Quality Control - An Approach Applying Multivariate Control Charts during the Operation of Systems Involving Human Processes Open Access

Quality assurance during the operation of a system is critical for maintaining performance within desired specifications. Without proper monitoring and control, a system is capable of erratic behavior resulting in degraded performance, unplanned downtime for maintenance, or system failure. Statistical analysis has proven useful when appropriately applied for quality control activities, as is evidenced within the manufacturing industry. The collection of statistical techniques commonly applied to evaluate the performance of systems and/or processes is known as statistical process control. This paper presents an approach concerning the statistical process control technique of control charting, demonstrating its applicability to controlling and monitoring operational systems involving human processes with multiple quality characteristics. Typical control chart application assumes a normal distribution for analyzed data and sufficient data points necessary to collect an appropriately sized sample. The novelty of the proposed approach is in the intent of monitoring the overall operation of a process, focusing on initial inputs and final outputs, while utilizing 100% of process-generated data from systems where the operational pace does not lend to the collection of large amounts of data points. In this paper, the proposed approach is demonstrated through application to a corporate information technology help desk as well as through simulation. The approach presented within this paper would be beneficial to multiple industries and organizations for evaluation of the quality of systems consisting of human-involved processes.

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