TY - CHAP A1 - Andulkar, Mayur A1 - Le, Duc Tho A1 - Berger, Ulrich T1 - A multi-case study on Industry 4.0 for SME’s in Brandenburg, Germany T2 - Proceedings of the 51st Hawaii International Conference on System Sciences, 2018 N2 - Industry 4.0 is still in its development phase and it promises to bring remarkable benefits to the manufacturing industry around the world when employing the Smart Factory application in large organizations and their supply chains. However, there is a risk of a miss-match when trying to introduce Industry 4.0 to Small and Medium Enterprises (SME) as the concept is mainly being developed around large manufacturing companies. The purpose of this research is to analyze the readiness level and feasibility of implementing Industry 4.0 technologies for SME’s in the federal state of Brandenburg (Germany). The work is based on the survey of 20 SME’s assessing their current problems emphasizing on automation, Enterprise Resource Planning (ERP), CAD/CAM, factory layout planning and logistics. Five SME’s from different domains out of the 20 surveyed are taken as case studies to evaluate the potential benefits, trade-offs and barriers from an implementation of these integrated technologies. The findings revealed that the companies are still coping with the issues relating to planning, logistics and automation. It was also found that all the concepts of i4.0 may not be necessary or even beneficial to an enterprise in the current scenario and new strategies need to be developed for its realization in SME’s. Y1 - 2018 UR - http://hdl.handle.net/10125/50463 SN - 978-0-9981331-1-9 SP - 4544 EP - 4553 ER - TY - GEN A1 - Gebauer, Marc A1 - Lehmann, Marlon Antonin T1 - RFID-basierte Wäschesortieranlage für Wäschestücke aus Pflegeheimen T2 - Melliand-Textilberichte Y1 - 2018 SN - 0341-0781 VL - 99 IS - 2 SP - S. 93 ER - TY - CHAP A1 - Hodapp, Jan A1 - Andulkar, Mayur A1 - Reichling, Thorsten A1 - Berger, Ulrich T1 - Improvements in Robot Teaching for Handling Operations in Production Environments T2 - International Symposium on Robotics, ISR 2018, June 20-21, 2018 Messe München, Entrance East, Munich, Germany N2 - This work describes three technical improvements to the handling assistant, a collaborative robot for handling and commissioning, concerning the depth of information the robot can extract from the teaching process. The teaching process involves an unskilled worker setting up the robots movements and actions through hand guiding to instruct the robot to perform a given task. The possibilities of improvements in picking, placement and path demonstrated are identified and solutions for the same are presented. The task of picking of the part is improved through the use of null space motion of the robot and exploiting part symmetry. The task of placement of parts is improved through the use of data collected during the demonstration. Finally the path of the robot is optimized using regression with a cost function targeted minimizing the time required for path movement. The developed methods are implemented and validated on a test case using a handling assistant which has a KUKA iiwa robot and collaborative gripper. KW - Human-Robot-Collaboration KW - Handguiding KW - Robot-Programming Y1 - 2018 SN - 978-3-8007-4699-6 SP - 408 EP - 413 PB - VDE Verlag CY - Berlin [u.a.] ER - TY - CHAP A1 - Andulkar, Mayur A1 - Hodapp, Jan A1 - Reichling, Thorsten A1 - Reichenbach, Matthias A1 - Berger, Ulrich T1 - Training CNNs from Synthetic Data for Part Handling in Industrial Environments T2 - IEEE 14th International Conference on Automation Science and Engineering (CASE), Munich, Germany, August 20-24, 2018 N2 - As Convolutional Neural Network based models become reliable and efficient, two questions arise in relation to their applications for industrial purposes. The usefulness of these models in industrial environments and their implementation in these settings. This paper describes the autonomous generation of Region based CNN models trained on images from rendered CAD models and examines their applicability and performance for part handling application. The development of the automated synthetic data generation is detailed and two CNN models are trained with the aim to detect a car component and differentiate it against another similar looking part. The performance of these models is tested on real images and it was found that the proposed approach can be easily adopted for detecting a range of parts in arbitrary backgrounds. Moreover, the use of syntheic images for training CNNs automates the process of generating a detector. KW - CAD KW - cellular neural nets KW - convolution KW - data handling KW - feedforward neural nets KW - image processing KW - industrial engineering KW - learning (artificial intelligence) KW - materials handling KW - production engineering computing KW - rendering (computer graphics) Y1 - 2018 SN - 978-1-5386-3593-3 U6 - https://doi.org/10.1109/COASE.2018.8560470 SP - 624 EP - 629 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Schiemann, Markus A1 - Hodapp, Jan A1 - Berger, Ulrich T1 - Collaboration-Gap: A bus-modular architecture for human-robot-collaboration systems in production environments T2 - International Symposium on Robotics, ISR 2018, June 20-21, 2018 Messe München, Entrance East, Munich, Germany N2 - Due to the extensive changes along with Industry 4.0 many established barriers drop. One of those barriers which increasingly disappears separates the workspace between human beings and robots and thus prevents a versatile collaborating environment. This change has led to the development of a wide field of research focusing on the prevention of human-robot impacts and/or the minimization of related risks. This paper is focused on safety regulations introduced as a consequence of those developments over the last ten years and particularly on an approach for demonstrating the unintended gap arising between human and robot due to those regulations. Modularity and integrability as two of the key characteristics in the concept of Reconfigurable Manufacturing Systems (RMS), serve as the comparative parameters. KW - Human-Robot-Collaboration KW - Robot Safety Y1 - 2018 SN - 978-3-8007-4699-6 SP - 450 EP - 454 PB - VDE Verlag CY - Berlin [u.a.] ER - TY - GEN A1 - Colli, Michele A1 - Madsen, Ole A1 - Berger, Ulrich A1 - Møller, Charles A1 - Vejrum Wæhrens, Brian A1 - Bockholt, Markus T1 - Contextualizing the outcome of a maturity assessment for Industry 4.0 T2 - 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 : Bergamo, Italy, 11–13 June 2018 N2 - The transformation of the manufacturing sector towards Industry 4.0 is setting the scene for a major industrial change. Currently, the need for assisting companies in this transformation is covered by a number of maturity models that assess their digital maturity and provide indications accordingly. However, in order to provide operational recommendations to diverse companies, there is a need for making the assessment company-specific. To cope with this challenge, this paper provides an illustration of a new digital maturity assessment approach - 360 Digital Maturity Assessment - which is based on the Problem Based Learning (PBL) model. Y1 - 2018 U6 - https://doi.org/10.1016/j.ifacol.2018.08.343 SN - 1474-6670 SN - 2405-8963 VL - 51 IS - 11 SP - 1347 EP - 1352 ER -