Learning curves monitor the performance of workers for the given new task as well as it is a mathematical representation of the same learning process which can be analyzed after frequent repetitions. Now-a-days learning curve is a promotion effective tool for management concern with designing and controlling the process of imperfect production and redesigning unbalanced business operations in the production of goods or services related to scheduling, uncontrolled inventory management, quality management as well as inspection. Learning effect has direct impact in calculation of profit or loss. Generally, a business seller, in order to increase his sale prefers to lend his products to buyers for a definite period of time. There is no penalty before or during this definite time period however after the duration of lending time period is over, he will assign some extra charges. For this action, seller offers a trade credit financing period to his buyer. Assuming when buyer receives a lot he separates the defective and non-defective items by a screening process and defective items are then sold at a discounted price. The percentage of defective items decreases per lot according to learning curve. Seller too plans which condition is beneficial for good coordination of retailers and analysts. Different cases are explained broadly in this model to get maximum profit. In this paper, a fiscal construction feature model for imperfect quality items with trade credit policy is analyzed under the effects of learning. Total profit function per cycle has been derived with the help of involvement of different costs and related parameters for the retailers and a numerical example given ahead shows the verification of results. The impacts of key parameters of the model are studied by sensitivity analysts to deduce managerial insights.

Clustering is a popular data mining technique for grouping a set of objects into clusters so that objects in one cluster are very similar and objects in different clusters are quite distinct. K-means (KM) algorithm is an efficient data clustering method as it is simple in nature and has linear time complexity. However, it has possibilities of convergence to local minima in addition to dependence on initial cluster centers. Artificial Bee Colony (ABC) algorithm is a stochastic optimization method inspired by intelligent foraging behavior of honey bees. In order to make use of merits of both algorithms, a hybrid algorithm (MABCKM) based on modified ABC and KM algorithm is proposed in this paper. The solutions produced by modified ABC are treated as initial solutions for the KM algorithm. The performance of the proposed algorithm is compared with the ABC and KM algorithms on various data sets from the UCI repository. The experimental results prove the superiority of the MABCKM algorithm for data clustering applications.

In most of the published articles dealing with optimal order quantity model under permissible delay in payments, it is assumed that the supplier only put forwards fully permissible delay in payments if retailer ordered a bulky sufficient quantity otherwise permissible delay in payments would not be permitted. Practically, in competitive market environments and recession phases of business, every supplier wants to attract more retailers by the help of providing good facilities for trading. Necessity of order quantity may put a negative pressure on supplier’s demand. So, within the economic order quantity (EOQ) framework the main purpose of this paper is to broaden this extreme case by introducing a new credit policy, Flexible Trade Credit Policy (FTCP), for supplier which can help him provide more free space of trading to retailers. This policy, after adopting by suppliers, not only provides attractive trading environments for retailers but also enhances the demand of supplier due to the large number of new retailers. Here in, under this policy, an inventory system is investigated as a cost minimization problem to establish the retailer’s optimal inventory cycle time and optimal order quantity. Three theorems are established to describe and to lighten optimal replenishment policies for the retailer. Finally, numerical examples are considered to illustrate all these theorems and managerial insights are given based on considered numerical examples.

In this study, a single product is considered which starts to deteriorate with constant rate of replenishment and demand rate is time and price dependent exponential function. Shortage is allowed with partial back logging and the relationship between backorder rate and waiting time is considered to be exponential. The aim is to decide pricing strategy and maximize total average profit function. Total profit function is optimized analytically and proved to be concave function of price. Finally, numerical example is given to illustrate the implementation of the algorithm followed by the sensitivity analysis.

This paper presents an experimental study on rough cut, trim cut using distilled water as a dielectric fluid and Al & Si metal powders in dielectric fluid for WEDM of Nimonic-90. First, the influence of discharge energy (DE) in rough cut is evaluated for machining rate (MR) and surface roughness (SR) and compared with trim cut without any metal powder additives in dielectric fluid. The effect of Al and Si metal powders (varying concentration of 1g/L, 2g/L and 3g/L) in dielectric fluid is studied separately and comparison is also made for MR, SR, recast layer and micro hardness of machined Nimonic-90. From the results it is observed that using trim cut, a fine and uniform surface texture is obtained irrespective of the high discharge energy of rough cut. Al and Si powders additives show a significant reduction in MR for trim cutting operation whereas a remarkable modification is obtained in surface textures after trim cut using metals powder mixed dielectric. SR improves with a concentration of 1g/L and shows a little increase with high concentration of both metals powder. Using metals powder in dielectric fluid, the recast layer becomes smooth and denser and thus, micro hardness increases.

Sustainability reporting, under organizational reporting framework, gives information about economic, environmental, social, and governance performance (GRI). Corporate sustainability reporting has a strong practice of environmental reporting with corporate principles. Despite various guidelines such as GRI, the reporting and presentation of sustainable items are not common in practice. The study aims to analyze the current sustainability of Accounting Practices in Indian Cement Companies. To analyze the same, researchers have taken a case study of five prominent cement companies, JK Cement Ltd., Shree Cement Ltd., ACC Cement Ltd., Binani Cement Ltd., and Ambuja Cement. The study observed the common reporting methods of the selected companies under various common heads in the Indian Cement companies and later to make a comparison amongst them, further by taking the views of the company respondents, with a questionnaire. For measuring combined effect of the selected companies, financial and non-financial disclosure of the selected 13 items for sustainable reporting has been considered, and to analyze the independent variables having influenced upon the combined effect of dependent variables MANOVA statistical technique was applied. It was found that there is a critical difference in the reporting of financial and non-financial sustainability factors by Indian cement companies. The study concluded that the corporations should follow the best standards of environmental sustainability for strengthening their activities and documentation on sustainable growth.

Industries, nowadays, are concerned about energy consumption and ever narrowing rules of emissions by the governments. Therefore, a race to clean; green and less energy consuming manufacturing is going on throughout the world. But in authors’ perspective, the major part of energy exploitation lies in the production of a rejected product. Therefore alongside the use of energy saving processes and machinery, industry should primarily look for rejection reduction. This, apart from energy saving and profitability, will add to the moral responsibility of every person toward nature. Here in this paper, authors describe a case study in which the increased rejection rate of a part of cycle chain assembly is controlled by the application of Six Sigma. Six Sigma, from many years has proved to be an ultimate solution when it comes to the application part in manufacturing industries. It’s very generic and easily applicable methodology has drawn tremendous positive results throughout the world. A financial gain of INR 0.267 million was yielded by implying six-sigma approach. In a move toward energy saving, the money saved by the project was used for green manufacturing to promote energy conservation.

The contribution of Indian construction sector to the GDP is approximately 10%. Under new government policy, it is anticipated that $1000 Billion share for exclusively infrastructure segment would be completed within the next few years. Construction sector in developing country like India still depends on labor and the practice of mechanization, adopting to use of versatile construction equipment is not in force. The need for implementing new technologies and automation is essential to improve the quality, safety and efficiency. To meet the challenges ahead the construction, organizations should focus on utilization of machinery/equipment to achieve desirable results. Modern construction is characterized by the increase in utilization of equipment to accomplish numerous construction activities. The selection of construction equipment often affects the required amount of time and effort. It is therefore important for managements of construction organizations and planners to be familiar with the features of various types of equipment commonly used in construction activities. The selection of appropriate equipment is a crucial decision making process as it involves huge capital investment. The purpose of the present study is to develop a model pertaining to the factors influencing the selection of construction equipment by using interpretive structural modelling and the results indicate that productivity and safety are the important factors in selection of equipment in Indian construction organizations.

With superlative growth in the number of small organizations over the past two decades, the impact caused to environment due to higher production output is also immense. Most governments are continuously taking measures to mitigate the risks associated with industrial growth. One such measure is to implement green practices throughout the supply chain. Since small organizations are important part of supply chain and a major contributor of industrial output they also need to implement green supply chain practices. This paper aims to find out important enablers for green supply chain management (GSCM) from the view point of micro small and medium enterprises (MSMEs). Fuzzy analytical hierarchy process methodology has been used to rank the enablers, three important enablers were identified viz. top management commitment and finance, government support and regulations and recycling and reuse efforts. Managers of small organizations can benefit immensely by focusing on implementing these practices in their organizations.

This study aims to focus on the purchase intention of the consumer specifically the millennial age group with respect to the effect of Electronic word of mouth communication and brand image. The study is performed among the students of the University of Haripur. Study reveals that the effect of Electronic word of mouth and brand image for the purchase of consumer electronics products have positively correlated and the effect is significant, which means that the Word of mouth communication can positively respond to the purchase of the said products in case when the products are branded and have certain image in the mind of consumer.