Abstract
Control chart is a useful statistical tool for the production process control to maintain the product value at the standard. The objectives of this research were to propose the Tukey Moving Average - Double Exponentially Weighted Moving Average control chart (MMD-TCC chart) to detect the change of mean in the symmetric and non-symmetric distribution, and to compare the effectiveness of the change detection of MMD-TCC with that of MA, DEWMA, MMD, MDM, TCC, and MDM-TCC at the different parameter levels. ARL <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and MRL criteria were used to measure the efficiency by applying Monte Carlo (MC) simulation. Research results indicated that the change of mean in process under the control where ARL <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 370 with MMD-TCC was more efficient to detect the change than other control charts unless it was the symmetric distribution with the change of parameter at ±1.50, ±2.00, ±3.00, ±4.00, and the non-symmetric distributions with the change of parameter at 3.00, 4.00 with MA control chart. Furthermore, by applying the proposed control chart to real data, it was found to be in accordance with the research results from simulation technique.
Highlights
Statistical quality control is the key strategy for product and service quality retention in the production process to meet the standard required by the manufacturer and consumers
The distributions that were applied to this research involved the symmetric distributions which were normal (0,1), Laplace (0,1) and Student’s t (10), and the non-symmetric with right-skewed distribution which were exponential (1) and gamma (4,1), as well as the Average Run Length (ARL) and Median Run Length (MRL), which were the criteria for comparing the detection efficiency
The results showed that the data had the normal distribution, exponential distribution and gamma distribution respectively
Summary
Statistical quality control is the key strategy for product and service quality retention in the production process to meet the standard required by the manufacturer and consumers. That being said it is the standard offering the ultimate satisfaction to the consumers and the optimal profit in long term to the manufacturer so the enterprise can survive. Quality control applies the statistical approach to calculate and the results are used for-making a decision on quality of product, such as product development to meet the manufacturer standard and the product standard development to be competitive. Control chart is the acceptable statistical tool that is significant as it analyzes and examines the abnormalities of the production process and projects its status .
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