Prof. Suresh P. Sethi (University of Texas at Dallas, USA) "MANAGING WITH INCOMPLETE INVENTORY INFORMATION" Suresh P. Sethi is Eugene McDermott Professor of Operations Management and Director of the Center for Intelligent Supply Networks at The University of Texas at Dallas. He has written 7 books and published nearly 400 research papers in the fields of manufacturing and operations management, finance and economics, marketing, and optimization theory. He teaches a course on optimal control theory/applications and organizes a seminar series on operations management topics. He initiated and developed the doctoral programs in operations management at both University of Texas at Dallas and University of Toronto. He serves on the editorial boards of several journals including Production and Operations Management and SIAM Journal on Control and Optimization. He was named a Fellow of The Royal Society of Canada in 1994. Two conferences were organized and two books edited in his honor in 2005-6. Other honors include: IEEE Fellow (2001), INFORMS Fellow (2003), AAAS Fellow (2003), POMS Fellow (2005), IITB Distinguished Alum (2008), SIAM Fellow (2009), POMS President (2012).

Abstract: A critical assumption in the vast literature on inventory management has been that the current level of inventory is known to the decision maker. Some of the most celebrated results such as the optimality of base-stock policies have been obtained under this assumption. Yet it is often the case in practice that the decision makers have incomplete or partial information about their inventory levels. The reasons for this are many: Inventory records or cash register information differ from actual inventory because of a variety of factors including transaction errors, theft, spoilage, misplacement, unobserved lost demands, and information delays. As a result, what are usually observed are some events or surrogate measures, called signals, related to the inventory level. These relationships can provide the distribution of current inventory levels. Therefore, the system state in the inventory control problems is not the current inventory level, but rather its distribution given the observed signals. Thus, the analysis for finding optimal production or ordering policies takes place generally in the space of probability distributions. The purpose of this talk is to review recent developments in the analysis of inventory management problems with incomplete information.

Prof. Erwin Pesch (University of Siegen, Germany) "PLANNING AND SCHEDULING IN INTERMODAL TRANSPORT" Erwin Pesch holds a Chair in Management Information Sciences at the University of Siegen. He was employed as a Software Engineer at the Commerzbank AG and worked from 1989 to 2001 as an Assistant Professor at the Faculty of Economics and Business Administration of the University in Maastricht and as a Professor at the Institute of Economics of the University in Bonn. He holds a Ph.D. in Mathematics and a Habilitation in Business Administration both from the Technical University Darmstadt. His research areas are in Logistics, Management Information and Decision Support Systems, Project Management and Scheduling many of which are closely related to various industrial projects. He is author or co-author of 4 books and has published more than 150 papers in many international journals, among others in Mathematical Programming, Artificial Intelligence, Management Science, Journal of Combinatorial Theory, Journal of Graph Theory, IEEE Transactions on Robotics and Automation, Discrete Mathematics, Discrete Applied Mathematics, and serves on the editorial boards of 12 international journals including INFORMS Journal on Computing, Journal of Scheduling, European Journal of Operational Research, Operations Research Letters. He received many Federal Grants from the German National Science Foundation (DFG) and achieved leading positions in citation analysis and publication based rankings in German speaking countries. In 2008 he got the Award of the Polish Minister for Research and Education and obtained the prestigious Copernicus Award (with J. Blazewicz) in 2012.

Abstract: Attracting a higher share of freight traffic on rail requires freight handling in railway yards that is more efficient, and which includes technical innovations as well as the development of suitable optimization approaches and decision-support systems. In this talk we will review planning and scheduling problems of container processing in railway yards, and analyzes basic decision problems and solution approaches for the two most important yard types: conventional railroad and modern railrail transshipment yards. Furthermore, we review some of the relevant literature and identify open research challenges. Additionally we address a scheduling problem that arises in intermodal container transportation, where containers need to be transported between customers (shippers or receivers) and container terminals (rail or maritime) and vice versa. The solution method can be applied to other problems as well.

Prof. Jean-Marie Proth (INRIA, France) "ASSEMBLY LINE BALANCING: CONVENTIONAL METHODS AND EXTENSIONS" Jean-Marie Proth received the Ph.D. degree in mathematics from the University of Nancy (France) and the Ph.D. degree in management science from the University of Paris 9-Dauphine, Paris. His research activities are developed around the design, control and evaluation of dynamic systems. Industrial experience has been gained as a consultant, as well as manager of the research group SAGEP (INRIA). He led and participated in the implementation of 55 contracts of varying duration (between 6 months and 3 years). These contracts were funded by industry, the French authorities or the European Communities, according to their type. He wrote (or co-authored) 25 books on topics related to complex dynamic systems such as production systems and satellites. Note especially books that deal with scheduling, Petri nets, supply chains, outsourcing, forecasting, etc.

Abstract: Assembly line balancing is the process of assigning operations to workstations along an assembly line so as to satisfy a partial order between operations. The objective is not unique. Among the objectives usually displayed, we distinguish two: minimize the number of stations or minimize, over all stations, the period during which stations are inactive. Even in its simplest form, the problem to be solved is NP-hard. Users of assembly line balancing processes observed that some constraints that apply in real world balancing problems were not taken into account in the OR literature. First there is the fact that we do not rebuild a new assembly line every time a balancing problem arises. Clearly, we can not ignore the previously active line. The second problem is the inability to take into account certain constraints that depend on the assembly process under consideration, such as the need not to physically move certain operations attached to the physical characteristics of a station, or the need to locate several operations in a given area for reasons of multiple operators. In this presentation we first recall the classical models mentioned in the OR literature, as well as the algorithms available to provide a solution close to the optimum. We then introduce some extensions of previous algorithms, for example, the multi-product case and the case where the operating times are stochastic. We further propose two models particularly ingenious: the bucket-brigade model and the U-shaped model. Finally, we give a list of problems that currently remain without solution. It is in this area that could focus a part of future research.

Prof. Andrew Yeh-Ching Nee (National University of Singapore, Singapore) "VIRTUAL AND AUGMENTED REALITY APPLICATIONS IN MANUFACTURING" A.Y.C. Nee is professor in the Department of Mechanical Engineering, National University of Singapore since 1989. He received his PhD and DEng from Manchester and UMIST respectively. His research interest is in CAD of tool, die, fixture and process planning, augmented reality applications in manufacturing, sustainable manufacturing. He is a Fellow of CIRP (International Academy for Production Engineering) and SME (Society of Manufacturing Engineers), both elected in 1990. He served as the President of CIRP (2011-2012). Currently, he is the chief editor of Springer, World Scientific and Scrivener-Wiley book series on manufacturing technologies, and Asia editor of IJAMT and IJMTM, as well as editorial boards of some 20 international journals. He has published over 450 refereed journal and conference papers and 11 edited and authored books. He has received many awards and is a Fellow of the Academy of Engineering of Singapore.

Abstract: Virtual reality has been used successfully to simulate engineering and manufacturing operations for a number of years. Augmented reality is a natural progression from virtual reality and its ability to superimpose graphics, text, video and audio information on a real scene has made AR more intuitive than VR. This presentation first introduces the background of manufacturing simulation applications and the initial AR developments, followed by the current hardware and software tools associated with AR. Various studies of design and manufacturing activities, such as AR-assisted collaborative design, robot path planning, plant and facility layout, equipment maintenance, CNC simulation, and assembly operations using AR tools have been developed to assist manufacturing operations. Although AR technologies have been applied successfully, there are challenges such as human factors and interactions in AR systems as well as future trends and developments which will need to be addressed.

Prof. Stanislav V. Emelyanov (Institute for Systems Analysis of the Russian Academy of Sciences, Russia) "THE CONTROL UNDER UNCERTAINTY CONDITIONS: HISTORY AND PERSPECTIVE"

Abstract:  Within a problem of control of dynamic plants under uncertainty, both classical methods of the theory of systems with variable structure, and their modern development in the form of the theory of new types of feedback are considered. The exact structure of feedback in control variable structure systems is clarified. Existence of two types of feedback is revealed: one classical feedback by the general regulation error, and another, new type, the coordinate-to-operational feedback. Thus, feedback is responsible for a set of positive dynamical properties for control variable structure systems. Also, the perspective directions of further development of the theory of new types of feedback are considered. In particular, methods of simultaneous control by families of dynamic plants are considered.

Prof. Gennady A. Leonov (Saint-Petersburg State University, Russia) "NONLINEAR PROBLEMS IN CONTROL OF MANUFACTURING SYSTEMS" Gennady A. Leonov received his Candidate Degree in mathematical cybernetics from Saint-Petersburg State University in 1971 and Dr. Sci. in 1983. From 1985 - he is full professor at the Mathematics and Mechanics Faculty. He had been vice-rector of Saint-Petersburg State University from 1986 till 1988. Now Gennady A. Leonov is Dean of Mathematics and Mechanics Faculty (since 1988), Director of Research Institute of Mathematics and Mechanics of St.-Petersburg State University (since 2004), and the Head of Applied cybernetics department of Mathematics and Mechanics Faculty (since 2007). He is Member (corr.) of Russian Academy of Science, member of Russian National Committees on Theoretical Mechanics and Automatic control, member of Directorate of St.-Petersburg Mathematical Society. In 2011 Gennady A. Leonov was elected to IFAC Council. Gennady A. Leonov authored and co-authored 400 journal and conference papers, 20 books. His main interests are in dynamical systems, control theory and its applications.

Abstract:   This talk addresses the problem of tracking the uncertain demand in case of uncertain production speeds. The uncertainties are described by deterministic inequalities and the performance is analyzed in the from of worst-case scenarios. First, a manufacturing process is modeled as an integrator with saturated input. Since the cumulative demand (the reference signal to track) is a growing function of time, it is natural to consider control policies that involve integration of the mismatch between the current output and current demand. In the simplest setting it results in models similar to a double integrator closed by saturated linear feedback with an extra input modeling disturbances of different nature. This model is analyzed and particular attention is paid to the integrator windup phenomenon: lack of global stability of the system solutions that correspond to the same input signal. The next part of the talk deals with a similar control problem in discrete-time under the surplus-based policy: each machine in the production network tracks the demand trying to keep the downstream buffer at some specified safe level. The performance of manufacturing networks with different topologies is analyzed via the second Lyapunov method, while the disturbances are modeled as deterministic inequalities. The nature of the approach leads to performance analysis in the form of worst case scenarios and allows to find a trade-off between the inventory level and demand tracking accuracy. The third part of the talk illustrates how to make the theoretical findings operational with the experimental setup called Liquitrol. The experimental setup consists of a number of water tanks and pumps that can be interconnected via flexible piping. Each tank represents a buffer with the water playing a role of products. Each pump emulates a manufacturing machine and via piping it is possible to emulate different topologies of the manufacturing network. Due to its flexibility and mobility the setup allows not only to verify theoretical results via experiments, but also can be used in educational process to illustrate different phenomena in tandem and re-entrant manufacturing networks.
   This talk was prepared by G.A. Leonov, I. Adan, B.R. Andrievsky, N.V. Kuznetsov, A.Yu. Pogromsky, and K. Starkov. For more information see FILE.

Prof. Stanislav N. Vassilyev (V.A. Trapeznikov Institute of Control Sciences, Russia) "INTELLIGENT CONTROL OF INDUSTRIAL PROCESSES" Stanislav N. Vassilyev, Academician of the Russian Academy of Sciences, Professor, Director of the V.A. Trapeznikov Institute of Control Sciences (ICS) of the Russian Academy of Sciences (RAS), author of 350 publications, involving 10 monographs. Member of the National Committee on Automatic Control, as well as the International Federation of Nonlinear Analysts, and several other scientific committees and professional societies in Russia, USA, etc. He is the chief editor of the “Automation and Remote Control” journal and member of editorial boards of a number of international journals. The main scientific results of Stanislav Vassilyev relate to the research of stability, controllability, optimality and other dynamic properties of nonlinear, dynamic logical-mathematical models, as well as the problems of ensuring the autonomy of automatic control systems under conditions of uncertainty and disturbances. He has developed methods of reduction in system analysis, suggested the design of logics and methods of automatic inference search and hypothesis generation with applications to problems of intelligent control.

Abstract:   The paper analyzes the problems of intelligent production control subject to world economy trends. It discusses the evolution of the problem of integrated plant floor and plant logistics control and overviews the state-of-the-art control theory methods and the ways to apply them in production control.

 
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