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The Industrial Production Index (IPI) is an economic indicator published by the Federal Reserve Board of the United States that measures the real production output of manufacturing, mining, and utilities.
Simple example of a process control chart, tracking the etch (removal) rate of Silicon in an ICP Plasma Etcher at a microelectronics waferfab. [1] Time-series data shows the mean value and ±5% bars. A more sophisticated SPC chart may include "control limit" & "spec limit" % lines to indicate whether/what action should be taken.
Overall labor effectiveness (OLE) is a key performance indicator (KPI) that measures the utilization, performance, and quality of the workforce and its impact on productivity. Similar to overall equipment effectiveness (OEE), OLE measures availability, performance, and quality.
A performance indicator or key performance indicator (KPI) is a type of performance measurement. [1] KPIs evaluate the success of an organization or of a particular activity (such as projects, programs, products and other initiatives) in which it engages. [ 2 ]
An OEE of 100% means that only good parts are produced (100% quality), at the maximum speed (100% performance), and without interruption (100% availability). Measuring OEE is a manufacturing best practice. By measuring OEE and the underlying losses, important insights can be gained on how to systematically improve the manufacturing process.
Control charts are graphical plots used in production control to determine whether quality and manufacturing processes are being controlled under stable conditions. (ISO 7870-1) [1] The hourly status is arranged on the graph, and the occurrence of abnormalities is judged based on the presence of data that differs from the conventional trend or deviates from the control limit line.
Performance – compares the ideal output and the actual output. For example, if a certain process is planned to take 10 minutes, but actually takes 20, then the productivity is 50%. [3] Quality – to show the quality of a product, a company has to compare the number of good parts produced with the total parts produced.
In the long term, processes can shift or drift significantly (most control charts are only sensitive to changes of 1.5σ or greater in process output). If there was a 1.5 sigma shift 1.5σ off of target in the processes (see Six Sigma), it would then produce these relationships: [5]