What is meant by statistical throughput control, and how does it differ from statistical process control? Could you use \(\mathrm{SPC}\) tools (i.e., control charts) for throughput tracking?

Statistical Throughput Control (STC) is a technique used to monitor and control the throughput (rate of flow of finished goods) within a production system, such as a manufacturing facility or a supply chain. This is done by collecting real-time data on various factors that affect the efficiency and effectiveness of the process to identify bottlenecks, imbalance, or other issues that may impact the overall throughput.

Statistical Process Control (SPC) is a method used to monitor and control product quality and manufacturing processes through the use of statistical techniques. This is done by collecting, analyzing, and interpreting data on key process variables to identify trends, deviations from the norm, or other indications of possible process problems. The goal of SPC is to ensure that the process is consistent and stable, which in turn leads to consistent product quality.

The main differences between STC and SPC lie in their focus and purpose. STC is concerned with the throughput of the production system, while SPC focuses on product quality and process stability. STC tracks and analyzes factors that impact the overall efficiency and effectiveness of the production system, such as cycle time or inventory levels, to identify bottlenecks or other issues. SPC, on the other hand, monitors process variables to detect variability and deviations from the norm, which can indicate potential problems with product quality or process stability.

Control charts, a popular SPC tool, can indeed be used for throughput tracking. A control chart is a graphical representation of a process variable over time, with control limits set above and below the normal range of variation. When process variable data points exceed these control limits or exhibit non-random patterns, it indicates an out-of-control process that requires investigation. In the context of throughput tracking, control charts can be applied to relevant process variables that impact throughput, such as machine downtime, cycle time, or inventory levels. By monitoring these variables using control charts, potential bottlenecks, imbalance, or other issues affecting throughput can be identified early and corrective actions can be taken to improve throughput. However, it is important to note that utilizing SPC tools for throughput tracking should be complemented by other techniques that focus specifically on throughput management, such as bottleneck analysis, workload balancing, and continuous improvement initiatives.