Abstract: A method, system, and computer program product for determining carbon footprint for one or more products assembled by an assembly unit by receiving measurement data generated by at least one product counter sensor configured to detect a number of products assembled by the assembly unit over time; determining a number of assembled products in a period of time, based on the measurement data generated by the at least one product counter sensor; receiving measurement data generated by at least one energy supply sensor configured to measure an amount of energy being supplied to the assembly unit over time; determining an amount of supplied energy in the period of time, based on the measurement data generated by the at least one energy supply sensor; obtaining energy carbon footprint information representing an amount of greenhouse gas released into the atmosphere for generating the amount of energy being supplied to the assembly unit; estimating an amount of greenhouse gas released into the atmosphere for generati

Abstract: Computer-implemented methods and systems for predicting a cost estimate of a query manufactured component are provided. An example method involves operating at least one processor to: receive a query defining desired features for the query manufactured component; determine, using a predictive model, at least one cost estimate for the query manufactured component based on the query; and display, via a user interface, the at least one cost estimate for the query manufactured component. The desired features can include at least one of: a component type, a size, and a material for the query manufactured component.

Abstract: A method for inspecting a part in a manufacturing environment, the method including: acquiring at least one image of the part; optionally enhancing the at least one image; automatically analyzing the enhanced image to determine if the part has a potential defect; if it is determined that there is a potential defect: displaying the at least one image to an operator; and receiving operator input of a part status, wherein the part status may be defect or no defect; and storing the part status in association with the at least one image. The automatic analysis may include a confidence level and only images having a confidence level that does not meet a threshold will be displayed to an operator.

Abstract: A method for triggering a training event in a manufacturing line having at least one automation element, the method including: receiving automation data associated with the at least one automation element; detecting a trigger event based on the automation data; determining a training component associated with the trigger event; and providing access to the training component to an end user. A system for triggering a training event in a manufacturing line having at least one automation element, the system including: a data acquisition module configured to receive automation data associated with the at least one automation element; a data collection device trigger configured to detect a trigger event based on the automation data; a training module configured to determine a training component associated with the trigger event; and a notification module configured to provide access to the training component to an end user.

Abstract: The disclosure is directed at a method and system for diagnosing automation elements. The method and system include the determination of a trigger condition or event within operation data received from the automation elements. Based on the trigger condition or event, feed-back data captured by data collection devices is tagged and stored and/or captured and stored for review by an end user. The feed-back data may be stored together with associated operation data to assist in identifying faults, the causes of faults, or the like in the automation elements, in the products produced, or in the manufacturing process or overall manufacturing system.

Abstract: A method for inspecting a part in a manufacturing environment, the method including: acquiring at least one image of the part; optionally enhancing the at least one image; automatically analyzing the enhanced image to determine if the part has a potential defect; if it is determined that there is a potential defect: displaying the at least one image to an operator; and receiving operator input of a part status, wherein the part status may be defect or no defect; and storing the part status in association with the at least one image. The automatic analysis may include a confidence level and only images having a confidence level that does not meet a threshold will be displayed to an operator.