APPLICATION OF STATISTICAL PROCESS CONTROL THEORY IN COAL AND GAS OUTBURST PREVENTION

With Chinese coal exploitation extending to depth rapidly, a large number of coal and gas outburst accidents happened and resulted in thousands of casualties in the last decade. Coal and gas outburst prevention project has become the prerequisite of underground coal mining, but its process control ability is especially poor. By integrating statistical process control theory into the process of coal and gas outburst prevention, three urgent problems were solved. First at all, data structure of the process inspection parameters was designed asvectors, which only consisted of principle elements and formed data series as time went by. Secondly, based on sample data of the experimental area, statistical characteristic of inspection parameters was gained and their X-Rs control charts were drawn. Finally, performance of process running statuses that might be in control or beyond control were analyzed in detail. When the process was in control, curves should slightly fluctuate around their center lines and between upper control limits and lower control limits. Otherwise, the process was beyond control, in which X control charts were used to identify anomalies of data value fluctuation and Rs control charts were used to identify anomalies of data fluctuation amplitudes. By the experimental application in Hexi colliery of China, the interdisciplinary research was proved to be helpful to improve process control ability and then prevent coal and gas outburst accidents

Funnel plots for institutional comparisons

We introduce -funnelcompar-, a Stata routine that performs the analysis suggested by David J. Spiegelhalter (Funnel plots for comparing institutional performance, Statistics in Medicine, Volume 24 Issue 8, 1185-1202). The basic idea in funnel plot is to plot performance indicators against a measure of their precision in order to detect outliers. A scatter plot of an indicator level is plotted together with a baseline and control limits, that shrinks as the sample size gets bigger. Our command performs funnel plots for binomial (proportion) poisson (crude and standardized rates) and normal (means) distributed variables. The baseline (and stan- dard errors in case of normal variables) can either be specified by the user (for instance as literature reference) or be estimated from the data as a weighted or non-weighted mean of the data. By default confidence limits are plotted at 2 and 3 standard error, in order to detect alarm and alert signals, as recommended by statistical process control theory. Options have been implemented to mark single institutions, groups of institutions or those institutions lying outside control limits. These plots are increasingly used to report performance indicators at institutional level. Classical league tables imply the existence of ranking between institutions and implicitly support the idea that some of them are worse/better than others. A different approach is possible using statistical process control theory: all institutions are part of a single system and perform at the same level. Observed differences can never be completely eliminated and are explained by chance (common cause variation). If ob- served variation exceed that expected, special-cause variation exists and requires further explanation to identify its cause.

Self Optimizing Control Of An Evaporation Process Under Noisy Measurements

Recently, Cao (2004) presented a decentralized cascade self-optimizing control strategy and implemented on an evaporation process. In this method, the local optimal condition of a self optimizing control system is derived and this optimal condition is expressed as a gradient function in terms of the existing process measurements. This gradient function can then be used as a controlled variable to achieve local self optimization. Good results were obtained subject to noise free measurements but the performance deteriorates when measurement noise presents. This paper presents a method to overcome the detrimental effect of measurement noises on self-optimising control. Filtering the process measurements in conjunction with self-optimising control can reduce the effect of measurement noise on the process performance. The benefit of this method is quantified in terms of the total operating cost reduction compared to non-filtered gradient control. Operating cost comparison of a 10 hour period for various cases subject to the same disturbances clearly shows that the implementation of the proposed strategy reduces the operating cost

Getting high added-value from sampling

Determination of the complete sampling distribution (Lyman, 2014), as opposed to estimation of the sampling variance, represents a significant advance in sampling theory. This is one link that has been missing for sampling results to be used to their full potential. In particular, access to the complete sampling distribution provides opportunities to bring all the concepts and risk assessment tools from statistical process control (SPC) into the production and trading of mineral commodities, giving sampling investments and results their full added-value. The paper focuses on the way by which sampling theory, via the complete sampling distribution, interfaces with production and statistical process control theory and practice. The paper evaluates specifically the effect of using the full sampling distribution on the Operating Characteristic curve and control charts’ Run Length distributions, two SPC cornerstones that are essential for quality assurance and quality control analysis and decision-making. It is shown that departure from normality of the sampling distribution has a strong effect on SPC analyses. Analysis of the Operating Characteristic curve for example shows that assumption of normality may lead to erroneous risk assessment of the conformity of commercial lots. It is concluded that the actual sampling distribution should be used for quality control and quality assurance in order to derive the highest value from sampling

Experimenting with Realism in Software Engineering Team Projects: An Experience Report

Over Several years, we observed that our students were sceptical of Software Engineering practices, because we did not convey the experience and demands of production quality software development. Assessment focused on features delivered, rather than imposing responsibility for longer term `technical debt'. Academics acting as 'uncertain' customers were rejected as malevolent and implausible. Student teams composed of novices lacked the benefits of leadership provided by more experienced engineers. To address these shortcomings, real customers were introduced, exposing students to real requirements uncertainty. Flipped classroom teaching was adopted, giving teams one day each week to work on their project in a redesigned laboratory. Software process and quality were emphasised in the course assessment, imposing technical debt. Finally, we introduced a leadership course for senior students, who acted as mentors to the project team students. This paper reports on the experience of these changes, from the perspective of different stakeholders

Diseño para operabilidad: Una revisión de enfoques y estrategias de solución

In the last decades the chemical engineering scientific research community has largely addressed the design-foroperability problem. Such an interest responds to the fact that the operability quality of a process is determined by design, becoming evident the convenience of considering operability issues in early design stages rather than later when the impact of modifications is less effective and more expensive. The necessity of integrating design and operability is dictated by the increasing complexity of the processes as result of progressively stringent economic, quality, safety and environmental constraints. Although the design-for-operability problem concerns to practically every technical discipline, it has achieved a particular identity within the chemical engineering field due to the economic magnitude of the involved processes. The work on design and analysis for operability in chemical engineering is really vast and a complete review in terms of papers is beyond the scope of this contribution. Instead, two major approaches will be addressed and those papers that in our belief had the most significance to the development of the field will be described in some detail.En las últimas décadas, la comunidad científica de ingeniería química ha abordado intensamente el problema de diseño-para-operabilidad. Tal interés responde al hecho de que la calidad operativa de un proceso esta determinada por diseño, resultando evidente la conveniencia de considerar aspectos operativos en las etapas tempranas del diseño y no luego, cuando el impacto de las modificaciones es menos efectivo y más costoso. La necesidad de integrar diseño y operabilidad esta dictada por la creciente complejidad de los procesos como resultado de las cada vez mayores restricciones económicas, de calidad de seguridad y medioambientales. Aunque el problema de diseño para operabilidad concierne a prácticamente toda disciplina, ha adquirido una identidad particular dentro de la ingeniería química debido a la magnitud económica de los procesos involucrados. El trabajo sobre diseño y análisis para operabilidad es realmente vasto y una revisión completa en términos de artículos supera los alcances de este trabajo. En su lugar, se discutirán los dos enfoques principales y aquellos artículos que en nuestra opinión han tenido mayor impacto para el desarrollo de la disciplina serán descriptos con cierto detalle.Fil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin