their beliefs, economic activity, and the shaped society. The most obvious examples of these modifications are traditional crops, buildings and infrastructures.
In 2020, the European Commission launched a Research proposal (or “topic”) with a budget of 10 million Euros that aimed at the development of innovative and sustainable mini-hydropower solutions in Central Asia.
What makes this remote part of the world special for the European Commission to fund a project there? Central Asia is a geographic pivot of Eurasia and encompasses the five ex-Soviet republics of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan. It is one of the oldest inhabited areas and as such has witnessed rich culture and traditions such as the ancient Silk Road. Landlocked, it is an area of great energy and mineral resources. Specifically, according to a 2019 Report by the United Nations Industrial Development Organization, Central Asia has the second largest potential for Mini-hydropower generation in the world with 34.4 GW, and it is only behind Eastern Asia (China, Japan, the two Koreas and Mongolia) with 75.4 GW. However, to date, less than 1% of this potential has been exploited, which means that Central Asia is the region in the world with the lowest percentage of SHP development. Therefore, it seems clear that behind this “topic”, it is the Commission´s interest in opening new markets for the European mini-hydropower industry.
What are the main barriers that are preventing the development of the sector in Central Asia? We find a wide range of political, economic, social, technological, legal and environmental implications. There are common problems as the lack of information, the lack of financing from the private sector, or the absence of legal incentives. Moreover, some Central Asian countries have to deal with extreme weather conditions as for example, in high altitude regions where streams are likely to freeze in winter. In addition, it is crucial to consider the concept of a cross-border Water/Food/Energy/Climate nexus with a view to the future in order to avoid ecological disasters such as that of the Aral Sea, which continues to dry up due to unsustainable cotton exploitation.
The Hydro4U project was the winner of this call from the European Commission and began its journey in June 2021 with an expected duration of 5 years. Led by the Technical University of Munich, the rest of the consortium is completed by European turbine manufacturers such as Global Hydro Energy, entities from Central Asia such as the International Water Management Institute or technological centers such as CARTIF, which is leading the replication activities. Within the framework of the project, two new Mini-hydropower plants are being developed with designs adapted to the conditions of the region, and which will radically reduce planning, construction and maintenance costs, without compromising efficiency. The plants will be installed in two selected sites in Uzbekistan and Kyrgyzstan.
As for CARTIF, a key point of the work we are carrying out is the development of a replication guideline tool oriented to future investors or public authorities to support decision-making of new Mini-hydropower projects in Central Asia. The tool will be based on a computational model integrating Geographic Information System (GIS) mapping and statistical data. The tool will be implemented at river basin level, and will be applied in the two main rivers of the region: Syr-Darya and Amu-Darya. The tool will consist on several interactive modules, aiming to (1) visualize the total sustainable hydropower potential and installed capacity, (2) simulate Hydropower generation scenarios considering Water-Food-Energy-Climate Nexus constrains, sustainability of resources and socio-economic impacts and (3) provide technology recommendations as well as lessons learnt related to the implementation of new hydropower projects.
The guideline replication tool will be released by the end of 2025, and in CARTIF we are currently working on defining the sustainable hydropower potential as well as on the Water-Food-Energy-Climate Nexus model at the basin level that will allow us to simulate future generation scenarios sustainable with natural resources.
Stay informed of the progress of the project in the News&Events section of the Hydro4U webiste, as well as on its social netowrks: Twitter and Linkedin.
Researchers are increasingly confronted with situations of “digitalise” something that has not been digitalised before, temperatures, pressures, energy consumes,etc. for these cases we look for measure systems or a sensor in a commercial catalogue: a temperature probe, a pressure switch, a clamp ammeter for measuring an electric current, etc.
Sometimes, we find ourselves in the need of measure “something” for which you can´t find commercial sensors. This can be due to they aren´t common measure needs and there isn´t enough market for these type of sensor or directly, doesn´t exist commercial technical solutions available for different reasons. For example, it could be necessary to measure characteristics such as humidity of solid matter currents, or characteristics only measurable in a quality control laboratory in an indirect way and that needs a high experimentation level.
Also, sometimes, characteristics are required to be measured in very harsh environments due to high temperatures, as it can be melting furnace, or environments with lots of dust that saturate any conventional measure system and it may sometimes be necessary to evaluate a characteristic that is not evenly distributed (for example, quantity of fat in a meat piece, presence of impurities). Other factor to take into account is, that not always possible to be installed a sensor without interferences in the manufacturing process of the material that we want to measure, or the only way is taking a sample to realise an analysis out of the line and obtain a value or characteristic time after, but never in real time.
In these situations, it is necessary to resort to custom-made solutions that we call smart sensors or cognitive sensors. Apart from calling them sound exotic or cool, these are solutions that need to use a series of “conventional” sensors together with software or algorithms, for example, artificial intelligence, that process the measurements returned by these commmercial sensors to try to give as accurate an estimate as possible of the quality we want to measure.
Nowadays we are developing these types of smart sensors for different process industries such as asphalt manufacturing, steel billet and bars or pharmaceutical industry (e.g. pills) in the framework of the European Project CAPRI.
For example, in the manufacture of asphalt, sands of different sizes need to be dried before they are mixed with bitumen. During the continuous drying process of these sands, the finer sand size, called filler, is “released” in the form of dust from larger aggreggates and this dust needs to be industrially vacuumed using what is called a bag filter. Nowadays, the drying and suction of filler is done in a way that ensures that all the filler is extracted. The disadvantage of this process is that it is actually necessary to add additional filler when mixing the dried sands with the bitumen, because the filler improves the cohesion of the mix by filling the gaps between the sand grains. All this drying and complete suction of the filler entails an energy cost that, in order to try to minimise, it would be necessary to have a measure of the filler present in the sand mixture. Today, this measurement is obtained in a punctual way through a granulometric analysis in a laboratory with a sample of the material before drying.
Within CAPRI Project we are working on the complex task of being able to measure the flow of filler sucked in during the drying process. There is no sensor on the market that are guaranteed to measure a large concentration of dust (200,000 mg/m3) in suspension at high temperatures (150-200ºC).
Within the framework of the project, a solution to this problem has been developed, you can consult the laboratory results in the research article recently published in the scientific journal Sensors (“Vibration-Based Smart Sensor for High-Flow Dust Measurement”)
The development of this type of sensors requires various laboratory tests to be carried out under controlled conditions to verify the feasibility of this solution and then, also under laboratory conditions, to carry out calibrated tests to ensure that it is possible to estimate the true flow of filler sucked in during the sand drying process. CAPRI Project has successfully completed the testing of this sensor and others belonging to the manufacture of steel bars and pharmaceutical pills.
The Project in its commitment to the open science initiative promoted by the European Commission has published in its Zenodo channel, different results of these laboratory tests that allow us to corroborate the preliminary success of these sensors pending their validation and testing in the productive areas of the project partners. In the near future we will be able to share the results of the industrial operation of this and other sensors developed in the project.
Co-author
Cristina Vega Martínez. Industrial Engineer. Coordinator at CAPRI H2020 Project
