Mohammad Shamsuzzaman

Development of a multiattribute synthetic-np chart

Over the last few decades, multiattribute control charts have been widely recommended in practice. They outperform the simultaneous uniattribute charts for monitoring multiattribute processes in many applications. Jolayemi [A statistical model for the design of multiattribute control charts. Indian J Stat. 1999;61:351–365] developed a statistical model for the design of a multiattribute np (Mnp) chart. Based on this model, a multiattribute synthetic (MSyn) chart is proposed in this article. Furthermore, the main features of the MSyn chart and Mnp chart are integrated to build a multiattribute Syn-np (MSyn-np) chart. The results of the comparative studies indicate that the new MSyn-np chart significantly outperforms the Mnp chart and MSyn chart by 83% and 27%, respectively, in terms of the average number of defectives over a wide range of process shifts under different circumstances.

An optimisation design of the combined np-CUSUM scheme for attributes

The np chart and the binomial cumulative sum (CUSUM) chart are attribute charts that monitor the fraction non-conforming p. While the np chart is effective for detecting large process shifts in p, the CUSUM chart is more powerful for detecting small and moderate p shifts. This article presents an optimisation algorithm for the design of the combined np chart and CUSUM chart (the np-CUSUM scheme). This design algorithm not only optimises the charting parameters of the np chart element and CUSUM chart element, but also optimises the allocation of detection power between the two chart elements, so that the best overall performance can be achieved. The np-CUSUM scheme has the salient features of the np chart and the CUSUM chart. The performance of the np-CUSUM scheme is compared with that of other charts in a systematic and quantitative manner. The results show that the optimal np-CUSUM scheme always outperforms, or at least performs equally as, the individual np chart, CUSUM chart and binomial exponentially weighted moving average (EWMA) chart by 222%, 5% and 11%, respectively, in terms of the average number of defectives (AND), under different conditions. [Received 30 November 2010; Revised 21 February 2011; Accepted 3 May 2011]

Design of EWMA control chart for minimizing the proportion of defective units

Purpose – The exponentially weighted moving average (EWMA) control charts are widely used in industries for monitoring small and moderate process shifts. The purpose of this paper is to develop an algorithm for the optimization design of the EWMA chart (known as MD‐EWMA chart).Design/methodology/approach – The design algorithm adjusts the sample size n, sampling interval h, lower and upper control limits LCL and UCL, and the EWMA weight factor λ of the chart in an optimal manner in order to minimize the mean number of defective units (denoted as MD) produced per out‐of‐control case. The probability distribution of the random process shift (e.g. mean shift δ) is taken into account that may be modeled by a Rayleigh distribution based on the sample data acquired during the operation of the control chart.Findings – The results of the comparison studies and an example show that the proposed MD‐EWMA chart is significantly superior to the Shewhart‐type MD‐X¯ chart and the other EWMA charts in terms of the overal...

Improving reliability of repairable systems using preventive maintenance and time-between-failures monitoring

The purpose of this article is to investigate how to assess the rate of occurrence of failure (ROCOF) of a multi-component repairable system and improve its reliability. A procedure was developed and tested on closed-circuit television dome cameras operated in an airport in the United Arab Emirates. Optimum replacement times for critical components were calculated, and then a practical preventive maintenance schema was suggested to reduce the overall cost. Finally, a control chart was developed to monitor the time between failures (TBFs) on the basis of the calculated ROCOF. The results of the case study show that optimising the maintenance renewal intervals generated a saving of approximately 77% in maintenance costs, reduced the ROCOF by approximately 94%, and increased the level of planned maintenance by approximately 97%. Furthermore, monitoring the TBFs of repairable systems could detect changes that might lead to failures over time, thus improving the reliability and ensuring the effectiveness of preventive maintenance. [Received 12 April 2015; Revised 27 December 2015; Revised 3 March 2016; Accepted 18 March 2016]

Using Lean Six Sigma to improve mobile order fulfilment process in a telecom service sector

Abstract This study proposes and follows a specific and systematic framework for implementing Lean Six Sigma (LSS) methodology in a telecom company in order to improve customer satisfaction by minimizing the company’s response time to customer requirements. The goal of this study was achieved by utilizing several LSS tools under five phases of the DMAIC methodology. Unlike previous studies in the telecom sector that used only qualitative method, in this study, both qualitative and quantitative methods were utilized to draw meaningful conclusions. As a result of the implementation of the LSS methodology, the average order fulfilment lead time for sales orders (SO) and value-added service (VAS) orders was reduced from 10.3 to 5.9 days and from 1.5 to 0.5 days, respectively. The reduction in lead time resulted in an increase in the sigma level for SO and VAS orders from 0.44 to 1.26 and from 0.73 to 2.66, respectively. These improvements were expected to lead to a financial benefit in savings of over

EWMA control chart that minimizes the numbers of defectives for out-of-control cases

600,000 per year in operational costs, enhancements to customer experience and an increase in revenue generating opportunities. Moreover, this article enriches the existing literature on the application of LSS concept in the service industry, and helps the company to speed up the response to customer requirements.

Design of economic X̄ chart for monitoring electric power loss through transmission and distribution system

This article develops an algorithm for the optimization design of Exponentially Weighted Moving Average (EWMA) control charts. The design algorithm adjusts the sample size, sampling interval and control limits of the chart in an optimal manner in order to minimize the mean number of defective units (denoted as MD) produced per out-of-control case. The optimal chart is therefore named as the MD-EWMA chart. The probability distribution of the random process shifts (e.g. mean shift) is taken into account and is modeled by a Rayleigh distribution based on the sample data acquired during the operation of the control chart. Unlike the economic control chart designs, the design of the MD-EWMA chart only requires limited number of specifications that can be easily determined. The design of the proposed MD-EWMA chart is illustrated through an example.

Sensitivity Analyses of the Economic and Economic Statistical Designs of the Multivariate Synthetic T2 Chart

This article presents a model for the optimisation design of the chart based on Duncan’s model for identifying unusual power loss through transmission and distribution system so that an immediate action can be taken to maintain the power network stability. The model optimises the chart parameters in order to minimise the mean cost of power loss (MLC) under random process shifts (e.g. mean shifts), and ensures that the false alarm probability of the control chart will not exceed the allowable level and extra inspection resources (e.g. operators and measurement instruments) will be avoided. A comparative study based on fractional factorial experiment shows that, from an overall viewpoint, the optimal chart reduces the MLC by about 40% compared to the traditional chart. The effects of design specifications on the charting parameters and optimal MLC of the proposed chart are also investigated through sensitivity analysis. Finally, the design and application of the proposed chart is illustrated through an example. In general, this article will help reduce the cost of power loss and broaden the literature on the application of control chart in the service organisations.

Design of X̅&R control charts for monitoring quality of care for hypertension

This article performs a sensitivity analyses of the synthetic T2 chart using fractional factorial design, which integrates the interaction effects. We are interested in the effects of the input parameters on the optimal cost, charts parameters, and average run lengths. We also look at the input parameters responsible for the increase in cost and improvement in statistical performance under statistical constraints, and investigate how the input parameters influence the binding effect of the statistical constraints. The sensitivity analyses of the synthetic T2 chart are compared with that of the Hotellings T2 chart, and parameters responsible for the cost advantage of the synthetic T2 chart are identified.

Optimization Design of 2-EWMA Control Chart Based on Random Process Shift

The continuous monitoring of chronic diseases such as asthma, hypertension, diabetes and cardiovascular diseases are very important for their effective management. Statistical process control (SPC) tools are being used in many different areas other than manufacturing industries, since they are recommended whenever there is a need for continuous monitoring and improvement. This article designs X̅ & R charts for monitoring diastolic blood pressure (DBP) of a patient for effective management of hypertension. The X̅ & R charts are designed based on patient-generated data at home. Self-monitoring of blood pressure (BP) by patients at home is increasingly being used and appears to be the most appropriate method for the long-term follow-up of treated hypertension. The concept has been discussed and illustrated through a case study. In general, the use of control chart may provide an effective tool for the physician to understand the progress of his patient with a kind of medication, and to modify the treatment plan, if necessary.