Logistics and supply chain planners striving to maintain smooth business functions and prevent production disruptions...
may find Statistical Process Control (SPC) helpful. SPC is a process improvement tool available in the Quality Management component of the SAP ERP system that production planners can integrate into their existing production processes.
Consider a company that produces bakery products. One of the critical process parameters to watch for or closely monitor is the process temperature. A lower-than-desired process temperature leads to underbaked products and a higher temperature leads to overbaked or burnt products, which results in waste and supply chain disruption. SPC can help quickly identify when a process is out of control or at risk of getting out of control. Companies account for normal or routine disruptions (known as dispersions) to business processes and establish preventive measures. However, they typically do not have preventive measures in place for abnormal disruptions. If SPC is in place when a process parameter begins drifting into an abnormal, out-of-control zone, the person managing the process can take immediate action to rectify the situation.
Figure 1 is a sample chart from the SAP SPC tool. The chart shows a concentration of data points on the left side that are in the normal range for the process in question. Then the values ascend to an abnormally high point of 165, at which point someone took corrective action, and the value drops off to 94, which is within the normal range again.
Companies can widen the scope of SPC, integrating it not just into their production processes but also into their procurement and sales processes. In the procurement process, for example, the process parameter being monitored could be the physical strength of a steel bar that the company has procured. All steel bars must fall within specific tolerance limits for physical strength, and upon exceeding those limits, the SPC tool can provide the necessary alerts to minimize production and supply chain disruptions.
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