Abstract: The method includes determining a plurality of metrics for the project, the project having a plurality of subprojects. The method also includes accessing data for each metric from the plurality of metrics, the data concerning a subproject from the plurality of subprojects. The method also includes building a table having the data for a metric matched to the subproject. The method also includes calculating a numerical score based off of the table that represents progress of a first subproject relative to a second subproject with regard to the metric. The method also includes creating a visualization that includes the plurality of metrics and the numerical score of the first subproject.

Abstract: The method includes determining a plurality of metrics for the project, the project having a plurality of subprojects. The method also includes accessing data for each metric from the plurality of metrics, the data concerning a subproject from the plurality of subprojects. The method also includes building a table having the data for a metric matched to the subproject. The method also includes calculating a numerical score based off of the table that represents progress of a first subproject relative to a second subproject with regard to the metric. The method also includes creating a visualization that includes the plurality of metrics and the numerical score of the first subproject.

Abstract: The method includes determining a plurality of metrics for the project, the project having a plurality of subprojects. The method also includes accessing data for each metric from the plurality of metrics, the data concerning a subproject from the plurality of subprojects. The method also includes building a table having the data for a metric matched to the subproject. The method also includes calculating a numerical score based off of the table that represents progress of a first subproject relative to a second subproject with regard to the metric. The method also includes creating a visualization that includes the plurality of metrics and the numerical score of the first subproject.

Abstract: Methods, systems, and computer program products for implementing product randomization and analysis in a manufacturing environment are provided. A method includes processing products for a plurality of lots, at process equipment, using a randomization technique for selecting each product in the lots. The method further including generating an operation identification record for each operation in the process recipe that includes mapping, for each operation, a slot identifier associated with a randomly selected product to a process variable identifier, a process tool, and the operation. The method also includes defining slot groupings using slot identifiers for a product carrier and identifying product yield patterns by analyzing historical yields for each of the slot groupings.

Abstract: A method of optimizing production cycle queue time includes selecting a plurality of process steps for a production cycle, calculating queue times for each of the plurality of process steps, statistically analyzing the queue times, and generating at least one visual output that illustrates the statistically analyzed queue times.

Abstract: A method of optimizing production cycle queue time includes selecting a plurality of process steps for a production cycle, calculating queue times for each of the plurality of process steps, statistically analyzing the queue times, and generating at least one visual output that illustrates the statistically analyzed queue times.

Abstract: Methods, systems, and computer program products for implementing product randomization and analysis in a manufacturing environment are provided. A method includes processing products for a plurality of lots, at process equipment, using a randomization technique for selecting each product in the lots. The method further including generating an operation identification record for each operation in the process recipe that includes mapping, for each operation, a slot identifier associated with a randomly selected product to a process variable identifier, a process tool, and the operation. The method also includes defining slot groupings using slot identifiers for a product carrier and identifying product yield patterns by analyzing historical yields for each of the slot groupings.