Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Hysteresis modeling of Magneto-Rheological (MR) fluid damper by self tuning fuzzy control

Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention by the vibration control community. But inherent nonlinear hysteresis character of magneto-rheological fluid dampers is one of the challenging aspects for utilizing this device to achieve high system performance. So the development of accurate model is necessary to take the advantage their unique characteristics. Research by others [3] has shown that a system of nonlinear differential equations can successfully be used to describe the hysteresis behavior of the MR damper. The focus of this paper is to develop an alternative method for modeling a damper in the form of centre average fuzzy interference system, where back propagation learning rules are used to adjust the weight of network. The inputs for the model are used from the experimental data. The resulting fuzzy interference system is satisfactorily represents the behavior of the MR fluid damper with reduced computational requirements. Use of the neuro-fuzzy model increases the feasibility of real time simulation.

QoC Elastic Scheduling for Real-Time Control Systems

The elastic task model, a significant development in scheduling of real-time control tasks, provides a mechanism for flexible workload management in uncertain environments. It tells how to adjust the control periods to fulfill the workload constraints. However, it is not directly linked to the quality-of-control (QoC) management, the ultimate goal of a control system. As a result, it does not tell how to make the best use of the system resources to maximize the QoC improvement. To fill in this gap, a new feedback scheduling framework, which we refer to as QoC elastic scheduling, is developed in this paper for real-time process control systems. It addresses the QoC directly through embedding both the QoC management and workload adaptation into a constrained optimization problem. The resulting solution for period adjustment is in a closed-form expressed in QoC measurements, enabling closed-loop feedback of the QoC to the task scheduler. Whenever the QoC elastic scheduler is activated, it improves the QoC the most while still meeting the system constraints. Examples are given to demonstrate the effectiveness of the QoC elastic scheduling.

Unpacking the entrepreneurial process : A step-by-step guide to a successful venture in the entertainment industry

Unpacking the Entrepreneurial Process: A Step-by-Step Guide to a Successful Venture in the Entertainment Industry introduces a step-by-step guide to either students, entrepreneurs and intrapreneurs to fully understand the necessary steps to both unleash their entrepreneurial capabilities and to foster the development of new ones.

Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion

The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

Framework of a process laboratory for the operational control of service processes

Service processes such as financial advice, booking a business trip or conducting a consulting project have emerged as units of analysis of high interest for the business process and service management communities in practice and academia. While the transactional nature of production processes is relatively well understood and deployed, the less predictable and highly interactive nature of service processes still lacks in many areas appropriate methodological grounding. This paper proposes a framework of a process laboratory as a new IT artefact in order to facilitate the holistic analysis and simulation of such service processes. Using financial services as an example, it will be shown how such a process laboratory can be used to reduce the complexity of service process analysis and facilitate operational service process control.

Process Analytical Technology Approach on Fluid Bed Granulation and Drying : Identifying Critical Relationships and Constructing the Design Space

Fluid bed granulation is a key pharmaceutical process which improves many of the powder properties for tablet compression. Dry mixing, wetting and drying phases are included in the fluid bed granulation process. Granules of high quality can be obtained by understanding and controlling the critical process parameters by timely measurements. Physical process measurements and particle size data of a fluid bed granulator that are analysed in an integrated manner are included in process analytical technologies (PAT). Recent regulatory guidelines strongly encourage the pharmaceutical industry to apply scientific and risk management approaches to the development of a product and its manufacturing process. The aim of this study was to utilise PAT tools to increase the process understanding of fluid bed granulation and drying. Inlet air humidity levels and granulation liquid feed affect powder moisture during fluid bed granulation. Moisture influences on many process, granule and tablet qualities. The approach in this thesis was to identify sources of variation that are mainly related to moisture. The aim was to determine correlations and relationships, and utilise the PAT and design space concepts for the fluid bed granulation and drying. Monitoring the material behaviour in a fluidised bed has traditionally relied on the observational ability and experience of an operator. There has been a lack of good criteria for characterising material behaviour during spraying and drying phases, even though the entire performance of a process and end product quality are dependent on it. The granules were produced in an instrumented bench-scale Glatt WSG5 fluid bed granulator. The effect of inlet air humidity and granulation liquid feed on the temperature measurements at different locations of a fluid bed granulator system were determined. This revealed dynamic changes in the measurements and enabled finding the most optimal sites for process control. The moisture originating from the granulation liquid and inlet air affected the temperature of the mass and pressure difference over granules. Moreover, the effects of inlet air humidity and granulation liquid feed rate on granule size were evaluated and compensatory techniques used to optimize particle size. Various end-point indication techniques of drying were compared. The ∆T method, which is based on thermodynamic principles, eliminated the effects of humidity variations and resulted in the most precise estimation of the drying end-point. The influence of fluidisation behaviour on drying end-point detection was determined. The feasibility of the ∆T method and thus the similarities of end-point moisture contents were found to be dependent on the variation in fluidisation between manufacturing batches. A novel parameter that describes behaviour of material in a fluid bed was developed. Flow rate of the process air and turbine fan speed were used to calculate this parameter and it was compared to the fluidisation behaviour and the particle size results. The design space process trajectories for smooth fluidisation based on the fluidisation parameters were determined. With this design space it is possible to avoid excessive fluidisation and improper fluidisation and bed collapse. Furthermore, various process phenomena and failure modes were observed with the in-line particle size analyser. Both rapid increase and a decrease in granule size could be monitored in a timely manner. The fluidisation parameter and the pressure difference over filters were also discovered to express particle size when the granules had been formed. The various physical parameters evaluated in this thesis give valuable information of fluid bed process performance and increase the process understanding.

A deadline-constrained 802.11 MAC Protocol with QoS differentiation for soft real-time control

As one of the most widely used wireless network technologies, IEEE 802.11 wireless local area networks (WLANs) have found a dramatically increasing number of applications in soft real-time networked control systems (NCSs). To fulfill the real-time requirements in such NCSs, most of the bandwidth of the wireless networks need to be allocated to high-priority data for periodic measurements and control with deadline requirements. However, existing QoS-enabled 802.11 medium access control (MAC) protocols do not consider the deadline requirements explicitly, leading to unpredictable deadline performance of NCS networks. Consequentially, the soft real-time requirements of the periodic traffic may not be satisfied, particularly under congested network conditions. This paper makes two main contributions to address this problem in wireless NCSs. Firstly, a deadline-constrained MAC protocol with QoS differentiation is presented for IEEE 802.11 soft real-time NCSs. It handles periodic traffic by developing two specific mechanisms: a contention-sensitive backoff mechanism, and an intra-traffic-class QoS differentiation mechanism. Secondly, a theoretical model is established to describe the deadline-constrained MAC protocol and evaluate its performance of throughput, delay and packet-loss ratio in wireless NCSs. Numerical studies are conducted to validate the accuracy of the theoretical model and to demonstrate the effectiveness of the new MAC protocol.

Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed. (c) 2004 Elsevier Ltd. All rights reserved.

Improved polymeric medical devices for active substances delivery

The work presented in this thesis was developed in collaboration with a Portuguese company, BeyonDevices, devoted to pharmaceutical packaging, medical technology and device industry. Specifically, the composition impact and surface modification of two polymeric medical devices from the company were studied: inhalers and vaginal applicators. The polyethylene-based vaginal applicator was modified using supercritical fluid technology to acquire self-cleaning properties and prevent the transport of bacteria and yeasts to vaginal flora. For that, in-situ polymerization of 2-substituted oxazolines was performed within the polyethylene matrix using supercritical carbon dioxide. The cationic ring-opening polymerization process was followed by end-capping with N,N-dimethyldodecylamine. Furthermore, for the same propose, the polyethylene matrix was impregnated with lavender oil in supercritical medium. The obtained materials were characterized physical and morphologically and the antimicrobial activity against bacteria and yeasts was accessed. Materials modified using 2-substituted oxazolines showed an effective killing ability for all the tested microorganisms, while the materials modified with lavender oil did not show antimicrobial activity. Only materials modified with oligo(2-ethyl-2-oxazoline) maintain the activity during the long term stability. Furthermore, the cytotoxicity of the materials was tested, confirming their biocompatibilty. Regarding the inhaler, its surface was modified in order to improve powder flowability and consequently, to reduce powder retention in the inhaler´s nozzle. New dry powder inhalers (DPIs), with different needle’s diameters, were evaluated in terms of internal resistance and uniformity of the emitted dose. It was observed that they present a mean resistance of 0.06 cmH2O0.5/(L/min) and the maximum emitted dose obtained was 68.9% for the inhaler with higher needle´s diameter (2 mm). Thus, this inhaler was used as a test and modified by the coating with a commonly-used force control agent, magnesium stearate, dried with supercritical carbon dioxide (scCO2) and the uniformity of delivered dose tests were repeated. The modified inhaler showed an increase in emitted dose from 68.9% to 71.3% for lactose and from 30.0% to 33.7% for Foradil.

Development of Total Quality Management System in Seafood (Freezing) Industry in Kerala

Quality related problems have become dominant in the seafood processing industry in Kerala. This has resulted in the rejection of seafood sent from India to many destinations. The latest being the total block listing of seafood companies from India from being exported to Europe and partial block listing by the US. The quality systems prevailed in the seafood industry in India were outdated and no longer in use in the developed world. According to EC Directive discussed above all the seafood factories exporting to European countries have to adopt HACCP. Based on this, EIA has now made HACCP system mandatory in all the seafood processing factories in India. This transformation from a traditional product based inspection system to a process control system requires thorough changes in the various stages of production and quality management. This study is conducted by the author with to study the status of the existing infrastructure and quality control system in the seafood industry in Kerala with reference to the recent developments in the quality concepts in international markets and study the drawbacks, if any, of the existing quality management systems in force in the seafood factories in Kerala for introducing the mandatory HACCP concept. To assess the possibilities of introducing Total Quality Management system in the seafood industry in Kerala in order to effectively adopt the HACCP concept. This is also aimed at improving the quality of the products and productivity of the industry by sustaining the world markets in the long run.

Combining Human and Machine Brains - Practical systems in information & control

In this paper a look is taken at how the use of implant technology can be used to either increase the range of the abilities of a human and/or diminish the effects of a neural illness, such as Parkinson's Disease. The key element is the need for a clear interface linking the human brain directly with a computer. The area of interest here is the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Pilot tests and experimentation are invariably carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed here. The paper goes on to describe human experimentation, in particular that carried out by the author himself, which led to him receiving a neural implant which linked his nervous system bi-directionally with the internet. With this in place neural signals were transmitted to various technological devices to directly control them. In particular, feedback to the brain was obtained from the fingertips of a robot hand and ultrasonic (extra) sensory input. A view is taken as to the prospects for the future, both in the near term as a therapeutic device and in the long term as a form of enhancement.

Novel developments in process optimisation using predictive control

In industrial practice, constrained steady state optimisation and predictive control are separate, albeit closely related functions within the control hierarchy. This paper presents a method which integrates predictive control with on-line optimisation with economic objectives. A receding horizon optimal control problem is formulated using linear state space models. This optimal control problem is very similar to the one presented in many predictive control formulations, but the main difference is that it includes in its formulation a general steady state objective depending on the magnitudes of manipulated and measured output variables. This steady state objective may include the standard quadratic regulatory objective, together with economic objectives which are often linear. Assuming that the system settles to a steady state operating point under receding horizon control, conditions are given for the satisfaction of the necessary optimality conditions of the steady-state optimisation problem. The method is based on adaptive linear state space models, which are obtained by using on-line identification techniques. The use of model adaptation is justified from a theoretical standpoint and its beneficial effects are shown in simulations. The method is tested with simulations of an industrial distillation column and a system of chemical reactors.

The technocratic totalitarianism of construction process improvement: a critical perspective

The current research agenda for construction process improvement is heavily influenced by the rhetoric of business process re-engineering (BPR). In contrast to the wider literature on BPR, there is little evidence of critical thought within the construction management research community. A postmodernist interpretation is advocated whereby the reality of management practice is defined by the dominant management discourse. The persuasiveness of BPR rhetoric is analysed with particular reference to the way in which it plays on the insecurity of modern managers. Despite the lip service given to ‘empowerment’ and ‘teamwork’, the dominant theme of the re-engineering movement is that of technocratic totalitarianism. From a critical perspective, it is suggested that BPR is imposed on construction organizations to ensure continued control by the industry's dominant power groups. Whilst industry leaders are fond of calling for ‘attitudinal and cultural improvement’, the language of the accepted research agenda continually reinforces the industry's dominant culture of ‘control and command’. Therefore, current research directions in process improvement perpetuate existing attitudes rather than facilitating cultural change. The concept of lean construction is seen to be the latest manifestation of this phenomenon.