Abstract: Certain example embodiments relate to techniques generating a database of virtual families for real-time generation of part numbers for configurable products. For instance, certain example embodiments may include receiving a search request for part numbers and determining virtual families including entities matching the search request. The number of matching products matching the search request and the part numbers may be determined based on the virtual families and the independent groups stored in the virtual families that match the search request. The part numbers may be determined based on allowed characters, number and/or symbols for the part number positions defined in the independent groups of the virtual families including the entities matching the one or more configurable properties of the user input search request. Facet counts for the configurable product may also be determined based on the results of the user input search request.

Abstract: Embodiments relate to a system that generates a crop yield component map for a field. The system determines amounts of nitrogen applied to each portion of the field by a set of nitrogen applicator farming machines. The system accesses crop yield data associated with a crop that was grown in the field. The crop yield data was generated by a set of harvester farming machines that travelled through the field and harvested plant parts of the crop. The system determines, by analyzing the crop yield data, plant part metrics for the harvested plant parts in each field portion. The system generates a crop yield component map that maps, for each field portion, a plant part metric associated with the field portion and an amount of nitrogen applied to the field portion. The component map may then be provided for display.

Abstract: A method for generating a resultant test plan for testing a measurement object includes generating at least one data record by measuring the measurement object. The method includes assigning at least part of the measurement object to at least one object class based on the at least one data record. The method includes determining a test plan assigned to the at least one object class as an object-class-specific test plan. The method includes determining the resultant test plan based on the object-class-specific test plan. The assignment of the at least part of the measurement object to the at least one object class is independent of dimensions.

Abstract: Devices, systems, and methods for social behavior of a telepresence robot are disclosed herein. A telepresence robot may include a drive system, a control system, an object detection system, and a social behaviors component. The drive system is configured to move the telepresence robot. The control system is configured to control the drive system to drive the telepresence robot around a work area. The object detection system is configured to detect a human in proximity to the telepresence robot. The social behaviors component is configured to provide instructions to the control system to cause the telepresence robot to operate according to a first set of rules when a presence of one or more humans is not detected and operate according to a second set of rules when the presence of one or more humans is detected.

Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving operational parameters for one or more automation devices, wherein the one or more automation devices are configured to implement control logic generated based on a decision tree. The operations also include receiving an output by the decision tree based on the operational parameters. Further, the operations include determining the output is an anomalous output based on a constraint associated with the decision tree. Further still, the operations include generating an updated decision tree based on the anomalous output. Even further, the operations include generating updated control logic for the one or more automation devices based on the updated decision tree. Even further, the operations include sending the updated control logic to the one or more automation devices.

Abstract: The present invention provides a data sorting device and method and a monitoring and diagnosis device, which are able to create a model conveniently. A data sorting device and a monitoring and diagnosis device of the present invention include an operating data database which stores operating data of the plant equipment in a time-series manner. The devices input the operating data that are highly associated physically and engineeringly among the operating data stored in the operating data database, inputting processing attributes relevant to the operating data that are highly associated physically and engineeringly, creating a model simulating characteristics of the plant equipment, and performing data sorting, monitoring, and diagnosis through use of the model.

Abstract: Systems and methods are disclosed herein for detecting impurities of harvested plants in a receptacle of a harvester. In an embodiment, a harvester controller receives, from a camera facing the contents of the receptacle, an image of the contents. The harvester controller applies the image as input to a machine learning model. The harvester controller receives, as output from the machine learning model, an identification of an impurity of the harvested plants. The harvester controller transmits a control signal based on the impurity.

Abstract: The present disclosure provides a method for managing a pipe network of natural gas. The method may comprise: obtaining pipe network information of natural gas in at least one area, the pipe network information including a running time of a system of the pipe network of the natural gas and gas leakage information of the pipe network; extracting feature information based on the running time and the gas leakage information; predicting a maintenance time of the pipe network by inputting the feature information into a maintenance time prediction model.

Abstract: A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.

Abstract: There are provided systems and methods for determining processing weights of rule variables for rule processing optimization. A service provider, such as an electronic transaction processor for digital transactions, may utilize different decision services that implement rules for decision-making of data including real-time data in production computing environments. Rules may correspond to coded statements that perform an automated decision-making service for the computing services and platforms of the service provider. When writing rules, different variables for data objects may be utilized, where each variable may perform a different operation and/or utilize a different operation for fetching and retrieving data used during rule processing. Each variable may therefore have a different data processing weights based on processing requirements of the data. Thus, optimization of rule authoring may be performed by mapping variables to other similar variables and showing a processing weight of each variable.

Abstract: A state diagnosis apparatus of a moving system part is provided and includes a sensor unit that measures and collects state data of a moving system part relevant to an engine. A graphic controller primarily diagnoses classification data generated by classifying the state data according to a predetermined filtering condition as a normal state or an abnormal state using a Deep Learning model.

Abstract: Certain example embodiments relate to techniques generating a database of virtual families for real-time generation of part numbers for configurable products. For instance, certain example embodiments may include receiving a search request for part numbers and determining virtual families including entities matching the search request. The number of matching products matching the search request and the part numbers may be determined based on the virtual families and the independent groups stored in the virtual families that match the search request. The part numbers may be determined based on allowed characters, number and/or symbols for the part number positions defined in the independent groups of the virtual families including the entities matching the one or more configurable properties of the user input search request. Facet counts for the configurable product may also be determined based on the results of the user input search request.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data with coefficient data specific to a processing mode selection. For example, a computing system with processing units may mix the input data for a transmission in a radio frequency (RF) wireless domain with the coefficient data to generate output data that is representative of the transmission being processed according to a specific processing mode selection. The input data is mixed with coefficient data at layers of multiplication/accumulation processing units (MAC units). The processing mode selection may be associated with an aspect of a wireless protocol. Examples of systems and methods described herein may facilitate the processing of data for 5G wireless communications in a power-efficient and time-efficient manner.

Abstract: A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.

Abstract: Disclosed is a method for improving the measuring performance of automation field devices, wherein each of the field devices determines a process variable using a measuring algorithm and is exposed to measurable environmental influences. The method includes capturing the calibration data of the field devices and capturing an item of environmental information of the field devices at defined time intervals; storing the environmental information, the calibration data, and a time stamp in a database; selecting a group of field devices which determine a process variable using the same measuring algorithm and which are exposed to the same environmental influences; correlating the environmental information and calibration data captured over time; creating a mathematical model relating the calibration data and the environmental information; adapting the measuring algorithm on the basis of the model; and transmitting the adapted measuring algorithm to all field devices in the group.

Abstract: An information processing device includes a memory, and a processor coupled to the memory and configured to rearrange setup operations with respect to an initial input order according to which products are to be input to a processing line including a plurality of lines to which a product that requires a setup operation and a processing operation is to be input, setup operations being not executed with the setup operations overlapped with each other in the plurality of lines, determine a processing completion time of the processing line based on the rearranged setup operations, and determine, as planning data, an order of setup operations that achieves a processing completion time less than a processing completion time of the initial input order among the processing completion time calculated.

Abstract: Devices, systems, and methods for social behavior of a telepresence robot are disclosed herein. A telepresence robot may include a drive system, a control system, an object detection system, and a social behaviors component. The drive system is configured to move the telepresence robot. The control system is configured to control the drive system to drive the telepresence robot around a work area. The object detection system is configured to detect a human in proximity to the telepresence robot. The social behaviors component is configured to provide instructions to the control system to cause the telepresence robot to operate according to a first set of rules when a presence of one or more humans is not detected and operate according to a second set of rules when the presence of one or more humans is detected.

Abstract: A method and system for optimal control of ultra-precision cutting. The method for optimal control is based on time-precipitates-temperature characteristics of Al—Mg—Si series aluminum alloy, and includes first determining types of precipitates of machined materials, and establishing a Lifshitz-Slyozov-Wagner (LSW) model of each precipitate. A temperature range is determined corresponding to each precipitate according to the LSW model to obtain a comprehensive temperature range. A relation model is established between cutting parameters and a cutting temperature according to the LSW model. Finally the cutting parameters are optimized according to the comprehensive temperature range and the relation model, so that the cutting temperature is beyond the comprehensive temperature range to inhibit the generation of the precipitates.

Abstract: A method for calibrating a sensor with respect to a reference trajectory indicating a number of timely successive data values using an encoder/decoder neural network with an encoder function and a successive decoder function. The method includes training the encoder function and the decoder function of the encoder/decoder neural network with respect to a reference trajectory so that a reconstruction error of the reference trajectory at an input of the encoder function and a reconstructed reference trajectory at an output of the decoder function is minimized; training a calibration vector with respect to a sensor trajectory so that a reconstruction error between an output sensor trajectory and a corresponding reference trajectory is minimized, the output sensor trajectory is obtained by applying the calibration vector on the sensor trajectory and the encoder function and decoder function on the the calibrated sensor trajectory; and applying the calibration vector to calibrate the sensor.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage medium, for controlling operations of machine tool workstations. Machine tool workstations are grouped into functional groups. Neural networks corresponding to the functional groups are trained to process respective inputs representing parts to be processed to generate respective outputs representing sequences of ordered subsets of the parts that produce a reduced setup time for workstations in the functional groups. Data representing respective collections of parts to be processed by workstations included in the functional groups is processed using the trained neural networks to generate corresponding sequences of ordered subsets of the collection of parts. Average delay times associated with the generated sequences of ordered subsets of the collection of parts are computed.

Abstract: A substrate-handling vacuum robot includes a first robotic arm with a single-substrate end effector and a second robotic arm with a batch end effector. The single-substrate end effector permits single-substrate pick-and-place operations while the batch end effector permits batch handling of substrates within a vacuum environment.

Abstract: A generalized pattern recognition is used to identify faults in machine condition monitoring. Pattern clusters are identified in operating data. A classifier is trained using the pattern clusters in addition to annotated training data. The operating data is also used to cluster the signals in the operating data into signal clusters. Monitored data samples are then classified by evaluating confidence vectors that include substitutions of signals contained in the training data by signals in the same signal clusters as the signals contained in the training data.

Abstract: A method for monitoring the quality of laser-machining processes (500), in particular laser-cutting or laser-welding processes, including the operations of: acquiring via sensor means (540), in particular optical sensors, a machining-process signal (Xp) and calculating from said signal representing the process (Xp) parameters (E1, E2, DC) that represent the machining quality during the laser-machining process; and making available (130) corresponding reference parameters (E1r, E2r, DCr) representing a given machining quality, which are calculated from a process reference signal (Xr) acquired via said sensor means (540).

Abstract: An evaluation method of a progressive-addition lens is provided. First, powers of the progressive-addition lens at a plurality of measurement points are measured to obtain an actually measured power distribution. Next, a comparison power distribution created based on the actually measured power distribution and a defective power distribution prepared in advance are compared with each other to perform similarity search between the both. Thereafter, whether or not the comparison power distribution and the defective power distribution are similar to each other is determined based on the result of the similarity search step, and if it is determined that the comparison power distribution and the defective power distribution are similar to each other, then the progressive-addition lens is evaluated as defective.

Abstract: A process for the custom design and automated, custom manufacture of golf clubs. According to a first embodiment, a computer user interface, preferably a graphical user interface (GUI), guides a user's selection of preferred golf club design parameters. According to a second embodiment, input data about a golfer's style of play and golf club performance needs are captured from data collection systems, and analyzed by black box algorithms, preferably fuzzy logic algorithms, to infer golf club design parameters. After preferences for, or inferences about, golf club design parameters are developed in accordance with the two embodiments, a computer aided (CA) system is used to design and manufacture the desired golf clubs.

Abstract: Embodiments of the invention can include methods and systems for controlling clearances in a turbine. In one embodiment, a method can include applying at least one operating parameter as an input to at least one neural network model, modeling via the neural network model a thermal expansion of at least one turbine component, and taking a control action based at least in part on the modeled thermal expansion of the one or more turbine components. An example system can include a controller operable to determine and apply the operating parameters as inputs to the neural network model, model thermal expansion via the neural network model, and generate a control action based at least in part on the modeled thermal expansion.

Abstract: A method of fuzzy control for adjusting a semiconductor machine comprising: providing measurement values from first the “parameter of a pre-semiconductor manufacturing process”, second the “parameter of the semiconductor manufacturing process”, and third the “operation parameter of the semiconductor manufacturing process”; performing a fuzzy control to define two inputs and one output corresponding to the measurement values, wherein the difference between the first and third values, and the difference between the second and third values, forms the two inputs, then from the two inputs one target output is calculated by fuzzy inference; finally, determining if the target output is in or out of an acceptable range. Whereby the target output is the “machine control parameter of the semiconductor manufacturing process” and when within an acceptable range is used for adjusting the semiconductor machine.

Abstract: Crop information related to a particular crop is collected and stored in data storage during the performance of an agricultural operation. A harvested particular crop is segregated from all other genetically distinct crops by storing the particular harvested crops in one or more segregated storage volumes for storing the particular crop. Each segregated storage volume has a corresponding storage identifier. An electronically accessible data profile, associated with the particular crop, is provided or made available to a user. The data profile includes the collected crop information.

Abstract: A method for controlling the quality of an industrial process, of the type that comprises the steps of: providing one or more reference signals for the industrial process; acquiring one or more real signals that are indicative of the quality of said industrial process; and comparing said one or more reference signals with said one or more real signals in order to identify defects in said industrial process.

Abstract: Systems and methods of industrial control processes that employ a data matching component associated with a programming logic controller (PLC), to substitute a plurality of collected data points with a data pattern (e.g., a curve). Such data matching component can facilitate data trending analysis, wherein a running industrial process can be compared with a predetermined criteria (industrial process with optimal/desired performance). A graphical tool (e.g., an on-screen) can be provided as part of the matching component, to enable a user to interactively set deviation thresholds from a predetermined criteria (e.g., optimum performance of an industrial operation.

Abstract: Test molding and mass-production molding are performed by an injection molding machine that includes a control apparatus in which neural networks are used. A quality prediction function determined based on the test molding is revised as necessary during mass-production molding.

Abstract: A method and system for product fulfillment in an automated manufacturing system is disclosed. The method and system of the present invention includes obtaining requirements for a product from a customer. The method and system further includes creating a plan from the requirements using a descriptive language. The plan is then conveyed to an automated manufacturing system for use in manufacturing the product.

Abstract: The present invention provides a method of optimizing a painting process for applying a paint layer on an article. The method comprises defining a functional relationship paint processing parameters and a paint layer property (i.e., the average paint layer thickness) using a neural network. This functional relationship is then used in a paint optimization function that measures a combination of quality control parameters and efficiency parameters. Finally, the paint optimization function is optimized by adjusting the paint processing parameters utilizing the functional relationship formed by the neural network. The invention also provides a system that implements the methods of the invention.

Abstract: A method of determining properties relating to the manufacture of an injection-molded article is described. The method makes use of a hybrid model which includes at least one neural network and at least one rigorous model. In order to forecast (or predict) properties relating to the manufacture of a plastic molded part, a hybrid model is used which includes: one or more neural networks NN1, NN2, NN3, NN4, . . . , NNk; and one or more rigorous models R1, R2, R3, R4, . . . , which are connected to one another. The rigorous models are used to map model elements which can be described in mathematical formulae. The neural model elements are used to map processes whose relationship is present only in the form of data, as it is typically impossible to model such processes rigorously. As a result, a forecast (or prediction) relating to properties including, for example, the mechanical, thermal and rheological processing properties and relating to the cycle time of a plastic molded part can be made.

Abstract: The present invention: solves the problems of hitherto disclosed technologies, such as insufficient suppression of the oxidation loss of [Cr] and the excessive erosion of refractories, in the decarburization-refining of chromium-contained molten steel under a normal or reduced pressure; and is characterized by: determining, in sequence; a molten steel temperature during the refining through actual measurement or computation from a molten steel temperature before the refining and refining conditions; [C] and [Cr] concentrations during the refining through actual measurement or computation from molten steel components before the refining and refining conditions; a CO partial pressure PCO in an atmosphere during the refining from the total pressure P of the atmosphere, an oxygen gas supply rate and an inert gas supply rate, a Hilty's equilibrium temperature TH from said [C] and [Cr] concentrations and PCO; the difference &Dgr;T between said molten steel temp

Abstract: Control apparatus for a horizontal boring tool is described which drives a boring lance via boring rods. The tool includes an input interface for receiving actual values of controlled variables of the horizontal boring tool, and an output unit for issuing control signals for controlling the horizontal boring tool. Between the input interface and the output unit is provided a fuzzy control unit which determines the control signals for activation of the horizontal boring tool from the actual values of the controlled variables and the desired values for the controlled variables by fuzzy logic while taking into account heuristic process values. The control apparatus permits automatic operation of the horizontal boring tool with good course steering and high precision.

Abstract: An artificial multiped is constructed (either in simulation or embodied) in such a way that its natural body dynamics allow the lower part of each leg to swing naturally under the influence of gravity. The upper part of each leg is actively actuated in the sagittal plane. The necessary input to drive the above-mentioned actuators is derived from a neural network controller. The latter is arranged as two bi-directionally coupled chains of neural oscillators, the number of which equals twice that of the legs to be actuated. Parameter optimisation of the controllers is achieved by evolutionary computation in the form of a genetic algorithm.

Abstract: A system and method is provided for monitoring the operating condition of a pump by evaluating fault data encoded in the instantaneous current of the motor driving the pump. The data is converted to a frequency spectrum which is analyzed to create a fault signature having fault attributes relating to various fault conditions associated with the pump. The fault signature is then input to a neural network that operates in conjunction with a preprocessing and post processing module to perform decisions and output those decisions to a user interface. A stand alone module is also provided that includes an adaptive preprocessing module, a one-shot unsupervised neural network and a fuzzy based expert system to provide a decision making module that operates with limited human supervision.

Abstract: The present invention provides cavitation detection systems and methods employing a classifier for detecting, diagnosing and/or classifying cavitation in a pumping system. The classifier can be integral to tie cavitation detection system and/or operatively coupled to the cavitation system via a controller, diagnostic device and/or computer. Parameters such as flow, pressure and motor speed arc measured and/or estimated, and then provided to a classifier system Such systems include Bayesian, Fuzzy Set, nonlinear regression, neural networks and other training systems, for example The classifier system provides a signal indicative of the existence and extent of cavitation. An exemplary classification system is presented that delineates cavitation extent into one or more of the following categories: 0 (no cavitation), 1 (incipient cavitation), 2 (medium cavitation), 3 (fill cavitation) and 4 (surging cavitation).

Abstract: An intelligent control method for injection machine is to transplant the intelligent control and prediction techniques of a neural network to an injection machine, which has been exemplified capable of deciding the quasi best machine parameters rapidly in couple processing cycles for increasing yield with least loss, and for detecting and adjusting conditions until a desired operation environment is obtained.

Abstract: A method for modeling a paper winding device, particularly for modeling a tambour drum cutter. Influencing and control quantities are determined at a real paper winding device and are stored dependent on time. Said quantities are used to determine the web strength depending on the wound number of layers or, respectively, or a correlative quantity is used as a target quantity along with the other relevant control and influencing quantities to enable a neural network to be trained as a model for a nip (Ni) for this winding device. New data for training the network can be continually obtained during the operation of the arrangement, thereby improving the model. Optimal control parameters can be determined for various production requirements by means of an iterative process dependent on the winding quality, which can also be determined from the web strength.

Abstract: A system includes a sensor section which receives fuzzy information inputs X containing a plurality of components and converts the plurality of components into a plurality of measurable input physical quantities, a converter which receives a plurality of input physical quantities and converts the input physical quantities into a plurality of pulses having pulse widths corresponding to the magnitudes thereof, and a feature extraction section (NF) which receives a plurality of pulses, selects the plurality of pulses by using a set pulse width as a reference, and extracts feature information items y0, y1, y2, . . . which express the features of the fuzzy information inputs X from the fuzzy information inputs X according to the number of selected pulses.

Abstract: A control system for a harvester or similar implement includes a supervisory controller, a set of low-level controllers and a neuro-fuzzy inference system. The supervisory controller employs human expert knowledge and fuzzy logic. The controller monitors the quality of the harvesting process, such as gain loss, dockage, grain damage and the like. Based on the measurements, setpoints for all critical functional elements of the implement are determined. The neuro-fuzzy inference system determines machine settings according to operating conditions and learns from harvester experience. The parameters of the neuro-fuzzy inference system are stored in on-board memory. The neuro-fuzzy system can be used for harvester set-up and as one of the knowledge sources for repeated adjustments during the harvest.

Abstract: A method of determining properties relating to the manufacture of an injection-molded article is described. The method makes use of a hybrid model which includes at least one neural network and at least one rigorous model. In order to forecast (or predict) properties relating to the manufacture of a plastic molded part, a hybrid model is used which includes: one or more neural networks NN1, NN2, NN3, NN4 , . . . , NNk; and one or more rigorous models R1, R2, R3, R4, . . . , which are connected to one another. The rigorous models are used to map model elements which can be described in mathematical formulae. The neural model elements are used to map processes whose relationship is present only in the form of data, as it is typically impossible to model such processes rigorously. As a result, a forecast (or prediction) relating to properties including, for example, the mechanical, thermal and rheological processing properties and relating to the cycle time of a plastic molded part can be made.

Abstract: A method for tracking agents across loss of state events is described. After determining the number of terminal agents within a hierarchical agent system, an algorithm forms a first matrix containing data identifying agents within the hierarchical agent system. After a potential loss of state event has occurred, the algorithm forms a second matrix containing data identifying agents within the hierarchical agent system and compares the first matrix to the second matrix. If the matrices are identical, no agent switch occurred during the potential loss of state event. If the matrices are not identical, at least one agent switch occurred during the potential loss of state event.

Abstract: To maximize the production run speed of a sheet fabrication machine such as a turret punch press, and yet at the same time maintaining the requisite accuracy for each part produced from the production run, historical data pertaining to the various parameters for effecting the positioning moves of a worksheet are measured and collected using a reference machine or a prototype machine. For each positioning move to be effected, the CNC controller of the system retrieves the historical data from a database and, using that historical data, calculates the various parameters that affect the positioning move. By using fuzzy logic, the controller becomes, in a sense, self teaching, especially if updated historical data are provided to its database store to enhance the accuracy for later positioning moves. In addition to measuring and collecting historical data from reference or prototype machines, static process control (SPC) tests may be performed for different types of worksheets under different loads.

Abstract: A fuzzy control apparatus for a jet loom detects a flying state of a weft yarn, performs, based on a detected value thus detected, fuzzy inference to determine a modification amount to a rotational frequency of a motor, drives the motor to rotate at a predetermined rotational frequency, and corrects the rotational frequency of the motor based on the correction amount.

Abstract: An apparatus for regulating welding parameters during laser beam welding includes a camera for detecting the geometry of a melt bath formed during the welding process. The camera is connected with an image-data-processing unit. The welding depth is regulated by the processing unit as a function of the detected melt bath length or melt bath area. The focus position of the laser beam is regulated as a function of the geometric similarity factor, which is calculated as the quotient of the melt bath area and the distance between the geometric centers of gravity of the laser beam keyhole and the melt bath area. Detection and regulation of gaps between the workpieces of height offset between the workpieces and/or lateral offset of the laser beam is also provided for.

Abstract: A method of and apparatus for providing self-learning correction to the error in positioning movement of a platform in a vehicular wheelchair lift or any moving member of machinery or an equipment. The method includes the steps of programming the platform or moving member to stop at a target position, calculating an error between the programmed target position and an actual stop position of the platform or moving member, and deriving a new target position to stop the platform or moving member based on the calculated error to compensate the overshoot or shortcoming of the actual stop position of the platform or moving member. The apparatus implementing this method may include a programmable control mechanism such as a microprocessor having means for performing the programmed sequential operations.

Abstract: An electronic control device for management of the steering in earth-moving machines, essentially comprises a programmable logic electronic control unit (1) which is arranged as an interface between a pushbutton console (2) for setting a steering mode and an input diagnostics system (3) associated with the functions of the gearcase and the engine and with positioning of the wheels of the machine. The setting of a steering mode on the pushbutton console (2) is made possible by simultaneous selection of at least two switches (50). The input diagnostics system (3) of the electronic control unit (1) comprises a front wheel alignment sensor (28) and a rear wheel alignment sensor (29) which are respectively positioned in the region of the front and rear axles of the earth-moving machine and are designed to detect respectively the alignment position of the front and rear wheels with respect to the longitudinal axis of the machine itself.