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Journal : International Journal of Industrial Research and Applied Engineering

From Adaptive Reasoning to Cognitive Factory: Bringing Cognitive Intelligence to Manufacturing Technology Indar Sugiarto; Cristian Axenie; Jörg Conradt
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1186.697 KB) | DOI: 10.9744/JIRAE.1.1.1-10

Abstract

There are two important aspects that will play important roles in future manufacturing systems: changeability and human-machine collaboration. The first aspect, changeability, concerns with the ability of production tools to reconfigure themselves to the new manufacturing settings, possibly with unknown prior information, while maintaining their reliability at lowest cost. The second aspect, human-machine collaboration, emphasizes the ability of production tools to put themselves on the position as humans’ co-workers. The interplay between these two aspects will not only determine the economical accomplishment of a manufacturing process, but it will also shape the future of the technology itself. To address this future challenge of manufacturing systems, the concept of Cognitive Factory was proposed. Along this line, machines and processes are equipped with cognitive capabilities in order to allow them to assess and increase their scope of operation autonomously. However, the technical implementation of such a concept is still widely open for research, since there are several stumbling blocks that limit practicality of the proposed methods. In this paper, we introduce our method to achieve the goal of the Cognitive Factory. Our method is inspired by the working mechanisms of a human’s brain; it works by harnessing the reasoning capabilities of cognitive architecture. By utilizing such an adaptive reasoning mechanism, we envision the future manufacturing systems with cognitive intelligence. We provide illustrative examples from our current research work to demonstrate that our proposed method is notable to address the primary issues of the Cognitive Factory: changeability and human-machine collaboration.
Omni-Directional Mobile Robot Control using Raspberry Pi and Jetson Nano Evert Oneil; Indar Sugiarto
International Journal of Industrial Research and Applied Engineering Vol 4, No 2: OCTOBER 2019
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jirae.4.2.57-62

Abstract

The use of robots continues to increase in various fields in society today. Current developments require robots that are more effective and efficient in its application, especially in terms of its movement. This research is intended to design robots that move omni-directionally, making it easier to move in all directions by using the omniwheels, and the robots can detect simple object around them. The robot using 3 DC motors with encoder as feedback. System movement is controlled using Raspberry Pi 4, to move the robot to destination postition from user’s input. For robot to be able to detect certain object, the robot is equipped with infrared sensor for measure the distance and a camera for image processing purpose with jetson nano as a controller. By using inverse kinematics and odometry calculations for robot movement, it has an error of 9.51% on the x-axis and 8.12% on the y-axis at the robot's final position. The robot can detect objects using infrared sensors with error rate 0.87% and measure object sizes using a camera and image processing with error rate of 30.02% for object’s width readings and 41.8% for object’s height readings.