An evaluation of task analysis techniques for industrial process control

The concept of a task is fundamental to the discipline of ergonomics. Approaches to the analysis of tasks began in the early 1900's. These approaches have evolved and developed to the present day, when there is a vast array of methods available. Some of these methods are specific to particular contexts or applications, others more general. However, whilst many of these analyses allow tasks to be examined in detail, they do not act as tools to aid the design process or the designer. The present thesis examines the use of task analysis in a process control context, and in particular the use of task analysis to specify operator information and display requirements in such systems. The first part of the thesis examines the theoretical aspect of task analysis and presents a review of the methods, issues and concepts relating to task analysis. A review of over 80 methods of task analysis was carried out to form a basis for the development of a task analysis method to specify operator information requirements in industrial process control contexts. Of the methods reviewed Hierarchical Task Analysis was selected to provide such a basis and developed to meet the criteria outlined for such a method of task analysis. The second section outlines the practical application and evolution of the developed task analysis method. Four case studies were used to examine the method in an empirical context. The case studies represent a range of plant contexts and types, both complex and more simple, batch and continuous and high risk and low risk processes. The theoretical and empirical issues are drawn together and a method developed to provide a task analysis technique to specify operator information requirements and to provide the first stages of a tool to aid the design of VDU displays for process control.

Continuous property measurement techniques and physics based mathematical model for frost growth control

The development of a new set of frost property measurement techniques to be used in the control of frost growth and defrosting processes in refrigeration systems was investigated. Holographic interferometry and infrared thermometry were used to measure the temperature of the frost-air interface, while a beam element load sensor was used to obtain the weight of a deposited frost layer. The proposed measurement techniques were tested for the cases of natural and forced convection, and the characteristic charts were obtained for a set of operational conditions. ^ An improvement of existing frost growth mathematical models was also investigated. The early stage of frost nucleation was commonly not considered in these models and instead an initial value of layer thickness and porosity was regularly assumed. A nucleation model to obtain the droplet diameter and surface porosity at the end of the early frosting period was developed. The drop-wise early condensation in a cold flat plate under natural convection to a hot (room temperature) and humid air was modeled. A nucleation rate was found, and the relation of heat to mass transfer (Lewis number) was obtained. It was found that the Lewis number was much smaller than unity, which is the standard value usually assumed for most frosting numerical models. The nucleation model was validated against available experimental data for the early nucleation and full growth stages of the frosting process. ^ The combination of frost top temperature and weight variation signals can now be used to control the defrosting timing and the developed early nucleation model can now be used to simulate the entire process of frost growth in any surface material. ^

Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

Axis control optimization: autotuning techniques and frequency response analysis of industrial mechatronic systems

In the field of industrial automation, there is an increasing need to use optimal control systems that have low tracking errors and low power and energy consumption. The motors we are dealing with are mainly Permanent Magnet Synchronous Motors (PMSMs), controlled by 3 different types of controllers: a position controller, a speed controller, and a current controller. In this thesis, therefore, we are going to act on the gains of the first two controllers by going to find, through the TwinCAT 3 software, what might be the best set of parameters. To do this, starting with the default parameters recommended by TwinCAT, two main methods were used and then compared: the method of Ziegler and Nichols, which is a tabular method, and advanced tuning, an auto-tuning software method of TwinCAT. Therefore, in order to analyse which set of parameters was the best,several experiments were performed for each case, using the Motion Control Function Blocks. Moreover, some machines, such as large robotic arms, have vibration problems. To analyse them in detail, it was necessary to use the Bode Plot tool, which, through Bode plots, highlights in which frequencies there are resonance and anti-resonance peaks. This tool also makes it easier to figure out which and where to apply filters to improve control.

Proposal for the teaching of the chemical control of supragingival biofilm

The mechanical control of supragingival biofilm is accepted as one of the most important measures to treat and prevent dental caries and periodontal diseases. Nevertheless, maintaining dental surfaces biofilm-free is not an easy task. In this regard, chemical agents, mainly in the form of mouthwashes, have been studied to help overcome the difficulties involved in the mechanical control of biofilm. The aim of this paper was to discuss proposals for the teaching of supragingival chemical control (SCC) in order to improve dentists' knowledge regarding this clinical issue. Firstly, the literature regarding the efficacy of antiseptics is presented, clearly showing that chemical agents are clinically effective in the reduction of biofilm and gingival inflammation when used as adjuvant agents to mechanical control. Thus, it is suggested that the content related to SCC be included in the curricular grid of dental schools. Secondly, some essential topics are recommended to be included in the teaching of SCC as follows: skills and competencies expected of a graduate dentist regarding SCC; how to include this content in the curricular grid; teaching-learning tools and techniques to be employed; and program content.

Matched case-control study evaluating the frequency of the main agents associated with neonatal diarrhea in piglets

A case-control study was carried out in litters of 1 to 7-day-old piglets to identify the main infectious agents involved with neonatal diarrhea in pigs. Fecal samples (n=276) from piglets were collected on pig farms in the State of Rio Grande do Sul, Brazil, from May to September 2007. Litters with diarrhea were considered cases (n=129) and normal litters (n=147) controls. The samples were examined by latex agglutination test, PAGE, conventional isolating techniques, ELISA, PCR, and microscopic methods in order to detect rotavirus, bacterial pathogens (Escherichia coli, Clostridium perfringens type A and C, and Clostridium difficile), and parasites (Coccidian and Cryptosporidium spp.). Outbreaks of diarrhea were not observed during sampling. At least one agent was detected in fecal samples on 25 out of 28 farms (89.3%) and in 16 farms (57.1%) more than one agent was found. The main agents diagnosed were Coccidia (42.86%) and rotavirus (39.29%). The main agents identified in litters with diarrhea were Clostridium difficile (10.6%), Clostridium perfringens type A (8.8%) and rotavirus (7.5%); in control litters, Clostridium difficile (16.6%) and Coccidian (8.5%). Beta hemolytic Escherichia coli and Clostridium perfringens type C were not detected. When compared with controls, no agent was significantly associated with diarrhea in case litters. These findings stress the need for caution in the interpretation of laboratorial diagnosis of mild diarrhea in neonatal pigs, as the sole detection of an agent does not necessarily indicate that it is the cause of the problem.

Allosteric Control of Gating Mechanisms Revisited: The Large Conductance Ca(2+)-Activated K(+) Channel

Large-conductance Ca(2+)-activated K(+) channels (BK) play a fundamental role in modulating membrane potential in many cell types. The gating of BK channels and its modulation by Ca(2+) and voltage has been the subject of intensive research over almost three decades, yielding several of the most complicated kinetic mechanisms ever proposed. A large number of open and closed states disposed, respectively, in two planes, named tiers, characterize these mechanisms. Transitions between states in the same plane are cooperative and modulated by Ca(2+). Transitions across planes are highly concerted and voltage-dependent. Here we reexamine the validity of the two-tiered hypothesis by restricting attention to the modulation by Ca(2+). Large single channel data sets at five Ca(2+) concentrations were simultaneously analyzed from a Bayesian perspective by using hidden Markov models and Markov-chain Monte Carlo stochastic integration techniques. Our results support a dramatic reduction in model complexity, favoring a simple mechanism derived from the Monod-Wyman-Changeux allosteric model for homotetramers, able to explain the Ca(2+) modulation of the gating process. This model differs from the standard Monod-Wyman-Changeux scheme in that one distinguishes when two Ca(2+) ions are bound to adjacent or diagonal subunits of the tetramer.

Structural control of gold nanoparticles self-assemblies by layer-by-layer process

This work presents a novel way to introduce gold nanoparticles (Au NPs) in a multilayer polymer produced by the layer-by-layer (LbL) assembling technique. The technique chosen shows that, depending on the pH used, different morphological structures can be obtained from monolayer or bilayer Au NPs. The MEIS and RBS techniques allowed for the modelling of the interface polymer-NPs, as well as the understanding of the interaction of LbL system, when adjusting the pH in weak polyelectrolytes. The process reveals that the optical properties of multilayer systems could be fine-tuned by controlling the addition of metallic nanoparticles, which could also modify specific polarization responses.

Specification of Supervisory Control Systems for Ventricular Assist Devices

One of the most important recent improvements in cardiology is the use of ventricular assist devices (VADs) to help patients with severe heart diseases, especially when they are indicated to heart transplantation. The Institute Dante Pazzanese of Cardiology has been developing an implantable centrifugal blood pump that will be able to help a sick human heart to keep blood flow and pressure at physiological levels. This device will be used as a totally or partially implantable VAD. Therefore, an improvement on device performance is important for the betterment of the level of interaction with patient`s behavior or conditions. But some failures may occur if the device`s pumping control does not follow the changes in patient`s behavior or conditions. The VAD control system must consider tolerance to faults and have a dynamic adaptation according to patient`s cardiovascular system changes, and also must attend to changes in patient conditions, behavior, or comportments. This work proposes an application of the mechatronic approach to this class of devices based on advanced techniques for control, instrumentation, and automation to define a method for developing a hierarchical supervisory control system that is able to perform VAD control dynamically, automatically, and securely. For this methodology, we used concepts based on Bayesian network for patients` diagnoses, Petri nets to generate a VAD control algorithm, and Safety Instrumented Systems to ensure VAD system security. Applying these concepts, a VAD control system is being built for method effectiveness confirmation.

A simple and effective inverse projection scheme for void distribution control in topology optimization

The ability to control both the minimum size of holes and the minimum size of structural members are essential requirements in the topology optimization design process for manufacturing. This paper addresses both requirements by means of a unified approach involving mesh-independent projection techniques. An inverse projection is developed to control the minimum hole size while a standard direct projection scheme is used to control the minimum length of structural members. In addition, a heuristic scheme combining both contrasting requirements simultaneously is discussed. Two topology optimization implementations are contributed: one in which the projection (either inverse or direct) is used at each iteration; and the other in which a two-phase scheme is explored. In the first phase, the compliance minimization is carried out without any projection until convergence. In the second phase, the chosen projection scheme is applied iteratively until a solution is obtained while satisfying either the minimum member size or minimum hole size. Examples demonstrate the various features of the projection-based techniques presented.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Computationally efficient solution techniques for adsorption problems involving steep gradients in bidisperse particles

A piecewise uniform fitted mesh method turns out to be sufficient for the solution of a surprisingly wide variety of singularly perturbed problems involving steep gradients. The technique is applied to a model of adsorption in bidisperse solids for which two fitted mesh techniques, a fitted-mesh finite difference method (FMFDM) and fitted mesh collocation method (FMCM) are presented. A combination (FMCMD) of FMCM and the DASSL integration package is found to be most effective in solving the problems. Numerical solutions (FMFDM and FMCMD) were found to match the analytical solution when the adsorption isotherm is linear, even under conditions involving steep gradients for which global collocation fails. In particular, FMCMD is highly efficient for macropore diffusion control or micropore diffusion control. These techniques are simple and there is no limit on the range of the parameters. The techniques can be applied to a variety of adsorption and desorption problems in bidisperse solids with non-linear isotherm and for arbitrary particle geometry.

Modifying insect population age structure to control vector-borne disease

Age is a critical determinant of the ability of most arthropod vectors to transmit a range of human pathogens. This is due to the fact that most pathogens require a period of extrinsic incubation in the arthropod host before pathogen transmission can occur. This developmental period for the pathogen often comprises a significant proportion of the expected lifespan of the vector. As such, only a small proportion of the population that is oldest contributes to pathogen transmission. Given this, strategies that target vector age would be expected to obtain the most significant reductions in the capacity of a vector population to transmit disease. The recent identification of biological agents that shorten vector lifespan, such as Wolbachia, entomopathogenic fungi and densoviruses, offer new tools for the control of vector-borne diseases. Evaluation of the efficacy of these strategies under field conditions will be possible due to recent advances in insect age-grading techniques. Implementation of all of these strategies will require extensive field evaluation and consideration of the selective pressures that reductions in vector longevity may induce on both vector and pathogen.