Performance mapping of equipment performance parameters by capturing, mapping, and/or structuralizing equipment performance data of a device for installation in a system. This includes generating performance maps which outline the expected feature performance parameter behavior of the equipment based on a set of operating parameters that capture the operating conditions. Each performance parameter on the map is representative of an operating point of specific operating conditions taken at a particular point in time. In one example, a performance parameter can be defined by an individualized set of parameter coefficients which in turn are dependent on instantaneous operating conditions. With the performance maps determined individually for devices as part of the system, and stored along with a time of testing, activities such as continuous commissioning, monitoring and verification, preventative maintenance, fault detection and diagnostics, as well as energy performance benchmarking and long term monitoring can be performed.

An exemplary embodiment may include a control hub configured to receive data from an emissions analyzer and a leak detection camera. The emissions analyzer may detect levels of various gases and relay such information to the control hub. In an exemplary embodiment, the emissions analyzer may purge after every test to ensure longevity and accuracy. A leak detection camera may implement quantifying optical gas imaging in order to continuously monitor for fugitive leaks on a compressor package. If a leak is detected, it may be logged and the user or an operating group may be alerted.

A defects management system includes a server, a mobile computing device, and a local hub. The server has a database configured to store a plurality of records that respectively correspond to a plurality of products in an inspection line. The mobile computing device is configured to receive user input indicating a location of a defect on a selected product among the plurality of products. The local hub, in communication with the server, is configured to receive the user input from the mobile computing device and update a record among the plurality of records that corresponds to the selected product to include a defect indication in accordance with the user input.

Performance mapping of equipment performance parameters by capturing, mapping, and/or structuralizing equipment performance data of a device for installation in a system. This includes generating performance maps which outline the expected feature performance parameter behavior of the equipment based on a set of operating parameters that capture the operating conditions. Each performance parameter on the map is representative of an operating point of specific operating conditions taken at a particular point in time. In one example, a performance parameter can be defined by an individualized set of parameter coefficients which in turn are dependent on instantaneous operating conditions. With the performance maps determined individually for devices as part of the system, and stored along with a time of testing, activities such as continuous commissioning, monitoring and verification, preventative maintenance, fault detection and diagnostics, as well as energy performance benchmarking and long term monitoring can be performed.

A method for the automated identification of a product defect of a product and/or for the automated identification of a product defect cause of the product defect, includes producing the product from a plurality of product elements via a plurality of manufacturing steps, and gathering a number n of items of test information by at least one product test, wherein the n items of test information form an n-dimensional test value. The method also includes carrying out a dimension reduction of the n-dimensional test value by at least one statistics process to obtain a dimension-reduced test value, comparing the dimension-reduced test value with a multitude of learned reference values, assigning the dimension-reduced test value to at least one group of reference values that are similar to each other, and identifying, in an automated manner, the product defect and/or the product defect cause on the basis of the assignment.

Systems and other embodiments described herein relate to a defects mangement system that includes a server having a database configured to store a plurality of records that respectively correspond to a plurality of products in an inspection line, a mobile computing device configured to receive user input indicating a location of a defect on a selected product among the plurality of products, and a local hub, in communication with the server, that receives the user input from the mobile computing device and updates a record among the plurality of records that corresponds to the selected product to include a defect indication in accordance with the user input.

A computing system receives a request for computer-generated likelihood(s) for candidate evaluations of an industrial product set according to a measurement system analysis (MSA). The MSA comprises tests for evaluating, according to a measurement standard, the industrial product set. The request indicates a metric set representing metric(s) each quantifying an estimate of contribution to variation in evaluating the industrial product set according to the MSA. The system generates a design comprising a respective input set for each test of the MSA. The respective input set comprises setting(s) for conducting a test of the MSA. The design is designed to isolate candidate sources for contributing to the variation in evaluating the industrial product set according to the MSA. The system (e.g., prior to the MSA) outputs, based on the metric set and the design, the computer-generated likelihood(s) for the candidate evaluations of the industrial product set according to the MSA.

A test specimen for validating operating parameters of a method for the additive manufacturing of a part by laser melting on powder beds includes at least one upper face, at least one lower face and side faces, including a front side face and a rear side face that are substantially on opposite sides from one another. The test specimen has at least one recess opening onto the front and rear side faces, the recess having a substantially triangular cross sectional shape being delimited by three internal faces, including a first lower internal face oriented upwards, a second upper internal face oriented downwards, and a third upper internal face which defines a narrow wall with one other of the side faces, which is inclined.

The present application provides a system and method of monitoring a product packaging. By obtaining an actual weight value and theoretical weight parameters of a target packaging bag and analyzing whether the actual weight value matches the theoretical weight parameters, the target packaging bag is regarded as a packaging failure when the actual weight value fails to match the theoretical weight parameters. In the present application, after product packaging, weighing the packaging bag to obtain the actual weight value and matching the actual weight value for the theoretical weight parameters to realize the monitoring of whether the packaging bag is regarded as the packaging failure.

A computing system receives a request for computer-generated likelihood(s) for candidate evaluations of an industrial product set according to a measurement system analysis (MSA). The MSA comprises tests for evaluating, according to a measurement standard, the industrial product set. The request indicates a metric set representing metric(s) each quantifying an estimate of contribution to variation in evaluating the industrial product set according to the MSA. The system generates a design comprising a respective input set for each test of the MSA. The respective input set comprises setting(s) for conducting a test of the MSA. The design is designed to isolate candidate sources for contributing to the variation in evaluating the industrial product set according to the MSA. The system (e.g., prior to the MSA) outputs, based on the metric set and the design, the computer-generated likelihood(s) for the candidate evaluations of the industrial product set according to the MSA.