In this paper, a new method based on group runs (GR) control chart is proposed to enhance the monitoring of simple linear profiles in Phase II. The proposed method is based on simultaneous use of three independent GR control charts developed to monitor intercept, slope and error variance parameters of the simple linear regression model. The individual GR control charts of the proposed method are designed by integrating each of the individual Shewhart-type chart for monitoring intercept, slope and error variance with extended version of the CRL chart and method is referred to as GR Shewhart-3 method. The performance of the proposed GR Shewhart-3 method is evaluated by average run length criterion under sustained shifts of different magnitudes in the intercept, slope and error variance. A comprehensive comparison of proposed method with a number of competing methods is incorporated in the monitoring procedure to identify whether the proposed method has better performance than its main competitors. Simulation results revealed a good performance of the proposed GR Shewhart-3 method. Finally, the implementation of the proposed method is illustrated through an example.

Failure modes and effects analysis (FMEA) is an effective means for detecting and ranking the failure modes related to a particular system. In the literature, a number of shortcomings of FMEA have been reported such as the unreliability of conventional FMEA because in the weightage of risk factors are equal. Due to this, the current paper proposes new hybrid multi-criteria decision-making approaches i.e., fuzzy step wise weight assessment ratio analysis (SWARA) integrated with fuzzy measurement alternative and ranking according to compromise solution (MARCOS), fuzzy SWARA integrated with fuzzy combined compromised solution (CoCoSo) and fuzzy SWARA integrated with fuzzy weighted aggregated sum product assessment (WASPAS) method for prioritising the failure modes. These hybrid models that prioritise failure modes are the newly developed methodologies. The aim of this research study is to develop a hybrid method that prioritises the failure modes based on rational weightage of all risk factors. A case study has been described so as to validate the proposed fuzzy methodologies. The results obtained by these hybrid approaches are nearly equal besides the deviation in the rankings of some failure modes.

Product quality is predicated on the quality of the organisational assets dedicated to producing the product. Productive assets include people, technology, and process. Most often than not, the eventual quality of the products of an organisation is dependent of what the people (human) assets bring to the productive environment. In this regard a commitment to justice, equity, diversity, and inclusion (JEDI) is the forbearer to product quality, which is defined in terms of physical product, service output, or expected result. Many organisations currently pursuing JEDI initiatives do not consider the linkage of JEDI ideals to the desired level of product quality. In this paper, we present how the DEJI systems model can be used as a methodology to advance JEDI initiatives with respect to product quality integration.

The reliability and effectiveness of safety systems in the isomerisation unit of Isfahan refinery complex were evaluated. The methodology consisted of two parts: 1) identification of hazardous scenarios, protection layers, and safety integrity level (SIL); 2) verification of SIL of the system using fault tree analysis (FTA). Out of the 22 identified hazardous scenarios, four scenarios had SIL 1, 17 scenarios had SIL 2, and 1 scenario had SIL 3. The scenario related to stop the outflow of fluid from the pumps with the consequent increase in reaction intensity, rise in temperature, and ultimately the reactor explosion had the most critical points of the production process and SIL 3. In all the scenarios, SIL of the system was in accordance with the required SIL (Target SIL). The results indicated that the intrinsic safe design and use of up-to-date equipment with high reliability led to an acceptable level of risk.

Chemical processes as well as many non-industrial processes exhibit autocorrelation, for which the above-mentioned control procedures are not suitable. This paper considers the problem of monitoring a process in which the observations can be represented as a first-order autoregressive model following a heavy tailed distribution. It also presents practical usage of time series control charts on the chemical process of monitoring concentrations. The second part discusses the effect of autocorrelation on the process capability analysis when the observations are made by an autoregressive model of the first order. The process capability indices provide a measure of how a process fits within the specification limits. When calculating indices, it is usual to assume that the process data are independent. The simulation study in this part discusses the effect of a higher autocorrelation order on process capability indices.

The present study has provided a framework in order to improve the satisfaction of users of e-commerce sites using quality function deployment (QFD) and WebQual instruments. A structural equation model (SEM) has been developed in order to determine the significance of each aspect of the WebQual model and its significance weight. This study has evaluated the satisfaction of users with the quality of website content, transaction quality and security, usability and service interaction quality, and provided the solutions to improve these factors in form of the QFD method. Results showed the transaction quality and security has the highest priority for improvement. Among all the customers' requirements, the indicators such as a wide range of exchanges, preserving privacy, ease of transaction, the right format, ease of search, the usefulness of transactions, and finally the clear and understandable interactions should be placed in a higher priority for improvement by management.