Invited Speakers

	Recent developments in the Risk Management of Offshore production systems Dr. Daniel Averbuch Institut Français du Pétrole/Direction Mécanique Appliquée, Rueil-Malmaison/F
Abstract: The development of offshore Oil and Gas Fields involve important investments and operational expenditures to design, build and operate production facilities. In the context of deep offshore, several risks on the level of production are to be taken into account at the design phase. Various phenomena, such as gas hydrate plugs or wax deposit (named "flow failures"), which are related to the physical nature of the fluid and to the flowing conditions, can indeed lead to important reduction of production. Furthermore, the design of the system is mainly decided at a moment where informations on the nature of fluids or the reservoir itself are uncomplete. A rational design of the production system should then take into account uncertainties present at the moment of the decisions, through an appropriate risk management of phenomena potentially leading to loss of production. This talk will then describe a methodology developped by IFP to manage risk related to the production performance of Offshore Oil and Gas Fields. This original methodology allows to take into account risk caused by equipment failures as well as "flow failure" due to undesired physical phenomena resulting of the conditions of production. The approach is based on an explicit integration of production uncertainties resulting from a lack of knowledge on the reservoir, into the mathematical models describing the undesired physical phenomena. Dedicated tool lead to an evaluation of the probability of occurrence of such "flow failures", and their consequences on the availability and production availability of the production system is in a next step evaluated using dedicated software. The approach finally leads to a global performance evaluation and to a technico-economical optimisation of the production system. Examples of applications will be presented, based on representative situations of a deep offshore production system. The context and physical phenomena will firstly be described. The calculation methodology will be then presented and typical results will finally be given.
	Life cycle modelling in the chemical industries: is there any reuse of models in automation and control? Dr.-Ing. Jens Bausa BASF Aktiengesellschaft, Ludwigshafen/D Dr.-Ing. Guido Duennebier Bayer Technology Services GmbH, Leverkusen/D
Abstract: In the last two decades, simulation technology had a large influence on process industries. Today, modern numerical methods, powerful personal computers and convenient software packages facilitate the solution of complex engineering problems at every office workplace. Typical tasks are steady-state process design, dynamic process simulation for the development of control strategies and the design of model based control concepts. In principle, existing models could be applied comprehensively to make use of the already available process knowledge. For instance, this aspect comprises the usage of steady state design process models for controller design based on dynamic models. The concept of model usage along the process lifecycle and the supporting methods and tools are subject to current research and can be found in numerous publications. In practice, the integrated use of models for different applications can be found only rarely so far. This contribution concentrates on the later stages of the process lifecycle, in particular process optimisation and advanced control. By considering the different viewpoints of (academic) researchers, software providers and industrial users, the authors discuss potential reasons for the gap between the positions of these three groups. Specifically, it is remarkable that after a wave of projects using dynamic simulation in the 1990s, the integrated use of models for automation and control has not become widely accepted in process industries yet. However, using several examples, this contribution demonstrates the current state of industrial applications, the problems and limitations occurring therein, and the fact that these problems are no insurmountable obstacles for the application of model based methods in process industries.
	Challenges and opportunities in process innovation Dr. Larry R. Genskow Procter & Gamble Co., West Chester, OH/USA
Abstract: This talk will address key challenges and opportunities in process innovation. Important capability trends will be identified and discussed. Key challenges and opportunities to be addressed include: 1) The challenge of learning at the smallest scale to increase innovation speed and decrease cost – and lessons from biotech. 2) The importance of identifying disruptive innovations – innovations that can ultimately obsolete incumbent businesses with new to the world technologies. 3) The need for diversity to fuel diversity of thought - to nourish and enable creativity and invention. 4) The challenge and the promise of micro-technologies. 5) The role of modeling and simulation in process innovation.
	Systems Bio(techno)logy: The Process Systems Engineering of Cellular Processes Prof. Vassily Hatzimanikatis Northwestern University, Evanston, IL/USA
Abstract: Biological systems ‑ single cells, multicellular tissues and multi-tissue organisms ‑ are complex entities. From an engineering point of view, they consist of a large number of physicochemical and mechanical processes that operate in parallel and in series. Understanding the function of the individual processes and their interactions is critical for advances in drug discovery, and in industrial and agricultural biotechnology. Biological sciences and every field in biotechnology are experiencing the ongoing revolution of systems bio(techno)logy. It is an information revolution driven by advances in analytical technology, biochemistry, nanotechnology, polymer chemistry, and material science. These technologies enable the precise and quantitative characterization of the various molecules within a cell and the monitoring of many cellular processes simultaneously. Systems bio(techno)logy offers two main opportunities to process systems engineers: (i) contribution to technology development, and (ii) meaningful analysis of the large-scale information generated by these technologies. We will offer a perspective on the challenges posed to process systems engineers in the development and implementation of computational tools and frameworks for the management, analysis and interpretation of biological information, and for the integration of analytical technologies and computational tools for the elucidation and (re)engineering of the function of cellular processes. We will outline the capabilities and the limitations of some of the current technologies used in studying cellular function and discuss qualitative similarities between problems in processes systems engineering and systems bio(techno)logy.
	Recent Developments and Industrial Applications of Data-Based Process Monitoring and Process Control Dr. Manabu Kano Kyoto University/J Yoshiaki Nakagawa Sumitomo Metals (Kokura), Ltd./J
Abstract: The first objective of this paper is to review recent developments in data-based methods for process monitoring and process control. The focus is not only on theoretical developments but on industrial applications. Statistical process monitoring and control are now widely accepted in various industries. For example, multivariate statistical process control has become a handy tool for fault detection and diagnosis, and a number of applications were reported. In recent years, statistical process monitoring and control techniques are expected to solve quality-related problems. The issue of how to improve product quality and yield in a brief period of time becomes more critical in many industries where the product life cycle becomes shorter. Examples include sheet steel processes and liquid crystal display (LCD) processes. These processes are totally different in appearance, but the problems to solve are highly similar: how to build a reliable model from a very limited sample, how to analyze the model and optimize operating condition, and how to realize an on-line monitoring and control system and maintain it. In this paper, the problems and solutions are described with our application results in steel facilities and others, and a hierarchical quality improvement system (HiQIS) is presented. The focus is especially on problems and difficulties encountered in industrial applications, because another objective of this paper is to clarify challenges and opportunities for future research and development.
	Supply Chain Design, Management and Optimization PhD Dean Kassmann Amazon.com, Seattle, WA/USA
Abstract: Modeling and optimization are the traditional workhorses of supply chain management. The techniques have been used by many companies for planning, manufacturing, and logistics decision making. These techniques generally rely heavily on approaches grounded in operations research that excel at capturing stochastics and the discrete nature of these problems. Approaches fundamental to the process industries such as identification, dynamic simulation, model-based control, and more generally, operational-based decision making are often not understood or fully embraced by supply chain practitioners. This talk will discuss the challenges and opportunities in using modeling and optimization techniques in supply chain management at Amazon. We will also discuss the application of control and feedback to supply chain systems, and discuss theoretical and practical challenges as well as opportunities in applying these ideas to real-world supply chain decision systems.
	Innovation in the chemical industry: a growth engine! Dr. Stefan Marcinowski Member of the Board of Executive Directors and Research Executive Director of BASF Aktiengesellschaft/D
Abstract: The chemical industry is a key innovation engine for all industrial sectors, such as the automotive, construction, or microelectronics industry. Therefore, the long-term growth of the chemical industry is dependent upon the success of its customers in the globalizing market place. This presentation deals with the challenges and opportunities for profitable growth through innovation in the chemical industry: 1) Identify solutions that give the customer a competitive advantage in its market segment 2) Set up a superior cost structure derived from new processes and operational excellence 3) Adapt the speed of innovation to the product-cycles in the end-consumer market 4) Capture technological excellence by cooperation with the best universities, institutes, and start-up companies in the world.
	Process Intensification and Process System Engineering: a friendly Symbiosis Prof. Jacob A. Moulijn, Prof. Johan Grievink, Prof. Andrzej Stankiewicz Delft University of Technology/NL Prof. Andrzej Górak University Dortmund/D
Abstract: Process Intensification, is it a research area or a set of objectives? In our view the first is the case. Process Intensification (PI) is an area in the discipline chemical engineering; taking the conventional, existing technologies as a frame of reference, it tries to achieve drastic improvements in the efficiency of chemical and biochemical processes by developing innovative, often radically new types of equipment, processes and their operation. Miniaturization of the plant has become a hallmark of Process Intensification. But PI has also other sustainability-related dimensions, such as significantly increased material efficiency, reduced energy usage, reduced waste generation and increased process safety. Producing much more with much less is the clue to Process Intensification. It provides a new avenue to a better economy and ecology of industrial production clusters. Essential for Chemical Engineering is that it is a multilevel discipline. The question then arises at what level does PI takes place. An early definition was that PI was limited to the meso (reactor) and macrolevel (plant). So, given the chemistry, the chemical engineer designs the optimal intensified process. However, it is more rewarding to consider more scales. At the higher boundary the supply chain should be the reference level for setting life span oriented performance targets for an intensified plant; at the lower boundary the molecules and catalytic sites (A) are obviously instrumental in enabling the goals of PI. In this lecture we will focus on examples from heterogeneous catalysis. The importance of most levels is self-evident. With respect to the supply chain one might think of e.g. the consequences of transport of dangerous chemicals from one plant to the other. An example is the elimination of transport of phosgene. By microreactor technology small-scale on-site production can lead to PI. For catalytic reactors the mesolevel has its own challenges. The particle and the intraparticle space are considered to belong to the mesolevel. Good examples are membranes covering catalyst particles allowing high selectivities or pores consisting of a hydrophobic wall in an aqueous environment. This can lead to high precision, enabling in a sense PI at the source. What is good practical strategy for PI? It is clear that the philosophy of PI (PI, what is it and how can it be done, what are the drivers?) is not yet mature and, as a consequence, examples are crucial. The lecture will focus on examples from chemical and biochemical processing and from these examples contributions to theory will be formulated. Contribution can be in the field of equipment, e.g., structured or high-gravity reactors and processing methods, e g., (bio)reactive or hybrid separations. In a sense this division is analogous to that of IT in hardware and software. A classical example of PI-equipment is the so-called Spinning Disk Reactor, which applied to an industrial, phase transfer-catalyzed Darzen reaction, resulted in 1000-fold reduction of the processing time, 100-fold reduction of equipment inventory and 12-fold reduction of the by-products level. Structured reactors have fascinating characteristics. They enable high rates and selectivity. In multiphase applications in the so-called Taylor-flow regime they enable high rates of mass transfer at laminar conditions, defying the Chilton-Colburn analogy! Integrated heat exchanger reactors, where the heart source and sink are in direct contact, open up new ways for PI. Many enzymes exhibit simultaneously high selectivity and high rates, providing a basis for intensified processes. Also in this case the rule holds: a superior catalyst usually deserves a structured reactor! Microreactors in general are examples of structured reactors. Microreaction technology promises breakthrough technology in many areas. Here, we can learn from life sciences where microarrays play a crucial role not only in analysis but also in synthesis. The challenge is also the integrated design of material properties and process performance what can be illustrated on example of separation of large bio molecules. At the processing side a wealth of opportunities suggest themselves. Alternative forms of energy, such as microwaves may accelerate chemical processes hundreds if not thousands times. Some of these alternative energy forms, such as electromagnetic or acoustic fields, allow for essentially 100% selective product formation, without any by-products, unachievable with conventional technologies, or allow for synthesis of products that could not be synthesized at all with conventional methods. The application of photons in chemical engineering provides an additional degree of freedom with potential for PI. Not surprising, catalysis is instrumental in novel processes and photocatalysis is a new fast developing field, allowing for instance artificial photosynthesis, that might even (partially) solve the Greenhouse effect. The classic application of PI is in the area of reactive separations. Integration of reaction and separation is appealing and in fact catalytic distillation is more and more applied in industry. PI is important for all sectors where chemical engineering is important: from pharma to the oil refinery. A special sector is biotechnology where the systems in general are very diluted and, as a consequence, PI can contribute a lot. In-situ removal of products e.g. extraction of metabolites or adsorption of enzymes has the potential of making a revolutionary contribution. At the end of the lecture the potential for new contributions from and interactions with the PSE field will be highlighted. For the PSE community several challenges exist. Can PSE contribute to optimizing the overall process development and design cycle for intensified processes? How can PI be assessed in terms of sustainability? Does less equipment (often) lead to lower efficiency in terms of exergy? There might well be an important aspect regarding process control: highly compact, intensified units may be poorly controllable or responsive to changing external conditions, like feed composition, desired product mix. What is the impact of modern smart control (e.g., new micro-scale sensors and actuators and advanced First Principles model-based control algorithms) on the optimal design of intensified plants? Are dynamic modes of operation better achievable in intensified plants? What is the impact from the option of applying more extreme conditions? Other questions to be addressed are: What is the proper process modeling depth - from short-cuts to CFD applications – for each of the considered scales? What is the necessary accuracy of measured model parameters in connection with the chosen modeling depth? How predictive are the simulation methods of intensified processes? What are the best tools for the synthesis and design of intensified processes? Several examples of reactive separations will provide the answer to the latter questions.
	Model-centric technologies for support of manufacturing operations Prof. J.A. Romagnoli Louisiana State University, Baton Rouge, LA/USA
Abstract: The potential of model-based software tools to support industrial manufacturing operations has been widely recognised in the PSE/CAPE arena. Throughout the 1990s, the CAPE community made considerable progress in two strategic areas: the technical development and commercialisation of general-purpose modelling, simulation and optimisation environments; and the standardisation of open interface specifications for component-based process simulation. Rigorous mechanistic process models, however, are just one of the many components of any sophisticated software tool targeting industrial applications, and model-centric technologies must overcome a series of challenges limiting their ability to meet the needs of the Process Industries for support of manufacturing operations. First, a series of software components aiming at assisting the description of hybrid data-driven/model-based problems must be created so that realistic process-engineering problems can be defined and solved. Second, these software components must be integrated seamlessly into a single platform so that points-of-synergy between complementary model-based technologies can be unravelled and exploited. Finally, this software application must be compatible with commercial process-engineering software tools and, preferably, the CO standards, in order to use state-of-the-art modelling and solution techniques. In this work we discuss the impact of a series of technologies for analysis and improvement of industrial manufacturing operations. These technologies are fused in a model-centric framework for integrated simulation, estimation/reconciliation and optimisation of large-scale/plant-wide industrial process systems. A continuing industrial case-study is used to illustrate the characteristics and viability of these technologies, and their impact on the industrial workplace.
	Business Decision Making in the Chemical Industry: PSE Opportunities Prof. Rajagopalan Srinivasan IA Karimi & Aspi Gave Vania, National University of Singapore/SGP
Abstract: The chemical enterprise of today faces a complex, global, and increasingly competitive environment, one with numerous market prospects and fraught with endless uncertainties. All enterprise level decisions related to project, product as well as process selection, supply chain design and management, manufacturing, and logistics must carefully consider the various opportunities as well as the uncertainties and risk. In this talk, we will examine the role that the Process Systems Engineering community can play at this interface of business and engineering.
	Challenges for process system engineering in infrastructure operation and control Dr. Zofia Verwater-Lukszo Delft University of Technology/NL
Abstract: Infrastructures are socio-technical systems, which due to their complexity often operate in an insufficient or inefficient way. Reliable, safe, predictable, cheap etc operation of these systems is of crucial importance for our modern society. The PSE area defined by Grossmann and Westerberg is concerned with the improvement of decision making for the creation and operation of the chemical supply chain¹⁾. An interesting question is to what extent the methods from process systems engineering (PSE) are still applicable for improving the operation of infrastructures. In the paper we concentrate on the feasibility of applying PSE knowledge to the operation of infrastructures, and in particular the energy distribution infrastructures. We investigate the accomplishments in PSE from the past decades in the following areas: - Process Operation * Real-time optimization * Scheduling of process networks * Fault diagnosis Fault-tolerant control - Process Control Model predictive control * Nonlinear control * Distributed control * Hybrid control Statistical process control - Supporting tools / methods Large-scale optimization * Dynamic programming (optimal control) * Mixed-integer (non)linear programming (MILP, MINLP) * Mulit-level optimization * Global optimization * Artificial intelligence In the paper the special attention will be paid on scheduling, model predictive control, distributed control, large-scale optimization, MI(N)LP, multi-level optimization and artificial intelligence. For other areas our preliminary results will be presented. To enable a systematic review of PSE methods towards improved operation of infrastructures, we started with the energy distribution networks. However, the conclusions should be made generic and applicable to various types of infrastructure such as water, gas, waste, telecommunication and transport. This gives an invaluable support by understanding, analysis and control of the operation of multi-actor multi-level infrastructural systems. ¹⁾I. E. Grossmann, A.W. Westerberg, Research Challenges in Process Systems Engineering, AICHE J., 46 (9), 1700-1703 (2000)
	The emerging field of multiscale simulation in the chemical and biological sciences Prof. Dionisios Vlachos University of Delaware, Newark, DE/USA
Abstract: Multiscale simulation is emerging as a new scientific field in chemical sciences. The idea of multiscale modeling is straightforward: one computes information at a smaller (finer) scale and passes it to a model at a larger (coarser) scale by leaving out degrees of freedom as one moves from finer to coarser scales. The obvious goal of multiscale modeling is to predict macroscopic behavior of an engineering process from first principles (bottom-up approach). However, the emerging fields of nanotechnology and biotechnology impose new challenges and opportunities, especially for computer-aided process engineering. For example, the ability to predict and control phenomena and nano-devices with resolution approaching molecular scale while manipulating macroscopic (engineering) scale variables can only be realized via multiscale simulation (top-down approach). In this talk recent developments in multiscale simulation will be reviewed. Examples of applying multiscale modeling will be presented from product engineering, systems biology, and micropower generation.
	Engineering Life processes live: the Silicon cell Prof. Hans V. Westerhoff Systems Biology, Manchester Interdisciplinary Biocentre, The University of Manchester/UK, and Molecular Cell Physiology, Free University, Biocentre Amsterdam/NL, and Mathematical Biochemistry, University of Amsterdam, Biocentre Amsterdam/NL
Abstract: Process Engineering has been quite successful for the optimization of production in inanimate systems. Where biology enters the arena other than as the usual source of the material (oil, sewage), the success rate of process engineering tends to drop. Biological systems appear to be more resistant to control by the engineer; they are more stubborn. In this presentation we shall attempt to relate this phenomenon to a feature that emerges from an entirely different field, i.e. functional genomics. In the latter field, one regularly observes the phenomena of redundancy and robustness. Where the former used to be explained on the basis of parallel pathways, both may be more related to the processes of adaptation that are so characteristic of live and certainly Life systems. Although metabolic engineering did interface with genomics, it rarely incorporated the aspect of adaptation, i.e. of the changing of the structure of the network with conditions. Flux balance analysis does not do so either; its pathways are given and assumed to be always expressed. I will show that although metabolic control analysis deals with the engineering of Life processes in much the same way, it already explains part of the resistance of biological systems to process engineering. I shall then venture on to Hierarchical Control Analysis and Hierarchical Regulation Analysis, both of which allow for adaptation. Perhaps unexpectedly, I shall show how the concepts and principles developed for Life processes also apply to inanimate processes, yielding new principles for process engineering in general. The presentation will make ample use of a new tool in bioprocess engineering, i.e. the silicon cell (cf. www.siliconcell.net ). The silicon cell is a collection of computer replica of processes in living organisms, which should be linked up to produce models of larger networks. They can be also used to play with and engineer biological processes on line, in silico. For the particular case of the engineering of the production of baker's yeast I shall discuss some of the implications of these new approaches. Panem et circenses therefore.

Highlights

Invited Speakers

Recent developments in the Risk Management of Offshore production systems

Life cycle modelling in the chemical industries: is there any reuse of models in automation and control?

Challenges and opportunities in process innovation

Recent Developments and Industrial Applications of Data-Based Process Monitoring and Process Control

Model-centric technologies for support of manufacturing operations

Business Decision Making in the Chemical Industry: PSE Opportunities

Challenges for process system engineering in infrastructure operation and control

The emerging field of multiscale simulation in the chemical and biological sciences

Engineering Life processes live: the Silicon cell