Creativity is one of the most important factors to increase the productivity of any organization. There are literally different factors influencing creativity such as physical and non-physical components of a system. There are different studies to confirm that both physical and non-physical issues could impact the efficiency, significantly. The study of this paper considers eleven physical and ten non-physical activities in working environment of six organizations with various business activities of educational, manufacturing and service business. The study summarizes the most and the least important physical and non-physical factors based on some statistical tests

A good facility layout plays an important role on increasing the profitability of a production unit. A good location needs to meet different criteria such as the distance between the plants and the places to reach raw materials, customers, etc. In this paper, we proposed a multi criteria decision making problem to locate a suitable dairy plant. We assume that all factors influencing the plant involves uncertainty and proposed fuzzy numbers to handle the uncertainty associated with all input parameters. We apply the method for a real-world case study of dairy production unit and analyze the results of our proposed model.

Critical path method plays an important role on managing medium to large-scale problems. It is often difficult to determine the critical path for different reasons such as the existing uncertainties in processing tasks. One alternative to handle the uncertainty associated with the processing time is to use fuzzy techniques. We present a new method to calculate the critical path method when the processing times follow trapezoidal fuzzy numbers. The proposed model of this paper does not use any defuzzification technique to find the final processing time. The implementation of the proposed model is compared with other techniques using a well-known example from the literature.

Technical analysis has been one of the most popular methods for stock market predictions for the past few decades. There have been enormous technical analysis methods to study the behavior of stock market for different kinds of trading markets such as currency, commodity or stock. In this paper, we propose two different methods based on volume adjusted moving average and ease of movement for stock trading. These methods are used with and without generalized regression neural network methods and the results are compared with each other. The preliminary results on historical stock price of 20 firms indicate that there is no meaningful difference between various proposed models of this paper.

In this paper, we propose a multi criteria decision making technique to determine an efficient solution for quadratic assignment problem. The proposed method of this paper considers transportation cost, adjacency and separation as the most important criteria to find the efficient layout. A tabu search is used to generate a set of feasible solutions and for each solution, we evaluate various criteria. The proposed model of the paper uses DEA technique to choose the most efficient units among the feasible solutions. The implementation of the proposed method is demonstrated using some benchmark problems and the results are discussed in details.

Nowadays electronic commerce plays an important role in many business activities, operations, and transaction processing. The recent advances on e-businesses have created tremendous opportunities to increase profitability. This paper presents a multi-objective marketing planning model which simultaneously determines efficient marketing expenditure, service cost and product & apos; s selling price in two competitive markets. To solve the proposed model, we discuss a multi-objective geometric programming (GP) approach based on compromise programming method. Since our proposed model is a signomial GP and global optimality is not guaranteed for the problem, we transform the model to posynomial form. Finally, the solution procedure is illustrated via a numerical example and a sensitivity analysis is presented.

This paper presents a new mathematical model to select an optimal combination of productivity improvement techniques. The proposed model of this paper considers four-stage cycle productivity and the productivity is assumed to be a linear function of fifty four improvement techniques. The proposed model of this paper is implemented for a real-world case study of manufacturing plant. The resulted problem is formulated as a mixed integer programming which can be solved for optimality using traditional methods. The preliminary results of the implementation of the proposed model of this paper indicate that the productivity can be improved through a change on equipments and it can be easily applied for both manufacturing and service industries.

One of the most important issues on educational systems is to measure the relative efficiency of similar units based on non-financial factors. Data envelopment analysis (DEA) has become popular among many who wish to rank educational systems using different factors such as the rate of educational success or the number of employees, etc. However, one of the main concerns on implementing DEA methods is the uncertainty involved in input/output parameters. In this paper, a robust data envelopment analysis (RDEA) is developed to measure the efficiency of high schools considering uncertainty on output parameters. We present an empirical study on a set of high schools located in Tehran, which is the capital city of Iran. The study uses uncertain data for input/output information and the results are compared with an existing parametric stochastic frontier analysis (SFA). The preliminary results indicate that the robust DEA approach is relatively a reliable method for efficiency estimating.

Turning is the utmost elementary process among several CNC machine tool operations which is a versatile, efficient and widely used in industries including mechanical, aerospace and automotive sectors. Most frequently the manufacturing industries face the problem of cutting down the production cost without any oblation in the quality of products. Selection of process parameter is essential for assuring a quality product. Convenient choice of the cutting conditions, parameters and tools for the maximum Material removal rate (MRR) and surface finish needs a sophisticated approach adopting mathematical and statistical models as well as experimental method. Taguchi’s method is a very compelling tool to optimize the process variables. The intention of the present study is to determine surface roughness (Ra) and MRR which are key responses to justify the quality of turning operation. Four process parameters have been selected viz. Nose radius (NR), depth of cut (DOC), feed rate (FR) and spindle speed or cutting speed (CS) that influences these responses. During machining operations, the influence of the process parameters and their interac-tion have been analyzed using a statistical tool ANOVA. Aluminum alloy is widely acceptable by industries owing to its good strength to weight ratio, high resistance to corrosion, malleability and excellent resistance during elevated temperatures.

This research gives an overview of an investigation into existing non-destructive testing (NDT) methods used to analyse composite materials. From the investigation and subsequent experimentation a new technique of failure identification in composite materials was developed. The new technique is a form of thermography whereby a temperature rise in a composite material during failure is detected via a thermal camera and a thermal image captured. By observing the thermal images captured of the event the location and the severity of the failure could be gained by only using the thermal images combined with a visual inspection to validate the results. By taking a thermal image and analysing the constituent red, green and blue colours that make up the image, the location of the defect could be pinpointed. This analysis method was developed using MATLAB® in order for the location of a defect to be found using only a thermal image of the composite during failure. The analysis showed that the information that yields the most accurate location of failure was the red part of the images.