Abstract: A machine learning device includes a data extraction unit that extracts first and second parameters from a plurality of machining programs. The machining programs numerically control a machine tool. The first parameter is a parameter to be adjusted, and the second parameter is a parameter used to adjust the first parameter. The machine learning device also includes a machine learning unit that learns a value of the first parameter according to a data set that includes the first and second parameters.

Abstract: Techniques for performing an emissions demand response (EDR) event are described. In an example, a cloud-based HVAC control system may obtain a first emissions rate forecast and generate an EDR event with a start time and end time based on the first emissions rate forecast. The EDR event may then be transmitted to a thermostat and stored in a memory of the thermostat. At the start time, the thermostat may commence controlling an HVAC system according to the EDR event. After the start time and prior to the end time, the cloud-based HVAC control system may obtain a second emissions rate forecast and generate a modified EDR event with a modified end time. The modified EDR event may be transmitted to the thermostat before the end time and/or the modified end time whereupon the thermostat may control the HVAC system accordingly until the modified end time is reached.

Abstract: To easily perform examination of at least one facility based on detection signals of a plurality of sensors installed in the facility. Provided are an examining apparatus, an examining method and a recording medium, including: a group designation acquiring unit to acquire designation of a targeted group including a plurality of targeted sensors to be analyzed among a plurality of sensors installed in at least one facility; a sensor data acquiring unit to acquire sensor data from each targeted sensor included in the targeted group; a learning unit to learn an analysis model by using the sensor data from each targeted sensor included in the targeted group; and an examining unit to examine the facility by using the learned analysis model.

Abstract: A hemming path planning method and a hemming system are provided. The hemming path planning method includes the following steps. An initial contour data of a target is scanned to obtain. A first segment of the hemming path is planned according to the initial contour data. The first segment corresponds to a first bending angle. A second segment of the hemming path is planned according to the initial contour data and an expected springback amount related to the first bending angle. The second segment corresponds to a second bending angle. The first segment and the second segment are combined to obtain a continuous hemming path.

Abstract: A dual positioned recirculating chute that would allow the operator to run the plant in either closed circuit or open circuit position. While in closed circuit position, the plant will run rock through and the chute will provide as a recirculating chute for oversized rock to travel from the recirculating conveyor back into the feeder hopper for re-crushing. The operator can then reposition the chute to the open circuit position, which will change the direction of the chute away from the feeder hopper and discharge material off the side of the plant. This can be oversized rock material to form an additional stock pile or be redirected to an off-plant conveyor. This can also allow for the removal of trash and unwanted material from the plant cycle without the need for a full plant shutdown, locking out the proper equipment, and manually removing before restarting the crushing process again.

Abstract: A method for a direct current (DC) islanding detection based on positive feedback of a bus voltage at a specific frequency, essentially including three steps: extraction of a specific frequency component of the bus voltage, injection of a disturbance component of the specific frequency, and determination of DC islanding. The extraction of the specific frequency component of the bus voltage and the injection of the disturbance component of the specific frequency constitute a positive feedback mechanism in a power management unit control loop. In a grid-connected mode of a DC grid, the positive feedback mechanism fails due to a control action of a voltage management unit on a bus, and the bus voltage remains stable. In an islanding mode of the DC grid, under an action of the positive feedback mechanism, the power management unit allows the bus voltage to generate a self-excited oscillation at the specific frequency.

Abstract: A safety-directed control system comprises at least one safety sensor unit and at least one safety actuator unit, which are connected to one another via a fieldbus, and a programming device. Sensor connections for connecting safety sensors to the fieldbus are provided by the at least one safety sensor unit, the sensor connections being associated with safety lines. The programming device displays the available safety lines to a user via an output interface and receives a user input via an input interface, with the user input associating a selected safety response, which is executable by the safety actuator unit, with at least one selected safety line. The programming device further stores the association between the selected safety line and the selected safety response in the safety actuator unit as a safety configuration.

Abstract: The technology as disclosed herein includes a method and apparatus for deboning a meat item, and more particular for deboning a poultry item including performing an initial shoulder cut for removing boneless breast meat from the poultry carcass or frame. The method and apparatus disclosed and claimed herein is a combination of a robotic arm including an ultrasonic knife implement and a vision system for varying the cut path based on the shape and size of the poultry item. The combination as claimed including the ultrasonic knife can perform a meat cut while penetrating the meat with less force than the typical penetration that occurs when using a traditional knife.

Abstract: The systems and methods disclosed herein include a handheld programmer for replacing LED drivers in the field. The handheld programmer includes a communications module configured to communicate with a first light emitting diode (LED) driver and a second LED driver, and a processor configured to read a plurality of settings from the first LED driver and program the second LED driver with the plurality of settings from the first LED driver.

Abstract: The present disclosure provides systems, apparatuses, and methods for monitoring building efficiency by a heating, ventilation, and air conditioning (HVAC) system. In an aspect, an HVAC unit including a memory and a processor coupled with the memory is disclosed. The processor may be configured to establish a current building efficiency state value of a current run cycle of the HVAC system. The processor may also be configured to determine an building efficiency state deviation value based on a difference between an average building efficiency state value of a set of previous building efficiency state values and the current building efficiency state value. The processor may further be configured to determine whether the building efficiency state deviation value satisfies a building inefficiency threshold.

Abstract: A method of processing a substrate includes subjecting a substrate to processing that modifies a thickness of an outer layer of the substrate, measuring a spectrum of light reflected from the substrate during processing, reducing the dimensionality of the measured spectrum to generate a plurality of component values, generating a characterizing value using an artificial neural network, and determining at least one of whether to halt processing of the substrate or an adjustment for a processing parameter based on the characterizing value. The artificial neural network has a plurality of input nodes to receive the plurality of component values, an output node to output the characterizing value, and a plurality of hidden nodes connecting the input nodes to the output node.

Abstract: A method (1000) for condition monitoring is disclosed, comprising registering (1010) values (v1) of movement characteristics measured for cycles of motion of a cyclically moving machine, associating (1050) the occurrence of values in a frequency distribution (Fv1) of the values with respective defined indexes (a, b, c, . . . ) based on intervals, generating (1060) a word string (S) of the defined indexes corresponding to the occurrence of the values, segmenting (1070) said word string (S) into a sub-set of words (s1, s2, . . . , si), determining (1080) a frequency of the occurrence of the segmented words in said word string as a first reference term frequency (TF1), associated with a first machine status (M1), for subsequently registered set of values of movement characteristics, determining (1100) a subsequent term frequency (TFn), comparing (1110) the subsequent term frequency (TFn) with the first reference term frequency to determine a correlation with the first machine status.

Abstract: A controller for controlling an energy discharge from an energy saving device to a power grid. The system includes decision logic to implement a local response responsive to events currently occurring in a power grid and in addition remote commands sent from a remote location.

Abstract: Computer-implemented methods and structures deploy a heating ventilation and air conditioning (HVAC) energy optimization program. A standard operating control platform (OCP) is deployed in an energy optimization control engine (EOCE) computing system communicatively coupled to a plurality of HVAC components via a building automation system (BAS). An energy optimization portal (EOP), which receives from the EOCE computing system a first data set identifying the plurality of HVAC components, a second data set including operational control parameters for each of the plurality of HVAC components, and a third data set including measured operations data associated with each of the plurality of HVAC components. The EOP generates an energy optimized operating control platform based on the first, second, and third data sets, which is automatically communicated from the EOP to the EOCE computing system.

Abstract: Apparatuses and methods for dimensioning and modifying a part to be manufactured are provided. Part information for a part to be manufactured is received by a processor, where the part information includes a model and print of the part. Tolerance datum are extracted from the print and a manufacturability datum is determined as a function of the model and tolerance datum. Updated tolerance datum is generated and a manufacturability of the part is determined. A manufacturing quote and user feedback is provided.

Abstract: Examples of a predictive maintenance method includes determining whether analog data measured in a substrate treatment that has used a recipe exceeds an allowable threshold which corresponds to the recipe and has been determined beforehand, and notifying, in a case where it is determined that the analog data exceeds the allowable threshold in the determination, a user that a relating module which has been associated with the analog data beforehand has deteriorated.

Abstract: A method for controlling a heated process of an electric heater includes obtaining a setpoint variable indicating a target temperature of the heater. The method includes identifying an energy profile for the heater based on the setpoint variable. The energy profile provides a defined magnitude of initial electrical energy to be applied to the heater to have a temperature of the heated process reach the target temperature. The method includes obtaining a process variable indicating a performance characteristic of the heated process. The method includes providing electrical energy to the heater based on at least one of the energy profile and the process variable.

Abstract: An energy management system is configured to calculate a percentage of satisfied based on the report data for each of the plurality of buildings; create, for each of the plurality of buildings, a plan for operating each of the air-conditioning facilities based on the percentage of satisfied and a predetermined target percentage of satisfied; calculate a first energy consumption amount based on the first piece of data; calculate a second energy consumption amount based on the second piece of data, the third piece of data, and the fourth piece of data, the second energy consumption amount being obtained when the each of the air-conditioning facilities is operated after a lapse of a predetermined time period; and control, when the first energy consumption amount is larger than the second energy consumption amount, the operation of the each of the air-conditioning facilities so as to achieve the second energy consumption amount.

Abstract: A machine learning device performs machine learning with respect to a plurality of servo control units corresponding to a plurality of axes. A first servo control unit related to an axis receiving interference includes a compensation unit that compensates for at least one of a position error, a velocity command, and a torque command of the first servo control unit based on at least one of a variable related to a position command and a variable related to position feedback information of a second servo control unit related to an axis generating the interference. The machine learning device acquires state information including first and second servo control information and a coefficient of the function, outputs action information and a reward value for reinforcement learning, and updates a value function on the basis of the reward value, the state information, and the action information.

Abstract: A building management system (BMS) for filtering a fluid within a building is shown. The system includes one or more sensors configured to measure one or more characteristics of a first fluid within an air duct of the BMS and measure one or more characteristics of a second fluid after the second fluid has been filtered. The system further includes a pollutant management system configured to receive data from the one or more sensors and control a filtration process. The filtration process selects a filter of a plurality of filters based on at least one of a level of the one or more characteristics of the first fluid or the one or more characteristics of the second fluid.