An organization has to make the right decisions in time depending on demand information to enhance the commercial competitive advantage in a constantly fluctuating business environment. Therefore, estimating the demand quantity for the next period most likely appears to be crucial. Manufacturing companies consider forecasting a crucial process for effectively guiding several activities, and research has devoted particular attention to this issue. The objective of the paper is to propose a new forecasting mechanism which is modeled by integrating Fuzzy Delhi Method (FDM) with Artificial Neural Network (ANN) techniques to manage the demand with incomplete information. Artificial neural networks has been applied as it is capable to model complex, nonlinear processes without having to assume the form of the relationship between input and output variables. The effectiveness of the proposed approach to the demand forecasting issue is demonstrated for a 20/25 MVA Distribution Transformer from Energypac Engineering Limited, a leading power engineering company of Bangladesh.

With the change of education policy in 1991, more and more technical institutions are being set up in India. Some of these institutions provide quality education, but others are merely concentrating on quantity. These stakeholders are in a state of confusion about decision to select the best institute for their higher educational studies. Although various agencies including print media provide ranking of these institutions every year, but their results are controversial and biased. In this paper, the authors have made an endeavor to find the critical factors for technical institution evaluation from literature survey. A Pareto analysis has also been performed to find the intensity of these critical factors in evaluation. This will not only help the stake holders in taking right decisions but will also help the management of institutions in benchmarking for identifying the most important critical areas to improve the existing system. This will in turn help Indian economy.

Inconel 600 is a super alloy known for its properties like low thermal conductivity and work hard-ening. The work hardening property of this alloy makes it harder and harder during successive passes of the tool during machining. Therefore, machining of this type of material demands inno-vation in tool material, selection of proper combination of parameters and their levels for economical machining. Coated carbide tool inserts are most widely used for machining Inconel alloys. These inserts are coated with special materials by PVD or CVD technique to reduce flank wear, improve surface finish of machined components and increase the material removal rate (MRR). In this work carbide insert coated with nanocomposite coatings like AlTiN and TiAlSiN commercially known as Hyperlox and HSN2 were used and their performance during machining of Inconel 600 was studied. As improper selection of process parameter influences on the quality of products and productivity, it is important to identify the optimum combination of input process parameters. Most of the time the influence of the input process parameters on the output parameters like MRR, surface roughness and flank wear is studied independently. Information obtained through single objective optimization may not be sufficient because industries desire to optimize all the output parameters, simultaneously. Multi-objective optimization is the only solution to satisfy the requirements of industries and genetic algorithm based multi-objective optimization is adopted in this work in order to get the optimum combination of input process parameters to obtain maximum material removal rate, minimum surface roughness and minimum flank wear simultaneously.

We know that Cash Conversion Cycle (CCC) is one of the measures of liquidity management. In this paper, we made an attempt to analyse the impact of CCC on the cash management. In this study we selected five companies from Pharmaceutical Sector, including, Alchemist, Lupin, Dr. Reddy’s Laboratory, Cipla and Ranbaxy. In this study, we used the secondary data for analysis and retrieved from Capitaline database for ten years period from 2002 to 2011. Through cash conversion cycle we can easily determine the working capital requirement. Because, it considers the time gap between expenditure for the purchases of raw materials and collection from sales of finished goods prepared with such raw materials, CCC plays an important role in firm’s short term assets and liabilities as well as success of the firm.

Epoxy material being a key in a wide range of applications has become a center of attraction for interdisciplinary research. However, the limitations so far reported in using this material has led to the development of some new pitches such as Polyacetal and Araldite. Polyacetal being currently employed in bushes, wipers, gears, etc. while Araldite composites with a potential of delivering some august properties can be an alternative approach to the former. In this work, a comparative study is carried out on the me-chanical attributes of Polyacetal and Araldite (Epoxy) material. Various ASTM standard specimens casted with these materials are subjected to some exploratory assessments such as Tensile Test, Izod Impact Test, Charpy Impact Test, Three-point Bending Test and Vicker’s Hardness Test in order to determine the respective properties.

In these studies, we had observed polyaniline (PANI) supported p-toluene sulfonic acid (TsOH) and FeCl3 (PANI- TsOH, PANI-FeCl3) as excellent reusable solid acid catalysts for the synthesis of 1, 8-dioxo-octahydroxanthene derivatives 4(a-g) under solvent-free grinding method at mild conditions. Additionally, in the same optimized condition ferric nitrate nonahydrate also acted as (non-reusable) very reactive inexpensive Lewis acid catalyst. The ferric nitrate nonahydrate lost its activity in the form of Clayfen (Clay-supported ferric nitrate) catalyst.

A series of some new (E)-2-(arylbenzylidene)-2-((4-methoxyphenyl)amino)acetohydrazides 4(a-j) have been conveniently synthesized by intermolecular oxidative cyclization of (E)-2-(arylbenzylidene)-2-[(4-methoxyphenyl)amino]acetohydrazides promoted by iodobenzene diacetate as an oxidant. The structures of the synthesized compounds have been confirmed by 1H NMR, IR, MS and elemental analysis. All the synthesized compounds were tested for their inhibitory action against clinically isolated strains i.e., Bacillus subtilis, Staphylococcus aureus, Xanthomonas campestris, Escherichia coli and Fusarium oxysporum. Compounds 4f (21-28 mm, 73.8 %), 4i (20-24 mm, 72.4 %) and 4j (21-27 mm, 71.6 %) demonstrated good antimicrobial activity against all the tested bacterial and fungal strains.

This paper derives a deterministic inventory model for deteriorating items with inventory dependent demand rate. This study develops an order level inventory model with single warehouse where shortages are allowed and it is completely backlogged. The planning horizon is finite. This paper shows that there exists a unique optimal cycle time to minimize the total inventory cost per cycle. Truncated Taylor’s series expansion is used for finding closed form optimal cycle time, optimal time to finish positive inventory and optimal total inventory cost per cycle. The numerical example is given to validate the proposed model. The sensitivity analysis of the solution with the changes of the values of parameters associated with the model has also been discussed.

The improvement in manufacturing process is never ending effort, which is being derived by the culture of the organization. Therefore, an attitude of perfection, innovation and devotion is an essential part for the process improvement of an organization. Recently, innovations in the field of engineering help an entrepreneur sell the products through competitive environment. Moreover, the timely delivery of goods and cost effective product is the yardstick, which contributes to the performance index. These improvements resulted from continued performance enhancement efforts, helps in producing right quality in the right times which means providing stability to the organization performance. The role of lean thinking and supply chain characteristics is to create an effective marked on the organizational performance including bonding of all the participants where-so-ever possible. The purpose of this work is to examine the challenges, which integrate the Lean Principles to Supply Chain Characteristics for the real world situation to achieve better utilization of resources, timely delivery to the customer, and deletion of non-value added items including the control on all type of wastages as linked with supply chain systems.

The evaluation of the most appropriate flexibility in the manufacturing sector is one of the strategic issues that may affect the Flexibile Manufacturing System (FMS). In this paper, a Multiple Attribute Decision Making Method (MADM) methodology is structured to resolve this problem. The two decision making methods, which are Simple Additive Weighting (SAW) and Weighted Product Method (WPM), are integrated with Analytical hierarchy process (AHP) in order to get the best use of information available. The aim of using AHP is to give the weights of the attributes and these weights are used in SAW & WPM method for ranking of flexibility in FMS. Furthermore, the method uses fuzzy logic to change the qualitative attributes into the quantitative attributes. 15 factors are taken to evaluation of 15 flexibility. In this report, we concluded that Product Flexibility has the most impact in 15 flexibilities and Programme Flexibility has the least impact in these 15 flexibilities by this methodology.