Using Big Data to Enhance the Bosch Production Line Performance: A Kaggle Challenge

This paper describes our approach to the Bosch production line performance challenge run by Kaggle.com. Maximizing the production yield is at the heart of the manufacturing industry. At the Bosch assembly line, data is recorded for products as they progress through each stage. Data science methods are applied to this huge data repository consisting records of tests and measurements made for each component along the assembly line to predict internal failures. We found that it is possible to train a model that predicts which parts are most likely to fail. Thus a smarter failure detection system can be built and the parts tagged likely to fail can be salvaged to decrease operating costs and increase the profit margins.Comment: IEEE Big Data 2016 Conferenc

Macroscopic model with anisotropy based on micro-macro informations

Physical experiments can characterize the elastic response of granular materials in terms of macroscopic state-variables, namely volume (packing) fraction and stress, while the microstructure is not accessible and thus neglected. Here, by means of numerical simulations, we analyze dense, frictionless, granular assemblies with the final goal to relate the elastic moduli to the fabric state, i.e., to micro-structural averaged contact network features as contact number density and anisotropy. The particle samples are first isotropically compressed and later quasi-statically sheared under constant volume (undrained conditions). From various static, relaxed configurations at different shear strains, now infinitesimal strain steps are applied to "measure" the effective elastic response; we quantify the strain needed so that plasticity in the sample develops as soon as contact and structure rearrangements happen. Because of the anisotropy induced by shear, volumetric and deviatoric stresses and strains are cross-coupled via a single anisotropy modulus, which is proportional to the product of deviatoric fabric and bulk modulus (i.e. the isotropic fabric). Interestingly, the shear modulus of the material depends also on the actual stress state, along with the contact configuration anisotropy. Finally, a constitutive model based on incremental evolution equations for stress and fabric is introduced. By using the previously measured dependence of the stiffness tensor (elastic moduli) on the microstructure, the theory is able to predict with good agreement the evolution of pressure, shear stress and deviatoric fabric (anisotropy) for an independent undrained cyclic shear test, including the response to reversal of strain

Tuning the bulk properties of bidisperse granular mixtures by small amount of fines

We study the bulk properties of isotropic bidisperse granular mixtures using discrete element simulations. The focus is on the influence of the size (radius) ratio of the two constituents and volume fraction on the mixture properties. We show that the effective bulk modulus of a dense granular (base) assembly can be enhanced by up to 20% by substituting as little as 5% of its volume with smaller sized particles. Particles of similar sizes barely affect the macroscopic properties of the mixture. On the other extreme, when a huge number of fine particles are included, most of them lie in the voids of the base material, acting as rattlers, leading to an overall weakening effect. In between the limits, an optimum size ratio that maximizes the bulk modulus of the mixture is found. For loose systems, the bulk modulus decreases monotonically with addition of fines regardless of the size ratio. Finally, we relate the mixture properties to the 'typical' pore size in a disordered structure as induced by the combined effect of operating volume fraction (consolidation) and size ratio

Optimizing the cutting parameters using taguchi method to reduce the cutting tool vibration

In any machining operation, minimizing the vibration of the tool is a very important requirement for any turned workpiece. Thus the choice of optimized cutting parameter is very important for minimizing the vibration of the cutting tool. The focus of this study is the collection of tool vibration data generated by the lathe dry turning of SS304 samples of diameter 31mm using ISO 6R 1212 as the cutting tool at different levels of speed (140, 220, 360rpm), feed (0.1, 0.16, 0.25mm/rev) and depth of cut (0.5, 0.6, 0.7mm) and then analyzing the obtained data using taguchi analysis to show how tool vibration varies within a given range of speed, feed & depth of cut. The vibration here is represented by its peak acceleration. The analysis revealed that for the specified range of speed, feed and depth of cut, any change in the depth of cut causes a large change in the tool vibration while change in the cutting speed causes comparatively lowest change in tool vibration

Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform

In this paper, we provide details of implementing a system for managing a fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse premise. While the robots are themselves autonomous in its motion and obstacle avoidance capability, the target destination for each robot is provided by a global planner. The global planner and the ground vehicles (robots) constitute a multi agent system (MAS) which communicate with each other over a wireless network. Three different approaches are explored for implementation. The first two approaches make use of the distributed computing based Networked Robotics architecture and communication framework of Robot Operating System (ROS) itself while the third approach uses Rapyuta Cloud Robotics framework for this implementation. The comparative performance of these approaches are analyzed through simulation as well as real world experiment with actual robots. These analyses provide an in-depth understanding of the inner working of the Cloud Robotics Platform in contrast to the usual ROS framework. The insight gained through this exercise will be valuable for students as well as practicing engineers interested in implementing similar systems else where. In the process, we also identify few critical limitations of the current Rapyuta platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape

Intelligent information retrieval tools for police. Intelligence and security informatics. Proceedings.

Intelligent information retrieval tools can help intelligence and security agencies to retrieve and exploit relevant information from unstructured information sources and give them insight into the criminal behavior and networks, in order to fight crime more efficiently and effectively. This article aims at analysing off-the-shelf information extraction tools on their applicability and competency for such applications.