Optimal linear combination of poisson variables for multivariate statistical process control

In this paper we analyze the monitoring of p Poisson quality characteristics simultaneously, developing a new multivariate control chart based on the linear combination of the Poisson variables, the LCP control chart. The optimization of the coefficients of this linear combination (and control limit) for minimizing the out-of-control ARL is constrained by the desired in-control ARL. In order to facilitate the use of this new control chart the optimization is carried out employing user-friendly Windows© software, which also makes a comparison of performance between this chart and other schemes based on monitoring a set of Poisson variables; namely a control chart on the sum of the variables (MP chart), a control chart on their maximum (MX chart) and an optimized set of univariate Poisson charts (Multiple scheme). The LCP control chart shows very good performance. First, the desired in-control ARL (ARL0) is perfectly matched because the linear combination of Poisson variables is not constrained to integer values, which is an advantage over the rest of charts, which cannot in general match the required ARL0 value. Second, in the vast majority of cases this scheme signals process shifts faster than the rest of the charts.This work has been supported by the Ministry of Education and Science of Spain, research project number DPI2009-09925, the CNPq (the Brazilian Council for Scientific and Technological Development), project numbers 302326/2008-1 and 473706/2010-5, and SENESCYT-Ecuador (National Secretary of Higher Education, Science, Technology and Innovation of Equator). The authors are grateful to the referees for their comments, which led to significant improvement of the paper.Kahn Epprecht, E.; Aparisi García, FJ.; García Bustos, SL. (2013). Optimal linear combination of poisson variables for multivariate statistical process control. Computers and Operations Research. 40(12):3021-3032. https://doi.org/10.1016/j.cor.2013.07.007S30213032401

Optimum Multiple and Multivariate Poisson Statistical Control Charts

This paper deals with the simultaneous statistical process control of several Poisson variables. The practitioner of this type of monitoring may employ a multiple scheme, i.e. one chart for controlling each variable, or may use a multivariate scheme, based on monitoring all the variables with a single control chart. If the user employs the multivariate schemes, he or she can choose from, for example, three options: (i) a control chart based on the sum of the different Poisson variables; (ii) a control chart on the maximum value of the different Poisson variables; and (iii) in the case of only two variables, a chart that monitors the difference between them. In this paper, the previous control charts are studied when applied to the control of p = 2, 3 and 4 variables. In addition, the optimization of a set of univariate Poisson control charts (multiple scheme) is studied. The main purpose of this paper is to help the practitioner to select the most adequate scheme for her/his production process. Towards this goal, a friendly Windows (c) computer program has been developed. The program returns the best control limits for each control chart and makes a complete comparison of performance among all the previous schemes.This work has been supported by the Ministry of Education and Science of Spain, research project number DPI2009-09925, the CNPq (the Brazilian Council for Scientific and Technological Development), project numbers 302326/2008-1 and 473706/2010-5, and SENESCYT-Ecuador (National Secretary of Higher Education, Science, Technology and Innovation of Equator). The authors are grateful to the referees for their comments, which led to significant improvement of the paper.Aparisi García, FJ.; García Bustos, SL.; Kahn Epprecht, E. (2014). Optimum Multiple and Multivariate Poisson Statistical Control Charts. Quality and Reliability Engineering International. 30(2):210-219. https://doi.org/10.1002/qre.1490S21021930

Bond of Reinforcement in Concrete Applied to Concrete Quality Control: The Bottle Bond Test

This paper presents the results of an experimental research dealing with bond strength as a parameter for concrete quality control. To this end, a low-cost testing technique has been developed: the Bottle Bond Test (BBT). Specimens for the BBT are produced by casting concrete into empty plastic bottles (used as moulds) with a reinforcing bar longitudinally centred. The result is a bottle-shaped concrete specimen with an embedded rebar, which is pulled out to determine bond strength. Different parameters related to this test setup modify bond strength: their effect has been analyzed. An equation to relate the obtained bond strength values to concrete compressive strength is presented. This equation has been validated with real production data from a readymix concrete plant. Its accuracy and therefore the feasibility of BBT for concrete quality control have been verified. Therefore, the BBT can be an alternative to conventional concrete quality based on uniaxial compression tests