Program overview
13:20 Opening Remark: Jingshan Li, Bengt Lennartson
13:25 Björn Johansson “Awareness and modeling for sustainable automation and production”
14:00 Kevin Lyons “Understanding Sustainable Manufacturing and Associated Analytics through Standards”
14:35 Andrea Matta “Energy saving in manufacturing: current trends and models”
15:10 Coffee Break
15:30 Bengt Lennartson “Energy Optimization of Robot Cells for Sustainable Production”
16:05 Yan Lu “Energy-Integrated Production Scheduling to Reduce Energy Consumption and Cost”
16:40 Liang Zhang “Real-Time Analysis and Control for Energy-Efficient Production”
17:15 Closing Remark: Jingshan Li, Bengt Lennartson
Sustainable Production Automation (SPA) research intends to develop innovative algorithms, models, heuristics, hardware and software in broad areas. The focus is on design, analysis and management of the processes involved in the product life cycle (from design to delivery to return) to have the minimal negative impacts on society (including environmental, economic and social). In this 1/2-day workshop, recent studies in SPA will be presented along with their implications for industrial automation. The goal is to introduce scientific models, methods and technologies with both solid theoretical development and practical importance that can contribute to improve process, efficiency, productivity, quality and reliability to achieve energy efficient and environmentally friendly manufacturing. The topics to be covered include decision tools regarding environmental impacts at different stages of product realization and life cycle. Focus is on reduced energy consumption, reduced emissions, reduced generation of waste products, and reduced use of non-renewable or toxic materials. New standards for sustainable manufacturing are also presented involving methods to calculate desired sustainability performance measures. Furthermore, a number of methods on energy optimization production systems are introduced, including path planning, scheduling, and control.
List of topics and their descriptions:
The workshop consists of six presentations, whose titles and authors are listed in the following.
Awareness and modeling for sustainable automation and production
Björn Johansson
Sustainability has become a pervasive term in almost every field, especially in engineering design and manufacturing. An increased awareness of environmental problems and resource depletion has led to an emphasis on sustainable production. This is especially true in manufacturing industries where energy consumption and the amount of waste generated can be high. This requires proactive tools to be developed to carefully analyze the cause-effect of current manufacturing practices and to investigate alternative practices. Further, new approaches to systematically analyze the utilization and processing of manufacturing resources in a factory setting are becoming important. Modeling and simulation can potentially play an important role. However, there are gaps in the simulation tools used by industry to provide reliable results from which effective and equitable decisions can be made regarding environmental impacts at different stages of product realization and life cycle. Enhanced modeling techniques are needed to understand and predict the sustainability aspects through design and manufacturing where technologies can be applied to transform materials with reduced energy consumption, reduced emissions, reduced generation of waste products, and reduced use of non-renewable or toxic materials.
Understanding Sustainable Manufacturing and Associated Analytics through Standards
Kevin Lyons, Paul Witherell, KC Morris, Rachuri Sudarsan and Yan Lu
Within the ASTM E60.13 Sustainable Manufacturing committee two new guides are being proposed: WK35702-New Guide for The Evaluation of Manufacturing Processes for Sustainable Improvement and WK35705-New Guide for Sustainability Characterization of Manufacturing Processes. The first guide provides provide a methodology and best practices for evaluating manufacturing processes for environmental sustainability. It addresses 1) how to identify the metrics necessary for sustainability-driven process evaluation, 2) how to structure these metrics in a way that allows for evaluation, and 3) how to use these metrics to make consistent process evaluations across a manufacturing enterprise. The second guide provides manufacturers a way to better characterize its manufacturing processes and to systematically capture and describe relevant sustainability information. The guide utilizes standardized and consistent methods for graphically and formally describing manufacturing processes. A formal information representation facilitates data exchange, sharing and communication with other manufacturing applications such as modeling and simulation and LCI. Ultimately, this guide will promote new tool development that can link manufacturing information and analytics for calculating the desired sustainability performance measures.
Energy saving in manufacturing: current trends and models
Andrea Matta
Energy saving in production plants is becoming more and more relevant due to the pressure from governments to contain the environmental impact of manufacturing, and from companies to reduce costs. Several measures can be taken to reduce energy consumption during the processing phase, the machine idle periods and the scheduling of the whole system. This talk will provide an overview on the current research trend and models about energy saving in manufacturing, ranging from simulation models of machining processes to scheduling of the whole manufacturing system to keep low the absorbed peak power.
Energy Optimization of Robot Cells for Sustainable Production
Bengt Lennartson
A sustainable future requires economical, human and environmental sustainability. Focusing on automation systems, these three aspects are in this presentation illustrated by modeling and optimization of moving devices. More specifically, novel methods for energy optimization of multi-robot cells and manikins are presented. A multi-robot system can be considered as a hybrid system, including continuous movements and high-level discrete interactions. A generic modeling framework for hybrid systems is therefore introduced and efficient energy optimization is obtained, based on a simple and robust nonlinear programming formulation. This optimization of hybrid systems is applied to a real robot station with interacting robots, which results in about 40% reduction in energy consumption. The proposed method is a key component in a running EU project called AREUS, where new technologies are developed to reduce the energy consumption of multi-robot systems.
Energy-Integrated Production Scheduling to Reduce Energy Consumption and Cost
Yan Lu
With the increasing awareness of environmental protection and concern of global warming, the industrial sector is facing mounting pressure to reduce its energy consumption and carbon footprints. The application of energy-integrated production scheduling for industrial plants is of high interests by industrial practitioners due to its capability to reduce energy consumptions and cost without sacrificing production throughput. The work-in-process available in the manufacturing system will be utilized to dynamically schedule the production of the different machines so that the energy consumption can be minimized while the production throughput can still be satisfied. The different energy tariffs, e.g., Time-of-Use (TOU), can also be integrated into the cost model to achieve the goal of energy cost saving along with energy consumption reduction.
Real-Time Analysis and Control for Energy-Efficient Production
Liang Zhang
Effective design and control of production systems are viewed as one of the most economical ways to improve energy efficiency of manufacturing processes. The current practice, however, relies mostly on the intuition and experience of factory floor operators and managers. While productivity and quality of production systems have been studied extensively and enjoyed tremendous practical success, the current literature offers limited rigorous quantitative results on analysis and improvement of energy efficiency in production systems. One of the main reasons of this is due to the lack or systematic understanding of the system’s transient behavior. In this work, we will present effective and computational efficient method for real-time analysis and control of production systems. The methods are based on Markvoian analysis approach and a set of analytical calculation-based decomposition/aggregation procedures. The algorithms can outperform discrete event simulations in terms of accuracy and computation efforts. Illustrative examples are given to demonstrate the efficacy of the methods.
Expected participants and their background: This tutorial is targeted at manufacturing system researchers and practitioners as well as industrial automation and information system designers.
Organizers: Jingshan Li, University of Wisconsin, Madison, USA; Bengt Lennartson, Chalmers University of Technology, Sweden
List of speakers and their biographical sketch:
1. Björn Johansson is Professor in Production Systems at Chalmers University of Technology, He performs research on sustainability aspects using virtual tools to analyze and improve production systems for industries. The goal is to create and improve production system performance in order to strive towards a more sustainable future in terms of less environmental impact, socially sound workplaces as well as a healthy economy. The results from the research aim at facilitating use of methodologies and tools for engineers to use while analyzing and creating production systems. Example of application areas are: Simulation of complete product lifecycles. Dynamic analysis for evaluation of environmental aspects of production systems. Realistic 3D animation of production equipment, facilities and environment. Layout planning, scheduling, balancing etc.
2, 5. Yan Lu is Senior Research Scientist at National Institute of Standards and Technology in Gaithersburgh. She is an automation and energy expert with intensive experience in building control, grid automation and industrial automation systems. Her research interest covers distributed agent-based control, fault detection & diagnosis, adaptive control systems, energy optimization and cyber security. In addition to contributing to corporate advanced manufacturing topics, Dr. Lu has led and successfully delivered more than 10 million dollars of government funded projects in the areas of survivable control systems, energy management and smart grid automation. Dr. Lu was the PI of three ARRA projects from US Department of Energy, on building energy efficiency, optimal dispatch of combined cooling, heating and power system and demand response respectively. She is also the PI of three active demonstration projects on building energy management, microgrid control and optimization and asset management funded by US Department of Defense. Dr. Lu have authored and co-authored more than 20 papers in the area of modeling, control, optimization and fault detection and diagnosis in the last three years.
3. Andrea Matta is Distinguished Professor at the Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University (SJTU). He graduated in Industrial Engineering at Politecnico di Milano where he developed his teaching and research activities as temporary Researcher from 1997 to 2001, Assistant Professor from 2001 to 2010 and Associate Professor from 2010. His research area includes analysis, design and management of production and health care systems. He currently teaches Stochastic Models and System Modeling & Simulation at SJTU. He has published more than 100 hundred papers appeared on international journals and conference proceedings.
4. Bengt Lennartson received the Ph.D. degree in automatic control from Chalmers University of Technology, Gothenburg, Sweden, in 1986. Since 1999, he has been a Professor of the Chair of Automation, Department of Signals and Systems. He was Dean of Education at Chalmers University of Technology from 2004 to 2007, and since 2005 he is a Guest Professor at University West, Trollhättan. He has been a Visiting Professor at University of Newcastle, Australia and University of Cagliari, Italy. He was General Chair of WODES 2008 and Associate Editor for Automatica 2002-2005, and currently he is Co-Chair of the RAS-TC on Sustainable Production Automation, Associate Editor for IEEE Transaction on Automation Science and Engineering, and General Chair of IEEE CASE 2015. He is (co)author of two books and more than 260 peer reviewed international papers. His main areas of interest include discrete event and hybrid systems, especially for manufacturing applications, as well as robust feedback control.
6. Liang Zhang received the B.E. and M.E. degrees from the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing, China, in 2002 and 2004, respectively, and the Ph.D. degree in Electrical Engineering – Systems from the University of Michigan, Ann Arbor, USA, in 2009. He is currently an Assistant Professor at the Department of Electrical and Computer Engineering, University of Connecticut (UConn). Before joining UConn, he was with the Department of Industrial and Manufacturing Engineering, University of Wisconsin-Milwaukee from 2009 to 2013. His research interests include modeling, analysis, improvement, design, control, and energy-efficient operations of manufacturing and service systems, as well as modeling and analysis of battery equalization systems.