Artificial intelligence (AI) techniques have been successfully applied in various social and consumer applications, such as voice and image recognitions, social media, advertisement, etc. However, AI techniques have seen limited adoption in industry, primarily due to the difficulty in obtaining adequate sets of training data that are required by various machine learning or neural networks. This presentation will discuss the challenges of adopting AI techniques to industrial applications, and propose a concept of industrial AI (augmented intelligence). Furthermore, experienced operators or engineers accumulated significant knowledge or experience over their professional career. The value behind historical maintenance records should also not be overlooked. Additionally, when sensory data and algorithms are combined with the engineering models, human experience or expert knowledge, and historical records, a new paradigm of industrial AI (iAI) becomes a powerful solution to many industrial problems. Selected applications will be presented to demonstrate the value of this new iAI.
Dr. Jun Ni is the Shien-Ming (Sam) Wu Collegiate Professor of Manufacturing Science and Professor of Mechanical Engineering at the University of Michigan, USA. He served as the founding Dean of the University of Michigan – Shanghai Jiao Tong University Joint Institute located in Shanghai, China since 2006.
Professor Ni has been invited to serve as a guest/advisory professor at many institutions, including Shanghai Jiao Tong University, Tsinghua University, Xi’an Jiao Tong University, Huazhong University of Science and Technology, Dalian University of Technology, and 10 other institutions. He served in the International Expert Advisory Board of the Ministry of Science and Technology of PRC to consult for the strategic planning in advanced manufacturing.
I will be speaking about the role of software in the additive manufacturing process, and how it can help companies take the technology to mass production volumes. The key points of focus will be Simulation, Design and Automation.
The aim of digital machining research is to develop mathematical models of metal cutting operations, machine tool vibrations and control. The science-based digital models allow the virtual design, testing, optimization, monitoring and control of machine tools and machining operations. The model predicts the cutting forces, torque and power consumed in machining parts by considering CNC system dynamics, material properties, cutter geometry, structural flexibilities, and cutting conditions along the tool path. The simulation system predicts chatter-free cutting conditions within the work volume of the machine tool or detects the presence of chatter vibrations along the tool path. An in-house developed virtual and real-time CNC system allows the design and analysis of any five-axis machine tool controller. Current research includes digital twin approach, where virtual simulation and real-time machine tool monitoring are integrated to achieve intelligent, self-adjusting smart machine tools.
Professor Altintas worked as a machine tool and manufacturing process development engineer in industry before joining The University of British Columbia in 1986. He conducts research on metal cutting, machine tool vibrations, control and digital machining. He has published about 200 archival journal and 100 conference articles with over 27,300 citations with h index of 87 (Google Scholar), and a widely used “Manufacturing Automation: Principals of Metal Cutting Mechanics, Machine Tool Vibrations and CNC Design. His research laboratory created advanced machining process simulation (CUTPRO), virtual part machining process simulation (MACHPRO) and open-modular 5 axis CNC system (Virtual CNC), which are used by over 300 companies and research centers in the field of machining and machine tools worldwide.
Professor Altintas is the fellow of Royal Society of Canada, CIRP, ASME, SME, CAE, EC, Tokyo University, P&WC, AvH and ISNM. He received Pratt & Whitney Canada’s (P&WC) university partnership (1997), APEG BC’s Meritorious (2002), APEG BC R.H. McLachlan (2010), UBC Killam Teaching Prize (2011), Gold Medal of Engineers Canada (2011), SME Albert M. Sergent Award (2012), NSERC Synergy Award, ASME Blackall best journal paper award, the scientific award of Turkey in Science and Engineering (2013), Georg Schlesinger Production Engineering Award (Berlin, 2016), and ASME William T. Ennor Manufacturing Technology Award (USA, 2016). He holds an Honorary Doctorate Degrees from Stuttgart University (2009) and Budapest University of Technology (2013), and holds Honorary Professor titles from BEIHANG University in Beijing and University Chair Professor from National Chung Hsing University-Taiwan. He was the past president of CIRP (International Academy of Production Engineering Researchers) for term 2016 – 2017. He is designated as the Distinguished University Scholar of Engineering at the University of British Columbia (2017). He currently directs NSERC CANRIMT Machining Research Network across Canada, and holds the NSERC – P&WC – Sandvik Coromant Industrial Research Chair Professorship to develop next generation Digital Machining Twin Technology.
Today's production with customized and specialized machine tools is often unable to achieve this requirement. As a result, autonomous systems that provide more flexible automation and more production freedom, while still maintaining high productivity and robustness regardless of lot size, are needed. Autonomous machine tools have the ability control the production themselves. In addition, the machine tools are able to adapt to unforeseen changes during the process. The basis for this are intelligent components with sensory and actuator capabilities.
Prof. Berend Denkena is Head of the Institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover. After obtaining doctorate at the Faculty of Mechanical Engineering at University of Hannover in 1992, he worked as a design engineer and head of various development groups for Thyssen Production Systems in both Germany and the United States. From 1996 to 2001, he was Head of Engineering and Turning Machine Development at Gildemeister Drehmaschinen in Bielefeld. Since 2001, he has been full professor of Production Engineering and Machine Tools and director of the Institute of Production Engineering and Machine Tools at Leibniz University Hannover.
최고의 디지털 인재들과 함께 고객의 경험을 디자인하는 두산의 디지털 트랜스포메이션 여정에 대해 소개한다.
형원준 사장은 2017년 두산 그룹의 IT 및 Digital Transformation을 총괄하기 위해 그룹 CDO이자 두산 정보통신 BU 사장으로 취임했습니다.
2008년부터 약 10년간 SAP 코리아 대표 이사/사장을 역임하면서 Design Thinking의 국내 전파에 기여하며 탁월한 경영 성과와 리더십을 높게 평가 받았다. 또한 i2 테크놀로지 코리아에서 부사장으로, 한국 및 아태지역 총괄 사장으로 역임하며 선진 글로벌 기업의 경영혁신 활동을 이끌었다.
협동로봇은 작업자와 로봇이 공유된 공간에서 협업할 수 있도록 안전하며, 복잡한 프로그래밍 없이도 직관적인 교시로 작업이 가능하다. 그러므로 장소가 협소하고 로봇 전문가가 없는 중소기업이나 서비스 산업에서도 쉽게 사용할 수 있어서 새로운 시장을 형성하고 있다. 본 강연에서는 협동로봇의 현재 기술과 산업 현장에의 적용 사례 등을 살펴본다. 또한, 기계식 중력보상장치를 활용하여 로봇의 가반하중을 대폭 증가시키거나 에너지 사용을 대폭 줄일 수 있는 기술도 소개한다.
- 서울대학교 기계공학과 사 (1983)
- MIT 기계공학과 공학박사 (1992)
- 고려대학교 기계공학부 교수 (1993- )
- 지능로봇연구센터 (고려대 부설) 소장 (2004-2016)
- IJCAS (SCIE 저널) 편집장 (2011-2013)
- 한국공학한림원 회원 (2013-)
- 한국로봇학회 회장 (2014)
- 대한기계학회 회장 (2020)
Improving the basic properties of machines, especially the accuracy and quality of machined surfaces, increasing machining performance and entire manufacturing processes, reducing parasitic vibrations, or increasing the reliability of machines and processes are among the main objectives of development and application of advanced computing and simulation means application. Virtual machine and process models are an effective means for analyzing, controlling and optimizing machine-tool-workpiece system behavior. The challenge is to achieve optimized process settings and machine control if the machine is unavailable. Examples of application of virtual models for preparation of machining of demanding parts are shown. In the presentation we will show how these solutions contribute to higher reliability of machine and process operation.
Dr. Sulitka is working at Czech Technical University in Prague at Research Center of Manufacturing Technology (RCMT). Main research interest of Dr. Sulitka is focused on virtual modeling of machine tool and machining processes. He has been responsible for the RCMT research program on virtual modeling since 2005 and the main achievement is represented by own virtual machining software system. Other fields of his research intetest include machine tool simulation of dynamic behaviour, structural optimization, effective use of machine tool in machining operations, and smart machine tool solutions.
Dr. Sulitka gained his master degree in 1996 and his Ph.D. in 2003; both at Czech Technical University in Prague. In RCMT he has been responsible for the Group of Simulation, Business and Project Development and currently he is a head of RCMT.
Advanced optics must to be fabricated with nanoprecision on surface and profile. In order to achieve this, nanoprecision machine tools and machining processes must be applied to optical fabrication. In recent years, nanoprecision machine tools which are driven at single nanometric resolution have been developed and moreover, higher resolution toward picoprecision is now being started to be studied.
For practical application of nanoprecision machine tools, an advanced desktop machine has newly been developed. This machine has 1nm feed resolution, and can mount diamond milling & turning, and also sophisticated grinding capabilities especially with newly developed ion-shot processing. Variety of micro optics can be fabricated on this machine.
The ion-shot processing can be used both for dressing on nanosurface grinding, and also for surface modification on cutting tools and workpieces enabling direct nanosurface cutting of ferrous materials using diamond tools.
Dr. Hitoshi Ohmori is the Chief Scientist and Director of Materials Fabrication Laboratory of RIKEN. He is also a professor at Graduate School of Saitama University. He got his Bachelor, Master and Doctor degrees of Engineering from Department of Precision Engineering, University of Tokyo in 1986, 1988 and 1991, respectively. He is a Fellow of The International Academy for Precision Engineering (CIRP) and Japan Society of Mechanical Engineering (JSME), and a member of Japan Society of Precision Engineering (JSPE) and Japan Society of Abrasive Technology (JSAT).
He invented the ELID (Electrolytic In-process Dressing) method enabling effective dressing of fine diamond grinding wheels during his doctorate program at the Graduate School, University of Tokyo, and has been working at RIKEN (The Institute of Physical and Chemical Research) as a research scientist, Vice Chief Scientist, and Chief Scientist of Materials Fabrication Laboratory (MFL) in the field of precision machining, particularly mirror surface grinding with ELID invented by him during the master course and related ultra/nanoprecision machining for more than 25 years.
He has been developing specific machining processes to improve surface quality and precision through the application of the ELID technique, and has also conducted analytical research on mirror surface generating mechanism by this grinding technique. He received CIRP F.W.Taylor Medal on this achievement. Through his research activities, he has put these new machining techniques based on the ELID method into practical applications for the processing of electronic, optical, medical, and advanced materials.
He has also been managing projects on the development of ultra/nanoprecision fabrication systems for critical components such as advanced X-ray optical elements, space telescope lenses, sensors, micro-tools, and medical devices. He has provided new achievements and promoted significant development in advanced science and engineering. In recent years, he has eagerly expanding his research fields and interests through working on micro grinding, surface functionalization, and a new cutting process development.