WE Colloquium: Igor Dykhno

Senior Advanced Manufacturing Strategy and Field Service Consultant, Oakstone Group, LLC

All dates for this event occur in the past.

111 EJTC
1248 Arthur Adams Dr
Columbus, OH 43221
United States

Abstract

A major trend in manufacturing is the increasing application of information technology to improve visibility and control over the factory floor. There are many terms being used to describe the tighter integration of computer systems across factory floors and supply chains, including the digital thread, smart factory, Industrial Internet of Things (IIoT), and Industry 4.0. The goal of Industry 4.0 is the transformation of manufacturing from isolated automated cells to fully integrated automated facilities, so called Smart Factory facilities. Cyber-physical systems monitor the physical processes of the factory and make decentralized decisions, communicating and cooperating both with each other and with the plant's workforce in real time via wireless devices. The expected benefits include improved production efficiency, agility, speed, and quality.

Numerous technical challenges that must be overcome to achieve Smart Factory operations are discussed. Most notable among them are the graceful handling of unexpected equipment failures and improving the consistency and quality of skill-based fabrication processes. Unexpected equipment failure can create a domino effect throughout the value chain, severely impacting and even paralyzing the entire manufacturing operation for an indefinite period of time. Consistent quality increases business profitability, and robust methods are needed to automatically monitor and analyze automated fabrication processes and ensure first-time quality. Different strategies of using an equipment and process performance data collection methodology and data analytics for overall equipment effectiveness (OEE) improvement are evaluated. OEE improvement can be addressed by cost-efficient predictive equipment maintenance solutions. Available solutions, which provide hardware for data collection and data streaming, as well as unique software for data development and data analytics, are compared. Major available welding equipment and welding processes monitoring technologies are compared. Potential value of performance data is evaluated, and data analytics capabilities across different data management platforms are compared. Case studies about how equipment and processes data management can allow manufacturing companies to improve their profitability and competitiveness are presented. Finally, Top Ten Big Data Trends for the near future will be discussed during the presentation.

Bio

Igor Dykhno is a world-renowned inventor, entrepreneur, advanced manufacturing expert and application engineer with PhD in welding and metallurgy. Dr. Dykhno is well experienced in Al alloys, Ti alloys, high strength steels, MIG robotic welding, laser welding, and plasma and TIG welding. He has industrial experience in the automotive, aerospace, defense, heavy machinery, and high-speed transportation industry sectors. As Senior Consultant he is responsible for delivering effective and innovative solutions to the business and manufacturing challenges of Oakstone Group, LLC clients. Prior to joining Oakstone Group, LLC, Igor was the Technology Leader at EWI, where he led several Internet of Things (IOT) Industry 4.0 projects related to improvement in overall equipment and metal fabrication manufacturing efficiency through the utilization of big data.