The machinability of a material can be defined as the ease with which it can be machined. Materials with good machinability property require less power to cut, can be cut quickly, and easily obtain a good finish without wearing the tooling much. Therefore, to manufacture components economically, production engineers are challenged to discover ways to determine machinability of materials which mainly depends on their mechanical properties, as well as on other cutting conditions. In this paper, the machinability characteristics of alloys of three materials, i.e. aluminium, copper and steel are studied applying grey TOPSIS (technique for order preference by similarity to ideal solution) method. For each case, eight different alloys are considered whose machinability is evaluated based on different mechanical properties which are expressed in grey numbers. Using the adopted methodology, it now becomes easier for the manufacturers to select a particular alloy that can be easily machined. It is observed that A357RC, CuCr1Zr and AISI 5140 are the best machinable aluminium, copper and steel alloys, respectively. It is also found that the ranking performance of grey TOPSIS method remains unaffected with the variation in greyness of the considered mechanical property values.

Piroxicam (POC) and oxfendazole (OFA) are two widely used veterinary non-steroidal anti-inflammatory and anthelmintic medicines, respectively. Simple, precise and accurate and cost-effective methods for the determination of POC and OFZ in bulk drug and in its dosage forms have been developed and validated. The methods are based on the potentiometric titration of compound with acetous perchloric acid in glacial acetic acid medium using modified glass-saturated calomel electrode system. The methods are applicable over the ranges 1.5 - 15 mg and 7.5-15 mg, for POC and OFA, respectively. The proposed methods were successfully applied to the determination of active substances in their pharmaceutical dosage forms. A statistical comparison was made on the results of proposed methods with those obtained for reference method. The intra-day and inter-day precision and accuracy values obtained were satisfactory with RSD and RE values less than 3%. Excipients in tablets did not interfere to the assay as shown by the recovery study via standard addition technique with mean percentage recoveries in the range 97.8 – 100.6%.

Electrochemical micromachining (EMM) appears to be a very promising micromachining process for having higher machining rate, better precision and control, reliability, flexibility, environmental acceptability, and capability of machining a wide range of materials. It permits machining of chemically resistant materials, like titanium, copper alloys, super alloys and stainless steel to be used in biomedical, electronic, micro-electromechanical system and nano-electromechanical system applications. Therefore, the optimal use of an EMM process for achieving enhanced machining rate and improved profile accuracy demands selection of its various machining parameters. Various optimization tools, primarily Derringer’s desirability function approach have been employed by the past researchers for deriving the best parametric settings of EMM processes, which inherently lead to sub-optimal or near optimal solutions. In this paper, an attempt is made to apply an almost new optimization tool, i.e. differential search algorithm (DSA) for parametric optimization of three EMM processes. A comparative study of optimization performance between DSA, genetic algorithm and desirability function approach proves the wide acceptability of DSA as a global optimization tool.

The outset of new technologies, systems and applications in manufacturing sector has no doubt lighten up our workload, yet the chance causes of variation in production system cannot be eliminated completely. Every produced/ordered lot may have some fraction of defectives which may vary from process to process. In addition the situation is more susceptible when the items are deteriorating in nature. However, the defective items can be secluded from the good quality lot through a careful inspection process. Thus, a screening process is obligatory in today’s technology driven industry which has the customer satisfaction as its only motto. Moreover, in order to survive in the current global markets, credit financing has been proven a very influential promotional tool to attract new customers and a good inducement policy for the retailers. Keeping this scenario in mind, the present paper investigates an inventory model for a retailer dealing with imperfect quality deteriorating items under permissible delay in payments. Shortages are allowed and fully backlogged. This model jointly optimizes the order quantity and shortages by maximizing the expected total profit. A mathematical model is developed to depict this scenario. Results have been validated with the help of numerical example. Comprehensive sensitivity analysis has also been presented.

In this paper, an inventory model is studied with ramp type demand rate where holding cost is expressed as linearly increasing function of time. The study includes some features that are likely to be associated with certain types of inventory, like inventory of seasonal fruits and vegetables, newly launched fashion items, etc. When stock on hand is zero, the inventory manager offers a price discount to customers who are willing to backorder their demand. The optimum ordering policy and the optimum discount offered for each backorder are determined by minimizing the total cost in a replenishment interval.

For measuring the efficiency of management of cash, cash holding is one of the most important financial decisions that the manager of the concerned organization, has to make in the organization. Basically, it is observed that the organization hold cash for future purposes is very negligible. If the organization invested cash in profitable securities then there is some flexibility but when it relates to the capital market holding cash is not advantageous. Generally two contradictory theories such as Trade-off theory and the Pecking order theory are considered for measuring the efficiency of cash management. In this study we generally observed measured the efficiency of Cash Management influenced by Cash Holding. We also measured whether cash holding of the organization is affected with the degree of financial leverage, size of the organization, investment and profitability. This study helps us to understand the influence of DFL, Investment and Size of the organization on Cash holding. Proper holding of cash in cash management can prevent the bankruptcy of any organization and also increases the efficiency of Cash or Liquidity management.

Due to environmental issues, social concerns, increased pollution and enforced regulations; organizations are focusing to include green practices in their supply chain. This can be accomplished by adoption of green supply chain management (GSCM) practices. Therefore, GSCM is now a proactive approach for firms to increase their ecological performance, corporate image, achieve competitive advantages and sustainable business practices. This study identifies, evaluate and analyze the critical factors (CFs) for successful implementation of GSCM practices. The proposed study uses hybrid Fuzzy DEMATEL model to prioritize the identified critical success factors (CSFs) for GSCM adoption. Fuzzy approach is integrated with DEMATEL to deal with uncertainty arises in decision making process. To demonstrate the application of the proposed approach a case study from electronic industry is considered. This approach investigates the cause and effect relationships among the CFs for successful adoption of GSCM practices in Indian electronic organizations.

Small and Medium Enterprises (SMEs) in India are currently facing the challenges of increased competitions. In such environment, labor retention is very important factor for competition and survival. In this context, appropriate leadership styles and Quality of Work Life (QWL) are very important factors for survival. Literature on QWL is limited to SMEs and several studies commonly correlated with only QWL dimensions but no study on QWL has association with Leadership styles. This empirical study is accomplished to predict QWL in relation to Transformational and Transactional leadership styles. The sample consists of 240 Mechanical Manufacturing SMEs in Bangalore, India. To draw the inference chi-square test, Pearson correlation and regression analysis was carried out for the collected data using Mini Tab14. The results indicate that 25% of SMEs have implemented good QWL, in 56.6% of SMEs have implemented Transformational leadership styles; QWL of SMEs has significant association with Leadership styles. QWL and Leadership styles of SMEs are independent of demographical factors of SMEs like age of the firms, size of the firms, and cost of the project. QWL dimensions like work environment, relation and cooperation, autonomy of work has a significant association with leadership style. For both transformational and transactional leadership style job satisfaction and job security has highest correlation coefficient.

In the global critical economic scenario, inflation plays a vital role in deciding optimal pricing of goods in any business entity. This article presents two single-vendor single-buyer integrated supply chain inventory models with inflation and time value of money. Shortage is allowed during the lead time and it is partially backlogged. Lead time is controllable and can be reduced using crashing cost. In the first model, we consider the demand of lead time follows a normal distribution, and in the second model, it is considered distribution-free. For both cases, our objective is to minimize the integrated system cost by simultaneously optimizing the order quantity, safety factor, lead time and number of lots. The discounted cash flow and classical optimization technique are used to derive the optimal solution for both cases. Numerical examples including the sensitivity analysis of system parameters is provided to validate the results of the supply chain models.

Optimization of a multi-response dynamic system aims at finding out a setting combination of input controllable factors that would result in optimum values for all response variables at all signal levels. In real life situation, often the multiple responses are found to be correlated. The main advantage of PCA-based approaches is that it takes into account the correlation among the multiple responses. Two PCA-based approaches that are commonly used for optimization of multiple responses in dynamic system are PCA-based technique for order preference by similarity to ideal solution (TOPSIS) and PCA-based multiple criteria evaluation of the grey relational model (MCE-GRM). This paper presents a new PCA-based approach, called PCA-based utility theory (UT) approach, for optimization of multiple dynamic responses and compares its optimization performance with other existing PCA-based approaches. The results show that the proposed PCA-based UT method is superior to the other PCA-based approaches.