the work aims at the optimization of the output feed rate of a Stationary Hook Hopper Feeder so that the best possible set of parameters affecting it can be selected to get the desired output. For this purpose the effect of various parameters on the feeder output is studied. To facilitate the study and detailed analysis, a statistical model is constructed which is used to predict and optimize the performance of the system. Efficient feed rate optimization determines the input variable settings to adjust the feed rate of the feeder according to the consumption of the parts in the next phase of production. The Stationary Hook Hopper Feeder, whose performance is to be studied, consists of a rotating circular plate and a guiding hook fixed at the centre and running up to the periphery of the plate. As the plate rotates, the parts follow the trajectory of the hook, orient themselves and then eventually are delivered through the delivery chute, tangentially to the plate. The factors influencing the feeder's performance include the speed of rotation of the disc, the population of the parts in the hopper and the size of parts to be fed. A series of experiments is performed on the three process parameters to investigate their effect on the feed rate. To study the interaction among the factors a full 23 factorial experiment approach has been adopted using the two basic principles of experimental designreplication and randomization. The process model was formulated based on Analysis of variance (ANOVA) using Minitab® statistical package. The outcome is represented graphically and in the form of empirical model which defines the performance characteristics of the Stationary Hook Hopper Feeder.Index Terms-ANOVA, design of experiments, full factorial design, stationary hook hopper feeder.

The work aims at the optimization of the output feed rate of a Stationary Hook Hopper Feeder so that the best possible set of parameters affecting it can be selected to get the desired output. For this purpose the effect of various parameters on the feeder output is studied. To facilitate the study and detailed analysis, a statistical model is constructed which is used to predict and optimize the performance of the system. Efficient feed rate optimization determines the input variable settings to adjust the feed rate of the feeder according to the consumption of the parts in the next phase of production. The Stationary Hook Hopper Feeder, whose performance is to be studied, consists of a rotating circular plate and a guiding hook fixed at the centre and running up to the periphery of the plate. As the plate rotates, the parts follow the trajectory of the hook, orient themselves and then eventually are delivered through the delivery chute, tangentially to the plate. The factors influencing the feeder’s performance include the speed of rotation of the disc, the population of the parts in the hopper and the size of parts to be fed. A series of experiments is performed on the three process parameters to investigate their effect on the feed rate. To study the interaction among the factors a full 23 factorial experiment approach has been adopted using the two basic principles of experimental design-replication and randomization. The process model was formulated based on Analysis of variance (ANOVA) using Minitab® statistical package. The outcome is represented graphically and in the form of empirical model which defines the performance characteristics of the Stationary Hook Hopper Feeder.

Obstacle avoidance is an important task for autonomous navigation. The paper presents a simple vision based obstacle detection and avoidance algorithm for mobile robots. Using a monocular vision system, a depth map is created in which every pixel of the image captured by the robot is classified in one of the two categories-ground or obstacle. A virtual triangular obstacle is then created on the depth map. To avoid this obstacle, the robot is directed along its edge having the maximum magnitude of slope. A distinct feature of the proposed algorithm is that along with the position, it takes into account, how densely populated are the obstacles in the field of view and turns the robot in the direction offering less hindrance. The algorithm can be effectively deployed for situations involving environment exploration.The algorithm has been validated on a differential steering robot with an on-board camera, driven by a remote computer which guides the robot, based on the algorithm implemented in MATLAB®. The algorithm is tested under uniform indoor lighting conditions and avoids collision of obstacles in its path successfully.Index Terms -obstacle avoidance, virtual obstacle, depth index, robot vision.

In the present industrial scenario, quality control is a crucial factor for the success of an industry or an organization. Process capability is an important statistical quality tool for measuring the capability of an industrial operation. The paper aims at the process capability of a reaming operation in manufacturing of cylinder head in a leading motorcycle company. The process capability of the reaming operation can be reflected by measuring the quality characteristics of its machined component. For this purpose, adequate sampling of the lot has been considered, probability plots and histograms have been prepared and the performance indices have been computed that indicate the capacity of the process to manufacture a component efficiently. Based on the observations made and data analysis, it has been proved that this statistical process control technique not only helps in improving quality and productivity of an industrial operation but also helps in taking important managerial decisions in an organization.