An intellectual quality management method is disclosed. A heatmap risk interface is created according to the required data and the parameter configuration which are calculated using a time dependent risk priority number (RPN) equation. An intellectual audit scheduling algorithm is defined via the heatmap risk interface to automatically generate at least one audit plan. An audit program corresponding to the audit plan is performed and a plurality of problem points are selected. Intellectual root cause category recommendation is performed to the questions points. intellectual corrective actions and preventive action recommendations are performed to the problem points according to the intellectual root cause category recommendation to obtain at least one optimum corrective action and at least one preventive action. Corrective actions are performed to each audit unit according to the corrective action to solve the problem points and prevention actions are performed to each audit unit according to the preventive action.

An information translation device, information translation method, and an information translation system based on Modbus are provided. The client module of the information translation device receives an information model file including identity information, receives a sensor signal corresponding to first identity information and Modbus data including memory addresses of Modbus protocol, determines a first memory address corresponding to the sensor signal according to sensed values of the sensor signal and values corresponding to each of the memory addresses and builds a memory address mapping table including the first memory address and the first identity information, and receives a first value of the first memory address and searches the first identity information corresponding to the first memory address according to the memory address mapping table. The server module of the information translation device receives the first value and the first identity information and transmits to an OPC UA device.

A system includes a first group of sensors and a control circuit including one or more processors. The first group of sensors is associated with an energy storage module having one or more energy storage devices. The sensors in the first group generate sensor measurements representing one or more parameters of the energy storage module. The control circuit is configured to receive the sensor measurements and determine one or more of a reference value or a reference variation of a specific parameter related to the energy storage module based at least in part on the sensor measurements. The control circuit compares one or more of monitored values or monitored variations of the specific parameter, based on the sensor measurements generated by sensors, to the reference value or the reference variation of the specific parameter and detects a deviation that is greater than a designated tolerance margin.

A safety detector including a detection module configured for reading a control signal at the input, the detector including two supply terminals, a first control input and a first control output, a first safety output and a second safety output, and a first free terminal and a second free terminal, the detector including: a second control input connected to the first free terminal and a second control output connected to the second free terminal, and a test module configured for notably applying a first test sequence including a disabling of the first control output and a test of a start loop connected between the second control output and the first control input.

A cooperative learning system usable for process monitoring in which a monitoring model is provided for each of plural processes arranged in chronological order at predetermined transition time period intervals. The system stores, in chronological order, first monitoring data in a first process, second monitoring data in a second process, and at least one monitoring result from the first process output from a first monitoring model using the first monitoring data as an input parameter. The system performs parent model learning processing for the first monitoring model using the first monitoring data and the monitoring result from the first monitoring model, and performs child model learning processing for a second monitoring model using a monitoring result from the first monitoring model at a first time as teacher data and using the second monitoring data at a second time shifted from the first time by a transition period as an input parameter.

A method and system for assigning slot addresses to modules in a fault tolerant industrial control system includes a pair of backplane switches on each base. Each backplane switch is configured to communicate between one backplane and the modules located on the base and to communicate between backplane switches located at adjacent bases. A backplane switch on a bank master base first assigns a base address and slot addresses to itself. The backplane switches on each additional base initiate transmission of a base address request. A base address response, including a base address and slot numbers for the adjacent base, is transmitted after a base has its own address assigned. Each base repeats the process in sequence along the bank, incrementing the base address by one and the slot address by the number of slots on the base and passing the new base and slot addresses along the bank.

Methods, systems, and non-transitory computer readable storage media are disclosed for generating action recommendations modifying physical emissions sources of an entity based on past and modeled emissions for the entity. Specifically, the disclosed system monitors emissions produced by an entity by determining a number of emissions sources corresponding to an entity and a plurality of emissions values for the emissions sources. Additionally, the disclosed system determines a plurality of constraints corresponding to the entity. The disclosed system also determines goals for the entity including target emissions values. The disclosed system utilizes a modified gradient descent model to iteratively adjust emissions values for the physical emissions sources to obtain the target emissions values according to the constraints. The disclosed system generates action recommendations for modifying the physical emissions sources utilizing the modified gradient descent model and provides the action recommendations for display within a graphical user interface.

Methods, systems, and non-transitory computer readable storage media are disclosed for generating action recommendations for generating action recommendations for modifying physical emissions sources of an entity based on forecasting and monitoring emissions production for the entity utilizing machine-learning models. Specifically, the disclosed system forecasts emissions produced by an entity by utilizing a plurality of different forecasting machine-learning models corresponding to different physical emissions sources to generate forecasted source attributes. Additionally, the disclosed system combines the forecasted source attributes to generate a plurality of forecasted emissions value modifications for a future time period. The disclosed system generates action recommendations for modifying the physical emissions sources based on the forecasted emissions value modifications. In additional embodiments, the disclosed system tracks emissions of the entity during the future time period and generate additional action recommendations in response to detecting deviations from forecasted emissions production.

An intellectual quality management method is disclosed. A heatmap risk interface is created according to the required data and the parameter configuration which are calculated using a time dependent risk priority number (RPN) equation. An intellectual audit scheduling algorithm is defined via the heatmap risk interface to automatically generate at least one audit plan. An audit program corresponding to the audit plan is performed and a plurality of problem points are selected. Intellectual root cause category recommendation is performed to the questions points. intellectual corrective actions and preventive action recommendations are performed to the problem points according to the intellectual root cause category recommendation to obtain at least one optimum corrective action and at least one preventive action. Corrective actions are performed to each audit unit according to the corrective action to solve the problem points and prevention actions are performed to each audit unit according to the preventive action.

A cargo-neutral climate control diagnostic system for a climate controlled mobile container includes a controller configured and disposed to be connected to one or more climate control components. The controller is configured and disposed to identify a cargo-neutral test opportunity and conduct a test to determine an operational state of the one or more climate control components of the climate controlled mobile cargo container while maintaining a desired environment.