JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL
Year:2014 | Volume:10 | Issue:4|Papers Count:8

In this paper, wire electrical discharge machining of D3 tool steel is studied. Influence of pulse-on time, pulse-off time, peak current and wire speed are investigated for MRR, dimensional deviation, gap current and machining time, during intricate machining of D3 tool steel. Taguchi method is used for single characteristics optimization and to optimize all four process parameters simultaneously, Grey relational analysis (GRA) is employed along with Taguchi method. Through GRA, grey relational grade is used as a performance index to determine the optimal setting of process parameters for multiobjective characteristics. Analysis of variance (ANOVA) shows that the peak current is the most significant parameters affecting on multi-objective characteristics. Confirmatory results, proves the potential of GRA to optimize process parameters successfully for multi-objective characteristics.

Process shift is an important input parameter in the economic design of control charts. Earlier x control chart designs considered constant shifts to occur in the mean of the process for a given assignable cause. This assumption has been criticized by many researchers since it may not be realistic to produce a constant shift whenever an assignable cause occurs. To overcome this difficulty, in the present work, a distribution for the shift parameter has been considered instead of a single value for a given assignable cause. Duncan’s economic design model for x chart has been extended to incorporate the distribution for the process shift parameter. It is proposed to minimize total expected loss-cost to obtain the control chart parameters.Further, three types of process shifts namely, positively skewed, uniform and negatively skewed distributions are considered and the situations where it is appropriate to use the suggested methodology are recommended.

The objective of this paper is to present a technique for order preference by similarity to ideal solution (TOPSIS) algorithm to linear fractional bi-level multiobjective decision-making problem. TOPSIS is used to yield most appropriate alternative from a finite set of alternatives based upon simultaneous shortest distance from positive ideal solution (PIS) and furthest distance from negative ideal solution (NIS). In the proposed approach, first, the PIS and NIS for both levels are determined and the membership functions of distance functions from PIS and NIS of both levels are formulated. Linearization technique is used in order to transform the nonlinear membership functions into equivalent linear membership functions and then normalize them. A possible relaxation on decision for both levels is considered for avoiding decision deadlock. Then fuzzy goal programming models are developed to achieve compromise solution of the problem by minimizing the negative deviational variables.Distance function is used to identify the optimal compromise solution. The paper presents a hybrid model of TOPSIS and fuzzy goal programming. An illustrative numerical example is solved to clarify the proposed approach. Finally, to demonstrate the efficiency of the proposed approach, the obtained solution is compared with the solution derived from existing methods in the literature.

Hubs are centers for collection, rearrangement, and redistribution of commodities in transportation networks.In this paper, non-linear multi-objective formulations for single and multiple allocation hub maximal covering problems as well as the linearized versions are proposed. The formulations substantially mitigate complexity of the existing models due to the fewer number of constraints and variables. Also, uncertain shipments are studied in the context of hub maximal covering problems.In many real-world applications, any link on the path from origin to destination may fail to work due to disruption.Therefore, in the proposed bi-objective model, maximizing safety of the weakest path in the network is considered as the second objective together with the traditional maximum coverage goal. Furthermore, to solve the bi-objective model, a modified version of NSGA-II with a new dynamic immigration operator is developed in which the accurate number of immigrants depends on the results of the other two common NSGA-II operators, i.e. mutation and crossover.Besides validating proposed models, computational results confirm a better performance of modified NSGA-II versus traditional one.

The importance in promoting, sustaining industries, manufacturing systems and economy through reliability measurement has become an area of interest. The profit of a system may be enhanced using highly reliable structural design of the system or subsystem of higher reliability. On improving the reliability and availability of a system, the production and associated profit will also increase. Reliability, availability and profit are some of the most important factors in any successful industry and manufacturing settings. In this paper, we compare three different repairable redundant systems using an external supporting device for operation based on the profit. Explicit expressions for the busy period of repairmen, steady-state availability and profit function are derived using linear first-order differential equations. Furthermore, we compare the profit for the three systems and find that system I is more profitable than systems II and III.

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary time series, these non-stationary events will lead to increased level of errors in the forecasting process. This paper generalizes the SES method into a new adaptive method called revised simple exponential smoothing (RSES), as an alternative method to recognize non-stationary level shifts in the time series. We show that the new method improves the accuracy of the forecasting process. This is done by controlling the number of observations and the smoothing parameter in an adaptive approach, and in accordance with the laws of statistical control limits and the Bayes rule of conditioning. We use a numerical example to show how the new RSES method outperforms its traditional counterpart, SES.

The purpose of this paper is to identify the critical success factors influencing the performance of power loom textiles, to evaluate their impact on the organizational performance and to find out the effect of these factors on the organizational performance of small and medium-sized enterprises (SMEs) in the Solapur (Maharashtra) industrial sector using AHP. In the methodology adopted, factors are identified through the literature survey and finalization of these factors is done by taking the opinion of experts in the Indian context. By cognitive map, the relation between these factors (direct and indirect effect) is determined and cause and effect diagram is prepared.Then these factors are arranged hierarchically and tree diagram is prepared. A questionnaire was designed and distributed among the experts; data is collected. Using expert choice software data is filled to quantify by pairwise comparison of these factors and are prioritized. The weights demonstrate several key findings: local and global priority reveals that there is a substantial effect of the human resource, product style, and volume on the organizational performance. The skills and technology upgradation impact on organizational performance. Maintenance plays an important role in improving the organizational performances of the SMEs. Overall, the results showed the central role of the operational factors are important. The research is subject to the normal limitations of AHP. The study is using perceptual data provided by Experts which may not provide clear measures of impact factors. However, this can be overcome using more experts to collect data in future studies. Interestingly, the findings here may be generalisable outside Solapur like Ichalkarnji, Malegaon, and Bhiwadi (Maharashtra). Solapur power loom SMEs should consider AHP as an innovative tool for quantification of factors impacting on performance and improving operational and organizational performance in today’s dynamic manufacturing environment. The finding suggests the notion that these critical success factors (CSFs) are to be studied carefully and improvement strategy should be developed. Moreover, the study emphasizes the need to link priority of factors to organizational performance and improvement. The study integrates the CSFs of performance and its quantification using AHP and its effect on performance of power loom textiles. The indirect impacts of underlying and fundamental factors are considered.Very few studies have been performed to investigate and understand this issue. Therefore, the research can make a useful contribution.

Control charts are extensively used in manufacturing contexts to monitor production processes. This article illustrates economical design of a variable sample size and control limit Hotelling’s T2 control chart based on a novel cost model when occurrence times of the assignable causes are exponentially distributed. The proposed nonlinear cost model is an extension of Duncan’s (J Am Stat Assoc 51: 228-242, 1956) model which was employed for univariate cases. Applying genetic algorithm to find optimum parameter values and using an L33 orthogonal array in sensitivity analysis on the model parameters is investigated through a numerical example to illustrate the effectiveness of the proposed approach.