Absenteeism is a major challenge for any organization in the current competitive world. Curbing absenteeism helps organizations achieve their targets and increases productivity. This study highlights the major causes of absenteeism in the production division of a garment industry under various dimensions, which influence on absenteeism like work environment, organizational culture, relation and co-operation, compensation and rewards, facilities, job satisfactory and security, and general factors. The Study helps to identify reasons for employee absenteeism in production division. Sample of 180 employees responses were considered for the study from the universe and the data were analysed, statistically. The study shows that the major factors like wages, other source of income, and bad relationship with supervisors were contributing to the major absence of employees from work. This clearly indicates that work environment, relation and co-operation, facilities provided by the organization and job satisfaction were the main components which are causing the employee absenteeism.

The main purpose of this research work is to present a reliability analysis of a two dissimilar parallel unit framework under the presumption that a framework’s unit may also fail during the preventive maintenance (PM). Only one repair man is available with the system. It has been assumed that he is well capable of doing every repair work including preventive maintenance. Here in this work we have assumed that failure and repair times of each unit are correlated. Utilizing regenerative point strategy different reliability attributes are obtained which are very much helpful to system/ framework designers and company managers. Graphical practices of mean time to system failure and profit/cost function have been studied.

Two sets of nine different silicon carbide particulate (SiCp) reinforced Al 7075 Metal Matrix Composites (MMCs) were fabricated using liquid metallurgy stir casting process. Mean particle size and weight percentage of the reinforcement were varied according to Taguchi L9 Design of Experiments (DOE). One set of the cast composites were then heat treated to T6 condition. Optical micrographs of the MMCs reveal consistent dispersion of reinforcements in the matrix phase. Mechanical properties were determined for both as-cast and heat treated MMCs for comparison of the experimental results. Linear regression models were developed for mechanical properties of the heat treated MMCs using list square method of regression analysis. The fabrication process parameters were then optimized using Taguchi based grey relational analysis for the multiple mechanical properties of the heat treated MMCs. The largest value of mean grey relational grade was obtained for the composite with mean particle size 6.18 µm and 25 weight % of reinforcement. The optimal combination of process parameters were then verified through confirmation experiments, which resulted 42% of improvement in the grey relational grade. Finally, the percentage of contribution of each process parameter on the multiple performance characteristics was calculated through Analysis of Variance (ANOVA).

Productivity is an indicator of efficiency with which resources, both human and material, are transformed into useful services and goods. The vital purpose of the prevailing work was to analyze the factors involved in the improvement of productivity in all its types such as material, capital, labor, machine and total productivity at the plant. This was obtained by decreasing the manufacturing cost per component by reducing its cycle time and increasing the monthly production rate. The experimentation revealed that using proposed processes and improved tooling, monthly production rate has increased by 16.2% due to reduced cycle time, the number of defected components i.e. rejection rate has reduced up to 2%. A reduction of 6.78% in manufacturing cost per component was recorded. Tooling cost has reduced by more than 12%. Saving up to 50% in inspection cost has been recorded due to close dimensional tolerances and high surface finish achieved on components. An increase of 4.84% was recorded in total productivity.

This study investigates the role played by service quality at manufacturer-distributor junction in small-medium manufacturing units, and presents a model that proposes and validates that contribution towards service quality on behalf of both the distributor and manufacturer leading to satisfaction as well as loyalty. The research design for this study includes a combination of literature review, exploratory interviews and a questionnaire survey conducted through interview schedule from 101 respondents working in different small-medium manufacturing units (SMEs) of North India. The study uses Structural Equation Modeling (SEM) to develop dual directional scales to measure service quality at manufacturer-distributor junction besides testing a set of propositions related to service quality. A model showing linkages of manufacturing organization’s service quality with distributor service quality leading to mutual satisfaction and loyalty is developed. The model is empirically tested and is found to be fit. This study would be of interest to SME practitioners interested in improving service quality w.r.t. distributors. This study finds support for strengthening relationships with distributors to achieve a win-win situation. Future researchers may validate this scale, and empirically test the proposed model in similar settings. Insights derived from this study may be transferred to other junctions of a manufacturing supply chain such as suppliers, retailers, employees and end customers.

This study deals with the performance modeling and reliability analysis of a redundant machining system composed of several functional machines. To analyze the more realistic scenarios, the concepts of switching failure and geometric reneging are included. The time-to-breakdown and repair time of operating and standby machines are assumed to follow the exponential distribution. For the quantitative assessment of the machine interference problem, various performance measures such as mean-time-to-failure, reliability, reneging rate, etc. have been formulated. To show the practicability of the developed model, a numerical illustration has been presented. For the practical justification and validity of the results established, the sensitivity analysis of reliability indices has been presented by varying different system descriptors.

The present paper emphasizes on the development of a hierarchical model using Fuzzy Multiple Attribute Decision Making (FMADM) method for the selection of E-learning websites. The working of the model developed in this research mainly consists of three steps: (i) Summarization and identification of selection indexes, (ii) Selection indexes weights calculations using Fuzzy Analytical Hierarchy Process (FAHP) and (iii) Ranking of alternatives by implementing three MADM analytical methods as Complex Proportional Assessment (COPRAS), Visekriterijumsko Kompromisno Rangiranje (VIKOR) and Weighted Distance Based Approximation (WDBA). In order to demonstrate the applicability and utility of the proposed methods, an empirical example related to the selection of E-learning websites that are widely used to learn the ‘C’ Programming Language for the software development is carried out. In addition, the results of these three methods are also compared to analyze the critical aspects of the selection indexes. It strongly shows that the developed FMADM model of this paper could be an efficient and effective assessment tool.

The present work predicts the numerical progressive failure response and crack growth of finite plate laminated composites with cutout and multiple cracks under in-plane tensile and compressive loads. The ply to ply failure response of the finite plate is predicted using ABAQUS user define field variables subroutine approach, whereas the extended finite element method is used for examination of crack growth direction for multiple through crack of laminated composite finite plate. The subroutine predicted results are compared and validated with published experimental results and extended finite element method results. The effect of changing mesh size, fibre orientation, crack length, crack inclination angle on failure load, progressive stress intensity factor and damage toughness of various crack types is presented and discussed.

Powder mixed electro discharge machining (PMEDM) is a hybrid machining process where the electrically conductive powder is mixed into the dielectric fluid to enhance the machining efficiency. In this investigation, PMEDM is performed for the machining of AISI 304 stainless steel when silicon carbide powder is mixed into the kerosene dielectric. Peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameter while material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) are considered as response. A face centered central composite design (FCCCD) based response surface methodology (RSM) is applied to design the experiment. A hybrid optimization technique like desirability coupled with fuzzy-logic method is performed to get the optimum level of the multiple performance characteristics. Analysis of variance (ANOVA) is performed for the statistical analysis. The result shows that peak current is the most significant parameter for MRR, TWR and Ra. The optimal setting for maximum MRR, minimum TWR and Ra have been obtained by desirability coupled with fuzzy-logic method.

Optimization of hole-making operations plays a crucial role in which tool travel and tool switch scheduling are the two major issues. Industrial applications such as moulds, dies, engine block etc. consist of large number of holes having different diameters, depths and surface finish. This results into to a large number of machining operations like drilling, reaming or tapping to achieve the final size of individual hole. Optimal sequence of operations and associated cutting speeds, which reduce the overall processing cost of these hole-making operations are essential to reach desirable products. In order to achieve this, an attempt is made by developing an effective methodology. An example of the injection mould is considered to demonstrate the proposed approach. The optimization of this example is carried out using recently developed particle swarm optimization (PSO) algorithm. The results obtained using PSO are compared with those obtained using tabu search method. It is observed that results obtained using PSO are slightly better than those obtained using tabu search method.