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Industrial statistics is the application of statistics in precision industries, the most common one of which is product quality control. Evaluating product quality usually requires product life tests to collect related information after using the product, and then a set of quality control standards are established based on the statistically analyzed data to meet the market demand. On the other hand, to efficiently and precisely control product operation in terms of quality control, the statistical experiment design is often required to evaluate preceding tests for the purpose of cost saving or enhancing the precision of highly reliable evaluations. The institute emphasizes experimental design and the Taguchi method in terms of studies on industrial statistics, but has mainly adopted product reliability analysis in recent years. Following technological development, product reliability has become an important basis for the requirements of consumers and manufacturers toward the products of different brands. Reliability means the probability that a product will be available for use within a specific time under certain conditions. Highly reliable products require a longer time to observe the failure information of the processing life test. Furthermore, due to high production costs, too much time and cost would be spent to observe enough data to inspect product reliability. Therefore, the accelerated life test is generally adopted to shorten the test time. Meanwhile, engineers or quality control personnel usually can provide product reliability associated information with an extensive understanding on the product’s process and quality from practical experiences. Currently, the reliability research of the institute is focused on Bayesian Reliability Analysis for accelerating life tests and competitive risks. |
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Statistical process control (SPC) provides tools for maintaining the quality of products in a mass production process. Basic techniques for SPC include control charts (Shewhart chart, Range chart, np-chart), process capability analysis, tolerance limits and the assessment of the average run length. More research oriented techniques include control charts for correlated data (EWMA chart, Copula-based chart), multivariate control charts, and profile monitoring. |
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Biostatistics 
