Nafis Ahmad

Present status and critical success factors of e-Commerce in Bangladesh

Online trading between businesses or individuals has employed attention of corporations worldwide as they are challenged to remain viable through difficult economic conditions. Despite the losses of so many businesses two years ago when the “dot-com bubble” burst, no serious business analyst disagrees that electronic commerce is steadily transforming how business is done, hence changing the business environment globally. Businesses everywhere need to understand if, when and how to use electronic commerce. The organizational factors, which are critical to the success of e-commerce, are investigated in this research. Different pieces of literature report different factors as key to success and generally based on subjective, perceptual data. A synthesis of existing literature is a basis for survey questions. The data is collected from Bangladesh e-commerce based organizations who are offering their goods & services on electronic channels, using postal questionnaires and Interview technique. The top factors found to be most critical for the success in e-commerce are: quick responsive products/services, organizational flexibility, services expansion, systems integration and enhanced customer service. An important lesson from this research is that organizations need to view the e-commerce initiative as a business critical area rather that just a technical issue. They need to give attention to internal integration, which may include channels, technology and business process integration, and improving the overall services to their customers.

Surface roughness prediction modelling for commercial dies using ANFIS, ANN and RSM

Surface roughness of dies is considered as a vital quality characteristic. In this study, average surface roughness for a die material H13 has been measured after ball end milling operation. A design of experiment was prepared with response surface methodology (RSM). Forty-nine experiments have been conducted varying six different cutting parameters. This 49 data have been used for training purpose and further 25 testing data have been collected with random selection of input parameters. Better ANFIS model has been selected for minimum value of mean square error, which is constructed with two Gaussian membership functions (gauss2MF) for each input variables and a linear membership function for output. The selected ANFIS model has been compared with theoretical model, ANN and RSM. Comparison shows that the selected ANFIS model gives better result. Correlation test shows that only cutter axis inclination angle and radial depth of cut have positive correlation with surface roughness.

Optimization of Multipass Turning Parameters by Genetic Algorithm

Optimization of cutting parameters is one of the key obstacles for CAD/CAM integration. In this work optimum cutting parameters, the best sequence, number, and type of passes of turning operation are determined by Genetic Algorithm (GA). Proposed optimization strategy ensures that no constraint will be violated at the optimum condition and determines the optimum number and type of passes such as rough, finish and semi-finish passes to complete a multipass turning operation. Here objective function is the unit production cost and constraints are limits of cutting force, power, tool life, stability condition, tool chip interface temperature, surface finish, feed rate to depth of cut ratio and the available rotational speed of spindle of machine tool.

An application of Pareto analysis and cause-and-effect diagram (CED) to examine stoppage losses: a textile case from Bangladesh

Abstract Spinning industries are facing challenges of improving productivity in the competitive market nowadays. Ring spinning, the most widely used yarn manufacturing process for short staple spinning, uses several types of machinery from blow room to ring frame for producing yarns from cotton fibers. An enterprise can improve utilization of resources by identifying unwanted machine stoppage and taking corrective actions at different points in the production cycle. This study focuses on the major six stoppage losses that are used to calculate Overall Equipment Efficiency (OEE) of ring frame section. The Pareto analysis reveals that idling and minor stoppage and breakdown losses are responsible 89.3% of total stoppage losses. According to cause-and-effect analysis, root causes for the stoppage losses are: high doffing time, high traveler changing time, broken end of yarn due to piles generation through the front roller, power failure and change in Draft Change Pinion (DCP) due to breakage of teeth of the gear during starting of machine by operators before lowering of ring rail and change of Twist Change Pinion (TCP) due to the displacement of TCP gear shaft. Finally, few recommendations are made to reduce stoppage losses and to increase the productivity of the ring frame section.

A Framework for Application of Reliability Centered Maintenance in the Lead Oxide Production System

In this work a framework on application of Reliability Centered Maintenance (RCM) for Lead Oxide production process in the battery industry is developed. Standard RCM method is used here through Failure Mode and Effect Analysis (FMEA) and decision making criteria is established in view of Criticality and Logic Tree Analysis (LTA). This paper also evaluates the system to find better scope of maintenance strategic fit. Proposed approach can shift the maintenance culture and thinking while maximizing equipment availability and enhancing plant reliability in this type of industries.

Machining parameter optimisation by genetic algorithm and artificial neural network

Machining operations are used for creating surfaces by cutting away unwanted materials from workpieces. These operations are highly constrained and non-linear in nature. As a result traditional techniques are not suitable for machining parameter optimisation. Turning and milling are the two most commonly used machining operations where machining time or cost is minimised by optimising cutting parameters. The important constraints are maximum cutting force, machine power, available rotational speed, tool deflection, required surface finish cusp height etc. Here, a genetic algorithm GA and artificial neural network ANN-based hybrid approach is presented. The proposed approach gives more emphasis on searching optimum cutting parameters near boundaries of feasible and infeasible solution spaces. The optimum solution obtained by this method also does not violate constraints for a specific machining operation. An example of ball end milling operation is presented to explain this technique.

Green design principles and trends of using them among Bangladeshi consumer goods manufacturers

Environmental awareness continues to rise, and customers of all types are realizing the importance of eco-friendly products which are essential to protect our planet. Green design rules are needed to support the implementation of environmental features in the practical design situation. Green design or Design for Environment (DfE) is a field of product design methodology that includes tools, methods and principles to help designers reduce environmental impact. The main objective of this work is to compile a set of DfE principles that are useful during the design process. Later the trends of Green Manufacturing in Bangladesh are studied. Today, many industries in Bangladesh are aware of green design and implementing DfE principles. The present situations about the Green Design trends in some of the leading consumer goods manufacturers, Unilever Bangladesh, PRAN-RFL Group and Rahimafrooz were studied. Moreover the Governments recent initiatives concerning DfE are discussed in this article. Though the list of compiled DfE principles is based on best practices, further work is needed to expand the list.