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Undertakes a comparative study of the statistical capability of three spreadsheets which are commonly used in the business sector. The spreadsheets considered are Lotus 1‐2‐3, Microsoft Excel and Quattro Pro. Considers five areas of statistical analysis regularly used by business decision makers (rather than specialist personnel). In order to obtain an objective measure of the statistical provision of each spreadsheet, comparison has also been made with dedicated statistical software regularly used by business decision makers, namely MINITAB. By making this comparison, argues that the spreadsheet is not only a tool for analysis, but also for presentation. Moreover, considers that two spreadsheets in particular, namely Excel and Quattro Pro, offer a user‐friendly statistical provision which should be sufficient for most business decision makers.

The current evaluation standards in German higher education institutions (HEIs) do not often lead to measurable quality improvement. The purpose of this paper is to critically evaluate whether Kaizen can improve the quality of teaching. The presented concept illustrates the evaluation of each course unit to continuously encourage quality feedback from the learners and intensify the exchange with lecturers.

Action research is used to combine the continuous improvement philosophy of Kaizen with student course evaluations. A pilot study of the concept provides data from four course cycles to analyze learnings and setbacks.

Learners in the pilot courses welcomed the intense participation and allowed improvements to elements such as course concept, course material, presentation style and content or detail selection. The participation rate declined during each term and was highly influenced by triggers like exam and grade relevance. Kaizen could successfully improve course quality, especially in the first two years of newly developed courses.

The presented results have been collected from one course over four years in one institution. The next stage of research would be the application of the approach in other institutions to validate results and make potential adjustments to the concept, for example, toward continuous learning.

Although course evaluation has become standard in German HEIs, most institutions only implement it once per term or year. This paper discusses a new approach to expedite the evaluation of teaching quality at the point of action (Gemba) to facilitate the short-term reactions of lecturers.

The growth and prosperity of a nation depends upon its ability to innovate technologically and engineering has erupted as a fundamental chauffer of this essence, since last couple of eras. But recent decline in engineering admissions triggers the downfall in skilled labor, which can cause recession in industries or can ultimately lead to economic crisis. This study tries to illustrate the present status of engineering-related education, particularly in India and tends to skim the various parameters that affect the enrollment of students among higher education institutes, directly or indirectly.

A unique approach had been unleashed to tackle the nuisance of low admission among Indian engineering colleges or universities. Factors reviewed from the literature were further prioritized quantitatively after distributing suitable questionnaires among a relevant set of engineering aspirants. The “survey form” used was tactically designed on the basis of response surface methodology (RSM), which analyzed the data captured in Minitab statistical software and deducted logical inferences to optimize the “critical-to-admission” (CTA) factors, applicably.

A case study was successfully executed in a North Indian state to prove the efficacy of proposed methodology as far as downtrend in admission was concerned. This study was a rare blend of questionnaire-based work, where design of experiments principles had been utilized exclusively. It provided significant findings on how to earmark different admission-decisive factors along with their required prioritization.

It can further help the universities and higher education institutes to draft their indispensable professional policies and vision–mission statements, appropriately.

Quantitative studies in the service sector (like higher education) are quite rare to see. The present work is not only providing a roadmap for engineering institutions to boost their admissions in upcoming challenging times but it also acts as a light house for new students as it provides necessary guidelines for shortlisting colleges or universities while seeking admission for higher studies.

The purpose of this paper is to analyze the significance of disparate design variables on the mechanical properties of the composite laminate. Four design variables such as stacking sequence, stacking angle, types of resins and thickness of laminate have been chosen to analyze the impact on mechanical properties of the composite laminate. The detailed investigation is carried out to analyze the effect of a carbon layer in stacking sequence and investigate the impact of various resins on the fastening strength of fibers, stacking angles of the fibers and the thickness of the laminate.

The Taguchi approach has been adopted to detect the most significant design variable for optimum mechanical properties of the hybrid composite laminate. For this intend, L16 orthogonal array has been composed in statistical software Minitab 17. To investigate an effect of design variables on mechanical properties, signal to noise ratio plots were developed in Minitab. The numerical analysis was done by using the analysis of variance.

The single parameter optimization gives the optimal combination A₁B₁C₄D₂ (i.e. stacking sequence C/G/G/G, stacking angle is 00, the type of resin is newly developed resin [NDR] and laminate thickness is 0.3 cm) for tensile strength; A₄B₂C₄D₂ (i.e. stacking sequence G/G/G/C, stacking angle is 450, the type of resin is NDR and laminate thickness is 0.3 cm) for shear strength; and A₂B₃C₄D₂ (i.e. stacking sequence G/C/G/G, stacking angle is 900, the type of resin is NDR and thickness is 0.3 cm) for flexural strength. The types of resins and stacking angles are the most significant design variables on the mechanical properties of the composite laminate.

The novelty in this study is the development of new resin called NDR from polyethylene and polyurea group. The comparative study was carried out between NDR and three conventional resins (i.e. polyester, vinyl ester and epoxy). The NDR gives higher fastening strength to the fibers. Field emission scanning electron microscope images illustrate the better fastening ability of NDR compared with epoxy. The NDR provides an excellent strengthening effect on the RCC beam structure along with carbon fiber (Figure 2).

Various test methods are used to characterize PCB plated‐through‐hole reliability. One such method is the interconnect stress test. The results from this test are often used to qualify PCB materials and/or fabricators. This paper will discuss how certain statistical analysis techniques may be used to decipher the results, and predict capabilities of PCB materials and/or processes.

Nowadays companies in the world are selling products by keeping quality as a central value for the customer. Quality-related costs arise from a series of activities performed in order to maintain the quality of product or service. Like other activities of business, quality costs can be programmed, budgeted, measured and analysed to attain the objective of better quality at lower cost. The purpose of this paper is to formulate a decisive methodology to optimize total quality cost (TQC), comprehensively.

The TQC borne by any small- and medium-sized enterprise (SME) is the authentic base, which decides budget and other financial policies for running its ongoing quality programmes. To minimize TQC, one has to make sufficient cut backs in the total failure cost (TFC). Through regression analysis, TFC has been statistically modelled with primary quality costs (like preventive costs (PC) and appraisal costs (AC)). Subsequent graphical analysis has been delineated to elaborate relevant behaviour of different quality costs. At last, potency of suggested methodology has been strategically verified by executing a successful case study in an Indian Auto SME. The requisite optimization has been achieved by using Minitab Statistical Software and its practical validation is checked by conducting a two-sample t-test, exclusively.

It has been found that TFC has a direct positive correlation with TQC and it increases with time. Further, TFC is inversely proportional with PC and AC. PC and AC act as independent costs, while TFC is a dependent or secondary quality cost. If the authors strategically allocate PC and AC in advance by using statistical advanced tools, then internal failure costs and external failure costs will diminish amply.

It inspires practitioner to harvest profits by inculcating quality cost optimization through lodged statistical behavioural investigation. Proposed approach is verified after performing an empirical study only on an automobile manufacturing SME. Further research is indeed required to testify the given methodology for more complex process configurations.

Data related to quality costs is well available with practitioners but generally lying ignored. The case findings will motivate quality practitioners to use the proposed step by step approach for sustainable reduction in overall quality cost.

SMEs find it difficult to lower their TQC due to severe scarcity of resources and funds. Moreover literature provides mainly the theoretical or qualitative cases which remain ineffective to propel SMEs towards the real world savings. But this manuscript will act as a unique road-map to de-code the behaviour of different quality costs quantitatively without ignoring the existing constraints of SMEs, especially in the developing nations.

Six Sigma as a powerful business strategy has been around for almost a decade and has grown exponentially in healthcare industry during the past five years. During the last five years or so, many leading healthcare institutions have implemented Lean and Six Sigma methodologies with remarkable results in terms of reducing ER cycle time, increasing timely completion of medical records, increasing bed availability, improving patient flow, enhancing patient safety, increasing capacity of the theatres, reducing medication errors and so on and so forth. The purpose of this paper is to reduce patient waiting time in a pathology department of a super-specialty hospital attached to a manufacturing company. The average waiting time for patients was estimated to be around 24 minutes with a standard deviation of 17.5 minutes. This was not acceptable in the eyes of patients, and hence, it was highly desirable to understand the reasons for excessive waiting times as well as the root causes of variation in the waiting times.

The Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) methodology was adopted for reducing the average waiting time and variation in waiting times.

During the execution of this case study, a number of non-value added activities were identified within the process and actions were initiated to systematically eliminate different forms of waste using the principles of Lean thinking. Cause-and-effect analysis was carried out to identify the potential causes for unacceptable waiting times and data were collected to validate these causes. The tools such as hypothesis test, box plot, dot plot etc. were used to analyse the data through Minitab statistical software and conclusions were made. As a result of this project, the average waiting time reduced from 24 minutes to 11 minutes (i.e. over 50 per cent reduction), the standard deviation reduced from 17.5 minutes to 10.04 minutes(over 40 per cent reduction).

This paper highlights the use of data driven and scientific problem solving methodology such as Six Sigma with the involvement of hospital staff members like nurses, clinicians and technicians. The results of the case study have provided greater stimulus among the senior management team for deploying the use of DMAIC methodology for tackling process and patient care related problems in the hospital.

The purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.

The contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.

The optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.