Measuring and / or control systems for optimizing the environmentally relevant energy consumption in production processes in plants or industrial sites and / or measuring systems for the automated measurement of environmental quantification measurements

Abstract

What is proposed is a control device (10) for optimizing the energy management and energy control of an industrial site (1) and measuring the environmental footprint of the industrial site or plant (1) and / or products manufactured or processed by the industrial site (1), the industrial site (1) including one or more processing units (12) for processing or manufacturing one or more products (2), the control device (10) including measurement devices and sensors (13) for capturing measurement parameters at the processing units (12) and / or environmental parameters associated with the industrial site (1), input / output devices (1011), and transmission lines / networks (1012) for transferring the measured parameters to the control device (1). This can also include different source feedstock scenarios, specific production practices (e.g. fertilizer use), and different environmental impact metrics like water and land use.

Description

[Technical field]

[0001] The present invention relates generally to measurement and optimized control and steering devices that optimize environmentally relevant energy consumption in the production processes of plants or industrial sites by optimizing both electrical and thermal energy in such a way as to achieve a desired overall plant performance. In particular, the present invention improves energy facility efficiency and reduces energy supply costs, CO 2 The present invention relates to an automated measuring and / or control / steering device for optimizing the measuring and steering of a plant with respect to energy consumption in a production process of a plant or industrial site, applicable in technological areas (e.g. production processes), manufacturing (e.g. facilities, plants, process lines) and tertiary areas (e.g. buildings, transport, etc.) where it is desirable to reduce at least one of the following: (carbon dioxide) emissions, water, waste and primary energy consumption. Furthermore, the present invention relates to a control and measuring system aimed at the measurement of environmental quantification measures. [Background technology]

[0002] Carbon dioxide (CO) resulting from human activities, especially industrial production and manufacturing processes. 2 ), methane (CH 4 ), and nitrous oxide (N 2Greenhouse gas emissions, such as CO, are one of the main causes of climate change with implications for food security and safety in terms of impacts on agricultural crops. Greenhouse gas fluxes are responsible for increasing temperatures, which leads to higher drought stress on crops due to increased evapotranspiration combined with a more uneven distribution of precipitation events. In addition, growing economic, social, and environmental challenges are further driving a new paradigm of sustainable development in which competitive sustainable manufacturing (SM) plays a central role. Rising energy and commodity prices, due to resource scarcity, government legislation, and consumer pressure, are driving environmentally conscious business strategies to gain sustainable advantages through effective energy product optimization and efficient resource consumption. Rising energy and labor costs continue to further increase the pressure to innovate. Hence, the need for reduction in energy consumption and greenhouse gas (GHG) emissions, mainly carbon dioxide (CO 2 ) Reducing emissions has become a top global challenge.

[0003] In this context, feed and food production is known to be a major contributor to greenhouse gas emissions, which cause global warming with serious environmental and economic components. In particular, industrial food and feed production processes, raw material processing and related manufacturing operations are energy intensive, and the electricity used also produces CO 2 Energy is often generated by fossil fuels, which are major contributors to emissions, water depletion, and land use. However, enhanced energy management in industrial processes requires robust physical measurement parameter driven monitoring, measurement and modeling, as well as the appropriate selection of Energy Performance Indicators (EnPIs) that provide measurements on the energy performance of a plant, process line or industrial process. Today, an effective Energy Management System (EMS) is recognized as a potential competitive advantage by many industrial sectors because it offers many benefits such as energy consumption and cost reduction, improving and optimizing the environmental impact reduction.

[0004] The food industry is divided into several sectors. Among these, the wheat processing sector is considered as one of the most energy intensive industrial consumers because it requires a high and regular energy supply. In the flour milling industry, electricity accounts for almost 75% of the total energy use and more than 90% of the energy costs, with consumption varying between 361 MJ / t and 1186 MJ / t. Thus, inefficient energy utilization can result in huge economic losses, since excessive energy consumption increases the cost of the goods produced. There have been great efforts in the energy efficiency of the food industry and wheat production. However, most of them are mainly focused on marketing, production planning or product quality. However, the prior art systems for the optimization of energy consumption in this industry do not provide adequate tools for energy management. Some of them are limited to monitor the energy requirements for the operations involved in the processing of wheat, while others try to optimize the process of how to reduce the peak load and the associated costs. Other systems have focused on the recognition of the development of the energy consumption patterns of the various unit operations required for the wheat processing plant. Moreover, in all prior art addressing grinding plants, the EnPI is based on a simple model of energy consumption versus production, without taking into account the variables of the wheat production process that affect energy consumption.

[0005] Many factors affect the energy requirements for wheat raw material conversion. Thus, a system that provides efficient energy management must be able to take into account the correlation between energy consumption and wheat grade, moisture content, feed rate, fast roll speed, roll speed difference and roll gap. Furthermore, since flour depends on proper conditioning to facilitate endosperm and bran separation, many mills add moisture to soften the grain to improve efficiency in terms of the energy required to produce flour. It is clear that the processing of natural resources depends on their composition. It is therefore important that the energy management system is made able to take into account the relationship between energy efficiency and raw material properties. The physical properties of wheat and the technological utilization parameters of the grinding rolls also directly affect the energy consumption of the grinding. However, most of the prior art systems that control plant processes focus on the impact on product quality instead of energy consumption. Thus, these systems typically considered the impact of normal and hard grinding and different conditioning times on wheat flour properties were studied without considering energy consumption.

[0006] It must be noted that, unless one takes into account the wheat processing sector mentioned above, feed and food production in general can contribute substantially to greenhouse gas emissions. For example, livestock have a large share, resulting in 18% of global greenhouse gas emissions. Then there are dairy products (cheese: 8.8 kg CO 2 e / kg cheese) and meat products (beef: 29.0 kg CO 2 Foods with animal protein components, such as beef (e / kg beef), show high greenhouse gas emissions. However, apart from livestock products, vegetables and cereals (tomatoes: 5.3 kg CO 2 e / kg tomato; rice: 1.2kg CO 2 e / kg rice) can also generate high emissions. Replacing animal with plant ingredients in food can reduce greenhouse gas emissions. Grain legumes such as peas or beans can be used as such plant replacement ingredients. 0.49 kg CO 2Grain legumes, with a carbon footprint of 10 ... However, while breeding techniques can help achieve this goal, they have only been satisfied with limited success. For example, to compare the environmental impacts of producing 1 kg of edible protein from beans, almonds, eggs, chicken, and beef, input parameter values ​​must be measured, including, for example, land and water to raise the animals and grow the animal feed, total fuel, and total fertilizer, as well as pesticides to grow the plant consumables, animal feed, and animal waste. As a result, producing 1 kg of protein from beans required approximately 18 times less land, 10 times less water, 9 times less fuel, 12 times less fertilizer, and 10 times less pesticides compared to producing 1 kg of protein from beef. Compared to producing 1 kg of protein from chicken and eggs, beef generated 5 to 6 times more waste (manure) to produce 1 kg of protein. In summary, the replacement of beef with beans in dietary patterns should also be encouraged to significantly reduce the global environmental footprint and reduce the prevalence of non-communicable chronic diseases.

[0007] Not all emissions of all greenhouse gases have the same effect. The different impacts of various greenhouse gases are related to the global warming potential (GWP), which is the heat absorbed by greenhouse gases in the atmosphere, compared to the global warming potential (GWP) of the same mass of carbon dioxide (CO 2 GWP is measured as a multiple of the heat absorbed by a given CO 2 For other gases, the GWP depends on the gas and the time frame. Carbon dioxide is used as a general standard; it has a GWP of 1 regardless of the time period used. 2 Emissions will cause atmospheric CO2 to accumulate for thousands of years. 2 To compare the impacts of various greenhouse gases, the carbon dioxide equivalent (CO 2 e(CO 2 eq or CO 2 GWP (Gross Weighted Average), also called GWP-e), is defined from GWP. It is measured in weight or concentration. For any amount of any gas, it is the amount of CO that will warm the earth as much as that amount of that gas. 2 It is calculated as the amount of CO2 emitted by a gas times its GWP. Thus, it provides a common scale for measuring the climate impact of different gases. It is calculated as the amount of CO2 emitted by a gas times its GWP. For example, if a gas has a GWP of 100, then 2 tonnes of that gas will have the same impact on the climate as 200 tonnes of CO2. 2 e, and 1 part per million of that gas in the atmosphere is equal to 100 parts per million of CO 2 Greenhouse gases (GHGs) are gases that absorb and emit radiant energy in the thermal infrared range, resulting in the greenhouse effect. The main greenhouse gases in the Earth's atmosphere are water vapor (H 2 O), carbon dioxide (CO 2 ), methane (CH 4 ), nitrous oxide (N 2 O, i.e. laughing gas), ozone (O 3 ) Without greenhouse gases, the average temperature on the Earth's surface would be about -18 °C instead of the current average of 15 °C.

[0008] Prior art US Pat. No. 6,299,366 shows a system for controlling, monitoring, and recording the use of incoming chemicals and power, and the emissions of an electronic device manufacturing system. According to US Pat. No. 6,299,366, the system is focused on so-called sub-fab equipment, which typically does not have monitoring data for energy consumption and / or energy savings. Sub-fab equipment as defined by US Pat. No. 6,299,366 can include auxiliary devices, such as mitigation tools, AC power distribution, primary vacuum pumps, standby vacuum pumps, water pumps, chillers, heat exchangers, process cooling water supply and delivery systems, electrical power supply and delivery systems, inert gas dumps, valves, device controllers, clean dry air supply and delivery systems, ambient air supply and delivery systems, inert gas supply and delivery systems, fuel supply and delivery systems, touch screens, process logic controllers, reagent supply and delivery systems, etc. Thus, US Pat. No. 6,299,366 proposed that the energy usage of the sub-fab equipment be monitored by an integrated sub-fab system. The integrated sub-fab system allows the system to capture different depths of energy saving modes such as idle (shallow energy saving where production equipment can return to normal production in seconds without impacting quality or throughput), sleep (deeper energy saving where production equipment can recover in minutes), or hibernate (where production equipment can take hours to recover without impacting quality or throughput). The system can monitor and display all gas emissions within the sub-fab and can measure CO 2 SemiS23 method reporting of equivalent emissions is also possible. The system can monitor outflow process gases and energy usage from specific process tools and sub-fab equipment. Thus, in principle, the '610 system proposes separate measurements and monitoring at different sub-fab equipment to capture or measure an overall monitoring and recording of the complete fab system's incoming chemical and power usage. Summary of the Invention [Problem to be solved by the invention]

[0009] It is an object of the present invention to provide a measurement and / or control system and method that provides automated measurement and / or optimization of energy handling and / or minimization of overall energy consumption in a production process of a plant or industrial site. For example, the present invention provides a method for measuring, among other things, quantified CO 2 It is an object of the present invention to provide a system and method for an intelligent control and / or measurement system or device with all the required data to enable automated and certified environmental quantification measurements by providing e-measurements. Furthermore, the system must be easily scalable and integrable to any kind of third party competitor / partner equipment. The system must be able to automatically collect the relevant data and process the data to generate site environmental footprint and / or product environmental intensity and impact intensity measurements. This may include measuring parameter values ​​from the raw material field / mine / value chain, such as the highest yielding wheat of a particular emission processed into flour. Furthermore, it must be able to automatically or at least semi-automatically provide improved quantification measurements by considering and mutually weighting the measured cost parameters, production or manufacturing measurements, and impact parameters. Thus, the present invention also goes beyond the technical approach as provided by the prior art systems in that the inventive measurement and control optimization system provides a technical structure that automatically enables measurement and contribution by automated control adaptive optimization and steering possible raw material footprint impacts. [Means for solving the problem]

[0010] According to the invention, these objects are achieved in particular by means of the features of the independent claims, in addition, further advantageous embodiments can be derived from the dependent claims and the associated description.

[0011] According to the present invention, the above mentioned objectives related to energy consumption control, measurement and monitoring of an industrial site or plant and measurement of the environmental footprint of an industrial site / plant and / or products manufactured or processed by the industrial site by a control device are in particular achieved by providing a control device for controlling an environmental footprint of the industrial site / plant, the control device comprising an input section including measuring devices and sensors for capturing and / or monitoring and / or recording predefined measurement parameters via data flow paths of the measuring devices and sensors in the processing units and / or environmental measurement parameters associated with the industrial site, an input section including an input / output interface and a data transmission line / network for transferring the measured parameters to the control device, and controlling the environmental footprint of the industrial site based on the monitored measurement parameter value settings. and optimizing the control, steering and / or monitoring of energy consumption associated with the industrial site or plant, in which the input is configured to capture and / or monitor and / or record predefined measurement parameters that trigger in a data path of measuring devices and sensors for generation of value settings for optimizing the control and steering of the energy management of the industrial site, in which the monitored measurement parameters include a parameter vector, the parameter values ​​of which are a time series of parameter values ​​that can change over a predefined operating period and / or a parameter scalar, the parameter values ​​of which do not change over the operating period, and structural parameters, the structural parameter values ​​being representative of structural features of the industrial site or plant. 2e, moisture depletion, and generation of product environmental quantification measurements based on measured parameters that measure land use impact intensity / environmental impact intensity values ​​of products processed or manufactured by the industrial site, in which emission factors are classified and monitored by life cycle stages, and the emission factors are classified (i) for discharged raw materials, (ii) for discharged waste including emission factors for energy emissions and emission factors for waste emissions, and (iii) for transportation emissions, for waste materials and production cycle materials, the control device includes a material detector that detects and / or determines the materials of the product according to the weight of each material, the environmental impact measurement, and an analysis of each material and product process, the product includes a plurality of materials, and the material detector further determines a weight ratio that is the ratio of the weight of each material to the total weight of the product according to the gravimetric analysis of each material, e.g., CO2 of each material and production process. 2 Total CO emissions from the product over its life cycle according to e-measurement 2 CO emitted from each material relative to e 2 e ratio (e.g., CO 2 In determining the environmental measurement ratio (e.g., by measuring the CO e value) of the products processed or manufactured by the industrial site based on the monitored measurement parameters, 2This is achieved in that environmental product quantification measurements are generated that measure the environmental impact intensity or strength (including e-impact intensity) and / or industrial site environmental quantification measurements are generated that measure the quantified environmental footprint of the industrial site or plant. The inventive system is enabled to provide environmental impact intensity measurement / prediction / optimization with or without automated and / or optimized environmentally related energy consumption control. The control device can be realized as an integrated part of the industrial site / or plant, thus providing the industrial site / or plant with autonomous and automatic electronic steering of the industrial site / or plant using e.g. PLC interfaces to the processing units of the industrial site / or plant. In particular, the measurement device and the sensory device can be an integrated part of the measurement and control device, thus the measurement and control device includes said measurement device and sensory device as part of its device structure.

[0012] In a variant of the embodiment, the measurement and / or control device can provide a dynamically adapted line configuration based on, for example, optimized improvement measures. 2Based on the product impact intensity quantification measurements and / or the measured industrial site environmental impact intensity quantification measurements (including the measured environmental footprint quantification measurements) the measurement and / or control and / or steering device can dynamically change the operational parameters of the industrial site or plant adapted to the operation of the processing units of the industrial site or plant, for example, until a minimum measured environmental footprint of the industrial site or plant and / or the product processed by the industrial site or plant is reached. The operational parameters of the industrial site or plant can be dynamically changed, for example, by applying simulated annealing to the parameter space of the operational parameters to change the operational parameters. The operational parameters of the industrial site or plant can be dynamically changed, for example, by changing at least two of the operational parameters in the parameter space of the operational parameters and by applying a first deviation based on Box-Wilson data processing to minimize the measured environmental footprint of the product and / or the industrial site. At least two of the operational parameters in the parameter space can be changed probabilistically or according to a minimum distance, for example, until an optimized environmental footprint measurement is measured. At least two of the operational parameters within the parameter space can be electronically varied, for example, until a predefined threshold of the measured environmental footprint is triggered.

[0013] The present invention, among other things, allows for the integration of competing and / or partner devices as well (e.g., CO 2The system has the advantage of being able to provide an intelligent control system with all the data necessary to provide an automated and certified environmental impact intensity quantification (including CO2 quantification). The system automatically collects the required data, processes the measured and captured data and generates quantitative site environmental footprint measurements. Furthermore, the system can process the captured and measured data and generate product and / or plant and / or industrial site environmental impact intensity and / or strength. Furthermore, the system can automatically provide appropriate remediation measures taking into account costs and / or measures and / or impacts ... 2 Added value can be created through the combination of e-quantification with process and sustainability knowledge. Furthermore, third-party certification can be provided, e.g. ISO certification. The system can provide the customer / user with controlled and secure access to the certificate, e.g. based on an identification number or other authentication mechanism. The system can provide dynamic line configurations for industrial sites to optimize energy management. In addition, the system can be linked in new and inventive ways to raw material databases, logistics and critical process parameters. The system can provide CO 2 Quality / CO is a unique and protected label that certifies the e-certification 2e. In particular, it allows certified measurements according to any technical requirements or regulatory standards, such as those given by the standards of the Greenhouse Gas Protocol initiated by the World Resources Institute (WRI) and the World Economic Council for Sustainable Development (WBCSD). Finally, the system can integrate blockchain technology to provide said authentication or trusted lawyer interaction. The integration of blockchain technology allows the implementation of a controlled multi-layer trust structure to make the inventive control system operate as a trust system. In a variant of this embodiment, the design of the blockchain technology used allows for three interacting trust layers, namely how actors interact with each other and how much information they need, the trusted information, e.g. CO 2 a social layer that captures how actors determine what form is necessary to be able to trust and take action based on e-authentication; a records or data layer that supplies the information that actors have determined they need to obtain from the control system to give them the confidence to act; and a records or data layer that captures the information actors interact with and obtains information about those interactions as fraud-proof, undeniable proof of fact about their actions, i.e., CO. 2 This allows the incorporation of a technical layer that captures the technical means of generating, storing and acquiring the data as measurements. The main focus of the present invention is on the recording layer, but this layer and the 2 In order to understand the means by which environmental certification, including e-certification, can be effectively managed by blockchain-based records, it is important to understand the other two layers and how they interact with each other in the design and operation of blockchain systems. [Brief description of the drawings]

[0014] The invention will now be explained in more detail, and by way of example only, with reference to the drawings, in which:

[0015] [Figure 1] 1 shows a block diagram that illustrates in a schematic way a punctual measuring and / or control device 10 for optimizing the energy consumption control, steering and monitoring of an industrial site or plant 1 and / or measuring the environmental footprint of the industrial site or plant 1 and / or products 2 manufactured or processed by the industrial site 1. The industrial site 1 comprises one or more processing units 12 for processing or manufacturing one or more products 2, the control device 10 comprising an input section 101 with measuring devices and sensors 13 for capturing measurement parameters in the processing units 12 and / or environmental measurement parameters related to the industrial site 1, an input / output interface 1011 and a data transmission line / network 1012 for transferring the measured parameters to the control device 10.

[0016] [Diagram 2] FIG. 2 shows a block diagram that illustrates a schematic example PFD for aluminum die casting, where the block marked with "T" indicates transport and the other blocks indicate processes. Reference numbers in circles indicate calculation and monitoring references. Processes are given in blue boxes while transports are given in yellow boxes. The rounded boxes indicate processes in cells, i.e. die casting machines. Table 1 below shows an example list and classification of raw materials, waste produced and used energy generating associated emission factors for each life cycle phase of the die casting process. FIGS. 2-8 are based on an example product evaluation in a die casting process by the inventive system 1.

[0017] [Table 1]

[0018] [Diagram 3] FIG. 3 shows a diagram that generally illustrates an exemplary CO2e distribution for a 1 kg aluminum die-cast part.

[0019] [Figure 4] Figure 4 shows a diagram that illustrates a schematic of an exemplary table with aluminum emission factors. It can be seen in Figure 4 that aluminum sourcing can significantly impact the final footprint.

[0020] [Diagram 5] 5 shows a diagram that generally illustrates measured and / or projected savings in an exemplary plant cell process performed by a die casting machine, including, among others, (i) holding and dosing, (ii) atomization, (iii) casting, (iv) thermal control, (v) extraction, (vi) cooling water system, (vii) cooling, and (viii) trimming.

[0021] [Figure 6] FIG. 6 shows a diagram that generally illustrates exemplary contributions to manufacturing emissions for waste disposal.

[0022] [Figure 7] FIG. 7 shows a diagram that illustrates a schematic of exemplary contributions to manufacturing emissions for energy.

[0023] [Figure 8] FIG. 8 shows a diagram that generally illustrates measured and / or projected savings in an exemplary customer value chain.

[0024] [Figure 9] FIG. 9 shows a diagram that illustrates a schematic of an exemplary CO2 distribution from narrow to wider ranges (ranges 1-3).

[0025] [Figure 10] Figure 10 shows a diagram that illustrates a schematic example breakdown of on-site emissions. Figure 10 is based on an exemplary on-site evaluation of a die casting example with the inventive system 1.

[0026] [Figure 11]FIG. 11 shows a diagram that illustrates an exemplary dependence from the choice of power source for CO2 emissions. Switching to green electricity (e.g. solar panels, see FIG. 11) can help to further reduce emissions. For example, photovoltaics can help to avoid emissions. This example in FIG. 11 uses electricity from a carbon-free source. This saves 2,500 tons of CO2 per year. This is a 5% saving in total on-site emissions compared to consuming electricity from the standard Swiss grid.

[0027] [Figure 12] Figure 12 shows a diagram that diagrammatically illustrates an exemplary process flow in flour production, where the blocks marked with "T" indicate transport and other blocks indicate processes. Reference numbers in circles indicate calculation and monitoring references. Processes are given in blue boxes and transports are given in yellow boxes. Figure 12 is based on an exemplary product evaluation in the example of milling by the inventive system 1.

[0028] [Figure 13] Figure 13 shows a diagram that illustrates a schematic example of an exemplary CO2e distribution for one ton of flour with transportation emissions in the milling example. Figure 13 is based on an exemplary product evaluation in the milling example with the inventive system 1.

[0029] [Figure 14] Figure 14 shows a diagram that illustrates a schematic example implementation of the definition and reporting of CO2 emissions. Figures 14-16 are based on an exemplary field evaluation in the example of comminution with the inventive system 1.

[0030] [Figure 15] 15 shows a diagram that illustrates a schematic of an exemplary result for an exemplary field evaluation with specific power emission factors. FIG. 15 is based on an exemplary field evaluation in the example of grinding with the inventive system 1.

[0031] [Figure 16]Fig. 16 shows a diagram that illustrates in a schematic way an exemplary semi-dynamic modeling or simulation structure that can simulate different scenarios, e.g., different raw material sources, transportation routes, etc. In particular, Fig. 16 shows a dynamic evaluation from plant or farm to distribution. Fig. 16 is based on an exemplary field evaluation in the example of comminution by the inventive system 1.

[0032] [Figure 17] 17-19 show diagrams / online dashboards that diagrammatically illustrate exemplary CO2e quantification for an example flour milling site and rice customer end product, respectively. [Figure 18] Figure 18 shows a diagram / online dashboard that illustrates in a schematic manner exemplary CO2e quantification for an example flour milling site and each of the rice customer end products. The example in Figure 18 includes data collected directly at the farm / field level. [Figure 19] Figure 19 shows a diagram / online dashboard that illustrates in a schematic manner exemplary CO2e quantification for an example flour milling site and each of the rice customer end products. The example in Figure 19 includes data collected directly at the farm / field level.

[0033] [Figure 20] Figure 20 shows how the impacts on water depletion, water scarcity, and land use can be quantified for different scenarios, depending on agricultural practices, crop and processing yields. Figure 20 thus illustrates the water and land use impacts.

[0034] [Figure 21] Figure 21 shows an example of how this solution can be used to realise a complete sustainability journey by measuring the current situation, reducing environmental impacts and only at the end looking at how to offset remaining emissions. The tool makes it possible to accompany clients through a comprehensive impact assessment, including multiple environmental metrics such as land use and water.

[0035] [Figure 22] Figure 22 shows an example of a tailored reduction plan for a bakery customer. The impact of the action plan is directly quantified so that improvements can be demonstrated and communicated. The tools and services provided help customers develop action plans and provide the solutions needed to achieve their goals.

[0036] [Diagram 23] FIG. 23 shows a US example of CO2e distribution of barley production (as a breakdown of the geo-footprint) with barley emissions in kgCO2e / kgbarley.

[0037] [Figure 24] FIG. 24 shows an example where different configuration / impact parameters can be evaluated and monitored by the device 10 to create different scenarios and final certifiable measurements and evaluations. As an embodiment variant, this can be linked to an action plan adjusted and dynamically generated based on the measured parameters, for example to reduce the environmental impact with specific actions. The example of FIG. 24 concerns rice, but it can be applied and adapted to any type of end product, food or non-food. FIG. 24 exemplarily shows that apart from the measured parameter values ​​of the measuring devices and sensors 13 of the device 10, the device 10 can receive additional data from different sources, for example to support a luminescence quantification step for a given process. This can also be realized by combining manual data input from a user, computational models with a database of scientific values, and data from a cloud connected to a specific processing / logistics stage in the value chain. Thus, the digital platform can provide an integrated B2B digital exchange platform or structure.

[0038] [Diagram 25]Figure 25 exemplarily illustrates how the parameters can be evaluated against different parameters such as land use, water, etc. The dynamic structure can have the capability of, for example, the life cycle of a product from cradle to grave.

[0039] [Figure 26] Figure 26 shows an exemplary direct emissions for an example plant for an example rice. Thus, Figure 26 shows an exemplary on-site assessment using global emission factors.

[0040] [Figure 27] Figure 27 shows an example of the CO2 distribution for 1 ton of milled rice that is not parboiled during production (see Figure 26). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0041] FIG. 1 shows a schematic diagram for a possible implementation of embodiments of the inventive method and system, in particular for the energy consumption control, the optimized steering and dynamic adaptation and monitoring of an industrial site or plant 1 and for the (quantified CO 21 shows a schematic architecture for an inventive measuring and control device 10 (also called dynamic environmental quantification measuring system 10) for optimizing the measurement of an environmental footprint (as an embodiment variant that can also be realized as a footprint). The environmental footprint can include not only measurements of manufacturing or processing process measurands provided at a specific site or plant or farm 1, but also measurements covering the complete environmental impacts of the production chain of an industrial product 2 from, for example, sowing, cropping, raw material processing, transport, industrial processing or manufacturing to delivery transport, thus covering all aspects of the production of an industrial product 2, including transport and packaging etc. In the latter embodiment variant of such measurements, the term "industrial site or plant 1" is used in a broader definition, including all technological means for the processing and provision of an industrial product, the extraction of raw materials or the cultivation into a final product 2. However, the measurement of the environmental footprint can also be limited to a specific industrial plant 1, production line 11 or production process 113, providing only partial steps in the overall industrial production chain of a product 2. The industrial site 1 may for example comprise at least one industrial plant 1 and / or processing line 11 and / or manufacturing facility / equipment 12. The industrial site 1 comprises one or more processing units 12 for processing or manufacturing one or more products 2. The measurement and control device 10 comprises an input 101 comprising measuring devices and sensors 13 for capturing measurement parameters in the processing units 12 and / or environmental measurement parameters related to the industrial site 1, an input / output interface 1011 and a data transmission line / network 1012 for transferring the measured parameters to the control device 10. The industrial site 1 may further comprise one or more processing lines 11 comprising at least one processing unit 12 for processing or manufacturing the products 2. It is important to note that the optimization of the energy consumption of the industrial site 1 and the measurement of the environmental footprint of the respective industrial site 1 and / or the products 2 manufactured or processed by the industrial site 1 may be decoupled from technological aspects.For example, if there is mitigated procurement of green energy in overall energy consumption, CO. 2 The reduction can be decoupled from the energy reduction. Thus, for the expert system aspects of the present invention, the measured environmental footprint or CO 2 The optimization of the energy consumption by footprint and suitable adaptation and steering, in particular the dynamic adaptation of the operating parameters of the process line 11 or the industrial plant 1, does not necessarily have a direct relationship.

[0042] The dynamic environmental quantification system and control device 10 can be built on an environmental quantification assessment (along with the GHG (Green House Gas) protocol). It takes all activity inputs (e.g. kwh / t, t / t of raw fertilizer) and converts them into specific emission factors (e.g. t CO 2 e / t wheat).

[0043] The dynamic monitoring and steering / control device 10 allows different entries for each activity. It can thus compare the environmental impact of different options (e.g., different agricultural activities, energy sources, transport routes, etc.). The dynamic device 10 can include a secure digital network, where the network is based on a blockchain-based structure that allows users to share data in an immutable and secure way within the digital network. The digital network provides the means for participants to share data on the carbon footprint for a given process stage in real time. Apart from the measured parameter values ​​of the measuring devices and sensors 13 of the device 10, the device 10 can for example receive additional data from different sources to assist the emission quantification step for a given process. This can also be achieved by linking manual data input from the user, computational models with a database of scientific values, and data from a cloud connected to a specific processing / logistics stage in the value chain. Thus, the digital platform can provide an integrated B2B digital exchange platform or structure.

[0044] Different configuration / impact parameters can be evaluated and monitored by the device 10 to create different scenarios and verifiable final measurements and evaluations. In a variation of the embodiment, this can be linked to a tailored and dynamically generated action plan based on the measurement parameters, for example, to reduce the environmental impact with specific actions. Figure 24 shows an example of rice, but it can be applied and adapted to any type of end product, food or non-food.

[0045] In a further embodiment variant, the setting of the parameters can be realized dynamically. Table 1 below shows examples of parameters that can be dynamically adapted and manipulated by the measurement and control device 10.

[0046] [Table 2]

[0047] These parameters can be evaluated against different parameters such as land use, water, etc. The dynamic structure can have the capacity of the product's life cycle from cradle to grave as shown in Figure 25. Figure 26 illustrates the direct emissions for an example rice factory. Thus, Figure 26 shows an exemplary site evaluation using global emission factors. Figure 27 shows the CO2 emissions for 1 ton of milled rice that is not parboiled during production. 2 An example of the distribution is shown below.

[0048] The control device 10 may include at least one programmable logic controller (PLC) or programmable controller associated with the industrial site, for example as an automation controller adapted for controlling a manufacturing process or a product processing process in the industrial site, and the PLC input / output devices (I / O) are realized as internal integration with a data processor or are rack-mounted as a modular device with I / O devices. The PLC of the industrial site may be connected through a data transmission network 4 to a supervisory control and data acquisition (SCADA) system of the control device, for example providing programming of the processing units of the industrial site and process fault diagnosis.

[0049] The input unit 101 captures and / or monitors and / or records predetermined measurement parameters 134 that trigger within the data path of the measuring devices and sensors 13 to generate value settings for optimizing the control and steering of the energy management of the industrial site 1.

[0050] The monitored measurement parameters 134 include parameter vectors, whose parameter values ​​are a time series of parameter values ​​that can change over a given operating period, and / or parameter scalars, whose parameter values ​​do not change over the operating period, and structural parameters, whose structural parameter values ​​represent structural characteristics of the industrial site 1.

[0051] Based on the monitored measurement parameters 134, product environmental quantification measurements 21 are generated to quantify (e.g., CO 2 e) and / or generated by measuring the environmental intensity 22 (e.g., CO 2 The industrial site environmental quantification measurements 141 at (e) are generated by measuring the quantified environmental footprint 14 of the industrial site or plant 1. 2 The quantification measurements 21 may be, for example, measured by the control device 10 or a dedicated CO 2 e quantification module 107. As used herein, the term "module" refers to logic embodied as hardware or firmware, or to a collection of software instructions written in a programming language and implemented on (or as) hardware to operate and operate the respective hardware component, e.g., as a processor. In one embodiment, the programming language may be Java, C, or assembly. One or more software instructions in a module may be embedded in firmware, such as in an EPROM. The modules described herein may be implemented as either software and / or hardware modules and may be stored on any type of non-transitory computer-readable storage medium or other storage device. Some non-limiting examples of non-transitory computer-readable storage media include CDs, DVDs, flash memory, and hard disk drives. (See, e.g., CO 2e) and / or the generated product environmental impact quantification measurements 211 (e.g., CO 2 Based on the generated industrial site environmental impact quantification measurements 141 (given in e) the control device 10 can provide for example optimized improvement measures and possible improvement measures by mutual weighting influence of different cost parameters. The control device 10 can for example provide a dynamically adapted line configuration based on the optimized improvement measures.

[0052] The control device 10 may further include a carbon footprint inventory system 108. The carbon footprint inventory system 108 may further include an interface 1081 and / or a data capture module 1082, a configuration module 1083, a selection module 1084, a material detector 1085, a notification module 1086, a data processing module 1087, a display module 1088, and a verification module 1089. The modules 1081-1089 may include computerized instructions in the form of one or more program codes stored in a storage device and executed by at least one processor. In one embodiment, the storage device may be an internal storage system, such as a random access memory (RAM) for temporary storage of information and / or a read-only memory (ROM) for permanent storage of information. In some embodiments, the storage device may be an external storage system, such as an external hard disk, a storage card, or a data storage medium. The interface receives an inventory procedure for a product or an industrial plant / industrial site, for example selected via a graphical user interface (GUI), and executes the inventory process for the product or industrial plant / industrial site. The inventory procedure may include, for example, a first inventory of a product or an industrial plant / industrial site, a reference template inventory, and / or a historical reference inventory. When the user selects the first inventory (e.g., by selecting the first inventory displayed on the display screen using a mouse, keyboard, and / or touch screen), the first setting module may set, for example, standard units and parameters of the inventory process, and receive, for example, standard units such as quality units and volume units, as well as parameters such as life cycle assessment (LCA) parameters and GWP parameters to be input into the inventory procedure. When the user selects the reference template inventory, the interface receives the template selected by the user. Different industries may apply different templates.The interface loads standard units and parameters of the reference template stock, for example, from a storage device, to provide various reference selections to the user in the inventory process. When the user selects the historical reference stock, the interface receives the historical reference stock and inventory structure selected by the user. The interface copies the standard units and parameters of the historical reference stock and inventory structure for approval by the user and / or provides the same reference selection as a predefined or starting setting. The first setting module sets the inventory target of the carbon footprint inventory of the product. The inventory target can include, for example, an inventory project, a specific inventory standard, the organization of the product or industrial plant / industrial site, and the inventory period. For example, in FIG. 2, the inventory project is "Alloy Manufacturing" and one of the inventory standards is shown by and given by the structure of "Carat 400 Cell", i.e., a die casting machine, and the inventory target can be, for example, (i) the CO2 of the alloy or manufacturing site or the entire manufacturing process. 2 (ii) measuring the e-footprint; 2 (iii) optimization of the e-footprint, or (iv) optimization of the energy consumption of the manufacturing process of the alloy. Finally, for example, the organization may be a steel company. A particular product on the manufacturing floor may be selected by the selection module according to, for example, an inventory target, and load the material data of the product. For example, the selection module may select a particular alloy as the product, for example, according to a user request. The selection module loads the material data of the product from a dedicated database. The material data may include a list of materials in the product and, in association with each material, e.g., the vendor and / or material characteristics, e.g., weight / composition / properties, etc. All materials of the product may be displayed by the selection module display on the display device according to, for example, a tree diagram or other suitable graphical representation. The selection module may further load an image of the product for reference. The material detector 1085 may, for example, measure the weight of each material and the CO 2 e-characteristics based CO 2The material detector 1085 electronically detects and / or determines the material of the product according to the e-analysis. The product 2 can include a number of different materials 214, and the weight and / or gravimetric properties (such as, for example, its molecular weight) of each material 2141-214i can be different. The material detector 1085 can determine a weight ratio 214i2, which is the ratio 214i2 of the weight 214i1 of each material 214i1 to the total weight of the product 2 according to the gravimetric analysis of each material 2141-214i. The material detector 1085 selects the material 2141-214i with a larger weight ratio to avoid wasting time on the materials 2141-214i with a smaller or less important weight ratio. The material detector 1085 can perform the same steps for a manufacturing cycle, for example, in situ. The material detector 1085 can determine the CO of each material 2141-214i. 2 Total CO emissions from the product during its life cycle according to analysis and manufacturing process 2 CO emitted from each material 2141-214i for e 2 e ratio is 214i3 CO 2 Finally, the notification module 1086 may generate appropriate notifications to vendors of materials participating in the carbon footprint inventory if the required data is not available, and may notify the vendors of the CO2 emissions of the materials 214. 2 Regarding the materials 2141-214i used in the manufacturing process, the materials 2141-214i may include more relevant or less relevant materials 2141-214i, and the more relevant materials 2141-214i may be the materials that are more relevant than the CO 2 e ratio reaches, for example, 1% greater than the less relevant materials 2141-214i. 2 e ratio 214i3 is the total CO emitted by product 2 during its life cycle 2 CO emitted from each material 2141-214i for e 2 The priority of the more relevant materials 2141-214i is higher than the priority of the less relevant materials 2141-214i. Thus, the material 214 has a larger CO2 The preference for materials 2141-214i having e ratio 214i3 is smaller CO 2 e ratio 214i3 has a higher priority than the materials 2141 to 214i.

[0053] The control device 10 determines the CO2 emissions of the product or the industrial plant / industrial site 1 according to the conditions and characteristic parameters of the setup of the process line 11 and / or the processing unit 12 of the carbon footprint inventory and / or according to the priority of the materials used. 2 The control device 10 controls the CO2 emission of the product or the industrial plant / site. 2 The uncertainties or imponderables of e are generated according to a generative structure for generating such uncertainties or imponderables. This structure can for example comprise machine learning-based or artificial intelligence-based units that are trained on historical data of the optimized running processing unit 12. The generative structure for generating the carbon footprint can for example be a set of units that estimate the amount of CO2 released during the life cycle of the product 2 or the industrial plant / industrial site 1. 2 Multiplying activity level data in the life cycle of a product or industrial plant / site by an emission factor to obtain e, or determining whether CO 2 The activity level data at a certain stage of the life cycle of the product 2 or industrial plant / industrial site 1 may be multiplied by an emission factor to obtain e. The activity level data includes material activity level data, power activity level data, and waste activity level data. The units of the activity level data may be, for example, kilograms, cubic meters, kilowatts, kilometers. The emission factor is the CO2 equivalent of the activity level data in each unit. 2 For example, for a particular product, the activity level data, the power activity level data, and the waste activity level data for the material or processing unit 12 are all 15 cubic meters, and the CO 2If e is 0.1 kilograms, then the CO2 emissions of product 2 in its life cycle 2 e is 1.5 kilograms, the result of multiplying 15 by 0.1. CO 2 Creating uncertainty about e is a CO 2 Taking into account any uncertainties in the results of the generation of e-values ​​and minimizing the impact of such uncertainties, 2 The aim of the project is to increase the confidence in the results of the generation of e-values. To generate such uncertainties, for example, Monte Carlo simulations can be used. Finally, the display module can be used to display, for example, the CO 2 The display module can, for example, combine the inventory report with a process chart for each stage in the life cycle of the product or the industrial plant / industrial site or process line 11 and / or the processing unit 12 and display the inventory report and the process chart on the display device. The process chart can, for example, 2 The system can include CO measurements and any uncertainties corresponding to each stage in the life cycle of the product or industrial plant / site. 2 The present invention can be implemented to generate a CO 2 It should be noted that although CO2 emissions and / or energy consumption are used in the examples, the output parameters of the control device 10 may convey other information. Most emissions can be calculated by applying accepted coefficients. 2 e-e emissions, but virtually any resource use by an organization or industry can be converted into CO 2can also be converted into e-emissions because every resource can be associated with the amount of energy used to create the resource, consume the resource, and dispose of any resource waste. For example, the amount of air travel or paper use by an employee can be converted into e-emissions. 2 e-emissions.

[0054] The organization shall report future emissions over a defined time period, e.g., 2020, based on the CO2 emissions forecast. 2 A target level for the control device 10 can be input, such as an e-level. The target level is typically a line that may increase, decrease, or remain unchanged over time. Typically, the organization's target for emissions is lower than an extrapolated estimated future emissions (baseline emissions) determined by the control device 10, where the baseline emissions are the predicted future emissions assuming no strategies to reduce emissions are implemented. For example, the control device 10 can determine that the organization's future emissions will increase by 10% per year due to the organization's expected growth.

[0055] The control device 10 can create a graphical representation as a chart showing the past, current and projected baseline emissions over a defined time period, such as a yearly period, along with a goal line. The baseline emissions and the goal lines usually diverge to form a wedge-shaped gap. The organization must then devise a way to close the gap using one or more strategies. These strategies may include, for example, progressively adapting or updating or optimizing the process units 12, using other energy resources, using other materials in the production process, changing the means or methods or structures of transportation, reducing employee travel, replacing light bulbs with LEDs, using more efficient windows, using green power sources, etc. Each strategy can be associated with a different implementation time. The strategies may be generated as an expert device by the control device 10 acting as an expert system. Again, the control device 10 can provide relevant information about each unit of the industrial site / plant 1 related to environmental impacts. Some of the information may relate to resource consumption of the industrial site 1, such as the type of energy used (e.g., electricity, natural gas, diesel, oil, coal, etc.), the amount of energy used (e.g., kwh, gallons, etc.), the date of energy used, the cost of energy used, air travel, lighting usage, type / amount of product produced and type / amount of emissions, efficiency, waste, water usage, raw input product usage (e.g., paper, metal, etc.), the cost of various related resources, and other types of data related to resource consumption. The control device 10 may store the individual resource consumption items as resource consumption items for the industrial site 10 in the carbon footprint inventory system 108. Some of the information may also relate to demographic characteristics of the organizational unit, such as facility area (e.g., square feet), facility revenue, facility production units, facility type (e.g., office, manufacturing, etc.), facility age, facility hours of operation, facility number of employees, facility HVAC type, facility location, and other types of data related to demographics.

[0056] When the resource consumption of the target unit / facility is not available, the control device can estimate the resource consumption, for example, based on comparable units / facilities within the entity or from a database containing data or historical data from comparable units / facilities of other industrial sites 1 outside the entity. The control device executes a measurement generation structure and matches comparable facilities based on their demographic data in a database or carbon footprint inventory system 108. The control device can then automatically select comparable facilities and determine resource consumption items of the selected comparable facilities from the database. The control device can then select a particular resource consumption item, such as a processing unit 12, determine the measured resource consumption of the target facility, and determine the environmental impact measurement from the measurement. Any report listing an estimated resource consumption or environmental impact measurement designates the value as an estimate.

[0057] CO2 of product 2 processed or manufactured by industrial site 1 2 Product CO based on monitored measurement parameters 134 measuring e intensity 22 2For the generation of quantitative measurements 211, the emission factors can be classified and monitored, for example, by life cycle stage, where the classification of emission factors includes: (a) for the discharged raw materials, acids, alkalis, aluminum, argon, base oil, cartons, ceramic abrasives, citric acid, demi water, ethanol, flocculants, glass abrasives, hydraulic fluids, isopropanol, lubricants, magnesium, nitrogen, oxygen, paper, penetrants, polyester, refractories, salt, sodium fluoride, steel, sulfur dioxide, surfactants, water, or, for example, wheat and / or flour and and / or other raw materials such as vitamins and / or water; (b) for waste generated, it includes (i) energy emissions, i.e., acetylene, diesel, electricity, solar power, fuel oil, natural gas, gasoline, propane; (ii) waste emissions, i.e., aluminum incineration, aluminum recycling, electronics dismantling, hazardous waste incineration, mercury treatment, mineral oil incineration with energy recovery, municipal solid waste incineration, paperboard incineration, PET incineration, sludge incineration with energy recovery, wood incineration; and c) for transportation emissions, it includes transportation by truck and transportation by ship.

[0058] For the generation of the final product 2 processed at the manufacturing site 1, the environmental quantification assessment can also include impacts on water depletion and utilization 142 and land use as measures to assess, for example, the impact on biodiversity, e.g., impacts 1422, 1423, e.g., impacts on agricultural land use per tonne of crop per year.

[0059] The product 2 assessment from feedstock production to distribution can be implemented, for example, as part of a dynamic and (semi-)automated tool, which can include dynamic scenarios of emissions, water and land use impacts based on activity data from specific feedstock production.

[0060] In a variant of the embodiment, the control device 10 controls the generated product CO 2 e Quantification measurements21 and / or generated industrial site CO 2It further provides third-party certification based on quantified measurements 141. The third-party certification includes ISO certification. The third-party certification can also be provided based on blockchain technology. [Prior art documents] [Patent documents]

[0061] [Patent Document 1] US Patent Application Publication No. 2011 / 0144791A1 [Explanation of symbols]

[0062] 1. Industrial site or plant 10 Control Device 101 Input section 1011 I / O Interface 1012 Network Interface 102 Supervisory Control and Data Acquisition Systems (SCADA) 103 Permanent Memory 1031 Non-volatile storage device 1032 Volatile storage device 104 Piloting and control parameters (i.e., the operating parameters of the industrial plant) 105 Environmental footprint generation for industrial site 1 106 Environmental Strength Impact of Product 2 107 Environmental Quantification Module 1071 CO 2 eQuantification module 108 Carbon Footprint Inventory System 1081 Interface 1082 Data Acquisition Module 1083 Settings Module 1084 Selection Module 1085 Material Detector 1086 Notification Module 1087 Data Processing Module 1088 Display Module 1089 Verification Module 11 Process Line 111 I / O Devices 112 Programmable Logic Controller (PLC) 113 Manufacturing Process 12 Processing unit 121 Operation value setting 13 Measuring Instruments Devices and Sensors 131 Processing unit operation measuring device 132 Environmental Measurement Devices 133 Product characteristic measuring devices and / or sensors 134 Measurement parameters 1341 Operational measurement parameters of processing unit 12 1342 Product characteristic measurement parameters 1343 Environmental Measurement Parameters 13431 Geographic Location Parameters 13432 Temporal and / or seasonal parameters 13433 Weather-related parameters 14 Environmental footprint or environmental impact intensity of an industrial site or plant 141 CO from industrial sites or plants 2 e Quantification measurements 142 Further sustainability measurement parameters 1421 Water use 1422 Land use 1433 Biodiversity 2 Products manufactured or processed by industrial site 1 21 Environmental impact intensity of product 2 211 Product CO 2 eQuantification means 212 Further sustainability measurement parameters 2121 Water use 2122 Land use 2123 Biodiversity 213 Emission Factors 2131 Raw materials 2132 Waste 21321 Energy Emissions 21322 Waste emissions 2133 Transport emissions 214 Product Materials 2141~214i Specific Materials 214i1 Weight of material 214i 214i2 Weight ratio of material 214i to the total weight of material 214 214i3 Total CO emissions from product 214 2 CO emitted from each material 2141-214i for e 2 Emission ratio of e 3. Industrial Plant 1 Environment 4 Data Transmission Network

Claims

1. A measuring and control device for optimizing the control and management of the energy consumption of an industrial site or plant and the measurement of the environmental footprint of products processed by said industrial site or plant, said industrial site comprising one or more processing units for processing one or more products, said control device comprising inputs connected to said measuring devices and sensors of said control device via input / output interfaces and a data transmission network in order to capture and / or monitor and / or record predefined measurement parameters in the data flow paths of said measuring devices and sensors of said control device, and based on said monitored measurement parameters the setting of operating values ​​of operating parameters is adapted in order to optimize the control of the energy consumption related to said environmental footprint of said industrial site and / or plant, said control device being an integral part of said industrial site and / or plant providing said industrial site and / or plant with autonomous or automatic electronic steering by means of a PLC interface to said processing units of said industrial site and / or plant, the monitored measurement parameters include: a parameter vector, the parameter values ​​of which are a time series of parameter values ​​that can vary over a predetermined operating period, and / or a parameter scalar, the parameter values ​​of which do not change over the entire operating period; and structural parameters, the structural parameter values ​​being indicative of structural characteristics of the industrial site or plant; Based on the monitored measured parameters, ２ e intensity, a product's environmental impact intensity value is generated; for generating said environmental impact intensity value of said product, emission factors are categorized and monitored by product cycle stage, said emission factors being categorized (i) for raw materials, (ii) for waste materials, including emission factors for energy emissions and emission factors for waste emissions, and (iii) for transport emissions; For the waste and product cycle stages, the control device detects the ingredients of the product triggered by the measured weight of each ingredient and calculates the CO ２ a material detector for generating a CO2 quantification of each material, the material including a plurality of materials, the material detector further comprising detecting a weight ratio, the weight ratio being a ratio of a weight of each material to a total weight of the material according to a weight of each material, the material detector detecting a weight ratio of each material to a total weight of the material according to a weight of each material, ２ e. the total CO emitted from the product in the product cycle according to the quantification ２ CO emitted from each material relative to e ２ e ratio CO ２ Measuring the e-ratio; Based on the measured industrial site environmental impact intensity value, the control device adapts the operation of the processing units of the industrial site or plant to dynamically change the operating value settings of the operating parameters of the industrial site or plant until a minimum measured value of the environmental impact intensity value of the product processed by the industrial site or plant is reached, at least two of the operating parameters being changed within a parameter space of the operating parameters. Measuring and control devices.

2. 2. The measuring and control device according to claim 1, characterized in that, based on the measured environmental impact intensity of a product and / or the measured environmental impact intensity of the industrial site or plant, the control device provides optimized improvement measures and possible improvement measures by mutually weighting influence of different cost parameters.

3. 3. The measurement and control device of claim 2, characterized in that the control device provides a dynamically adapted line configuration based on the dynamically adapted operating value settings, and based on the generated product impact intensity quantification measurements, the control device dynamically changes operating parameters of the industrial site or plant adapted to the operation of the processing units of the industrial site or plant until a minimum measured value of the environmental footprint of the product processed by the industrial site or plant is reached.

4. 2. The measuring and control device according to claim 1, characterized in that, based on the measured environmental impact intensity of a product and / or the measured environmental impact intensity of the industrial site or plant, the control device dynamically changes operating parameters of the industrial site or plant adapted to the operation of the processing units of the industrial site or plant until a minimum measured value of the environmental impact intensity of the industrial site or plant and / or the environmental impact intensity of the product processed by the industrial site or plant is reached.

5. 5. The measurement and control device of claim 4, wherein the operating parameters of the industrial site or plant are dynamically changed by applying simulated annealing to a parameter space of the operating parameters to change the operating parameters.

6. The operational parameters of the industrial site or plant are varied by varying at least two of the operational parameters within the parameter space of the operational parameters and the measured CO ２ 5. The measurement and control device of claim 4, wherein the e-footprint is dynamically modified by applying a first deviation based on Box-Wilson data processing to minimize the e-footprint.

7. The at least two of the operational parameters in the parameter space are optimized OC ２ 7. The measurement and control device of claim 6, wherein the e-footprint metric is probabilistically altered until it is measured.

8. The at least two of the operational parameters in the parameter space are ２ 7. The measurement and control device of claim 6, characterized in that a predefined threshold for the e-footprint is electronically altered until it is triggered.

9. 2. The measurement and control device of claim 1, characterized in that the industrial site comprises at least one industrial plant and / or process line and / or production facility / equipment.

10. 2. The measurement and control device of claim 1, characterized in that the control device further comprises at least one programmable logic controller (PLC) or programmable controller associated with the industrial site as an automation controller adapted for control of manufacturing processes or product processing processes at the industrial site, and input / output devices of the PLC are realized in the factory integrally with a data processor or are rack mounted as modular devices together with the input / output devices.

11. 11. The measurement and control device according to claim 10, characterized in that the at least one PLC of the industrial site is connected via a data transmission network to a supervisory control and data acquisition (SCADA) system of the control device, which provides programming and process fault diagnosis of processing units of the industrial site.

12. The measurement and control device of claim 1 , wherein the industrial site includes one or more process lines including at least one processing unit for processing or manufacturing the product.

13. CO of the product processed or manufactured by the industrial site ２ Product CO based on the monitored measurement parameters measuring e intensity ２ e For the generation of quantified measurements, emission factors are classified and monitored according to the emission factors of the raw materials generated, the processing and transportation of said products by product cycle stages, and the classification of said emission factors is as follows: (a) for the raw materials discharged: wheat and other crops, water, acids, alkalis, aluminium, argon, base oils, cartons, ceramic polishing agents, citric acid, demi water, ethanol, flocculants, glass polishing agents, liquid fluids, isopropanol, lubricants, magnesium, nitrogen, oxygen, paper, plastics and other packaging materials, penetrants, polyester, refractories, salt, sodium fluoride, steel. , sulfur dioxide, surfactants, water, and / or (b) waste material emissions including: (i) energy emissions: acetylene, diesel, electricity, solar, heavy oil, natural gas, gasoline, propane; (ii) waste material emissions: aluminum incineration, aluminum recycling, electronics dismantling, hazardous waste incineration, mercury processing, mineral oil incineration with energy recovery, municipal solid waste incineration, paperboard incineration, PET incineration, sludge incineration with energy recovery, wood incineration; and (c) transportation emissions: trucking, and shipping.

14. The measurement and control device of claim 1 , characterized in that the measurement devices and sensors are associated with the processing unit to measure or capture operational parameters and are associated with the industrial site or plant to measure environmental measurement parameters of the industrial site or plant.

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