Session: 02-13-02: Industry 4.0 Aspects

Paper Number: 69993

Start Time: Tuesday, 01:50 PM

69993 - A New Approach to Develop an Intelligent Robotic Gripper Using Virtual Tools Implementing IIoT and ML Technologies 

Virtual Tools (VT) have been used extensively in different companies in recent years. These tools enable the development of components, products, or assemblies in digital ways through their lifecycle. The entire lifecycle presents different challenges implementing VT and this paper explores relevant features between part design and manufacturing in mechatronics systems for an intelligent robotic gripper design. Manufacturing system integration is an important industrial and research activity to explore Next Generation Automated Systems (NGAS). Manufacturing systems have been incorporating flexible, reconfigurable, and intelligent features over the last few years, but advances in technology and trends such as Industry 4.0 will revolutionize the manufacturing industry tremendously. Important subjects towards this direction are Digital Twins (DT), Industrial Internet of Things (IIoT), Machine Learning (ML), and Collaborative Robots, which are integral to continue the progression of smart and reliable manufacturing processes. For example, IIoT and ML have been combined as important manufacturing paradigms to create intelligent gripper designs using DT. This represents contemporary research exploring NGAS trends and enhancing Industry 4.0 on a global scope. A motivation for this paper is on Computer Integrated Manufacturing (CIM), focusing specifically on an intelligent robotic gripper design using VT implementing IIoT and ML aspects along Industry 4.0 trends. With the vast amounts and types of instruments and controls used in closed-loop systems that communicate through IIoT and ML, new virtual methods are needed to securely integrate the NGAS. The expanding capabilities of IIoT and ML technologies increase the demands of customers for intelligent and interconnected instruments and controls, requiring new CIM methodologies to improve the integration of the manufacturing system. There is a need to explore new methodologies analyzing IIoT and ML technologies on CIM to improve the NGAS.  New Programmable Logic Controllers (PLCs) and advanced ML algorithms move the industry standard for manufacturing and process control forward. As Original Equipment Manufacturers (OEMs) and researchers produce new IIoT and ML technologies to bridge the gap, high-value capabilities that were previously unachievable are now possible. With these new technologies, comes the need for new methodologies. Remaining open to change and willing to embrace NGAS and all the available tools in innovative new ways is critical to remaining competitive in this revolutionary period. The goal of this paper is to propose a new approach analyzing IIoT and ML technologies to improve NGAS and analysis of intelligent robot gripper designs. Some researchers have been exploring approaches analyzing mainly Intelligent gripper design, understanding IIoT in the manufacturing domain, or exploring new ML algorithms for manufacturing applications. However, very few of them explored both IIoT and ML technologies together to produce advanced and intelligent robotic grippers. The research novelty contribution of this paper will be in the creation of a new methodology and framework to develop intelligent robotic grippers using VT and combining IIoT and ML technologies. In some advanced manufacturing systems, the merge of IIoT and ML technologies is the key to solving the complex feedback control for process variables using big data analysis. Part of the methodology used in this paper will be demonstrated through a proof of concept and design of an intelligent robotic gripper incorporated in a work cell physically located at Kennesaw State University. The work cell is an important infrastructure for the experimentation work of this research and the main elements are two Kawasaki ZX130L robots integrated with a conveyor system from Vanderlande Industries. The work cell presents a preliminary system integration, and some case studies will be exploring Industry 4.0 trends. This research uses SIMATIC S7-1500 PLC and IoT 2040 PLC through an HMI (all from Siemens) to control the Manufacturing Integrated System (MIS). The instruments (sensors) implemented in the MIS hardware include different manufacturers, but the controls (PLCs + HMIs) are Siemens’ brands. The software to perform the closed-loop feedback is Totally Integrated Automation (TIA V 16). The preliminary results or expected results, which should clearly support the claims of novelty.  

Presenting Author: David A. Guerra-Zubiaga Kennesaw State University

Authors:

David A. Guerra-Zubiaga Kennesaw State University
Logan Block Kennesaw State University
Adam Ricketts Kennesaw State University
Jacob Faile Kennesaw State University
Charlie Dickson Kennesaw State University