Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Effects of the preventive and corrective adjustments in economical designs for online process control for attributes with misclassification errors

The procedure for online process control by attributes consists of inspecting a single item at every m produced items. It is decided on the basis of the inspection result whether the process is in-control (the conforming fraction is stable) or out-of-control (the conforming fraction is decreased, for example). Most articles about online process control have cited the stoppage of the production process for an adjustment when the inspected item is non-conforming (then the production is restarted in-control, here denominated as corrective adjustment). Moreover, the articles related to this subject do not present semi-economical designs (which may yield high quantities of non-conforming items), as they do not include a policy of preventive adjustments (in such case no item is inspected), which can be more economical, mainly if the inspected item can be misclassified. In this article, the possibility of preventive or corrective adjustments in the process is decided at every m produced item. If a preventive adjustment is decided upon, then no item is inspected. On the contrary, the m-th item is inspected; if it conforms, the production goes on, otherwise, an adjustment takes place and the process restarts in-control. This approach is economically feasible for some practical situations and the parameters of the proposed procedure are determined minimizing an average cost function subject to some statistical restrictions (for example, to assure a minimal levelfixed in advanceof conforming items in the production process). Numerical examples illustrate the proposal.

Sterilization of Medical Devices by Ethylene Oxide, Determination of the Dissipation of Residues, and Use of Green Fluorescent Protein as an Indicator of Process Control

Ethylene oxide (EO) is used to sterilize Oxygenator and Tubing applied to heart surgery. Residual levels of EO and its derivatives, ethylene chlorohydrin (ECH) and ethylene glycol (EG), may be hazardous to the patients. Therefore, it must be removed by the aeration process. This study aimed to estimate the minimum aeration time for these devices to attain safe limits for use (avoiding excessive aeration time) and to evaluate the Green Fluorescent Protein (GFP) as a biosensor capable of best indicating the distribution and penetration of EO gas throughout the sterilization chamber. Sterilization cycles of 2, 4, and 8 h were monitored by Bacillus atrophaeus ATCC 9372 as a biological indicator (131) and by the GFP. Residual levels of EO, ECH, and EG were determined by gas chromatography (GC), and the residual dissipation was studied. Safe limits were reached right after the sterilization process for Oxygenator and after 204 h of aeration for Tubing. In the 2 h cycle, the GFP concentration decreased from 4.8 (+/- 3.2)% to 7.5 (+/- 2.5)%. For the 4 h cycle, the GFP concentration decreased from 17.4 (+/- 3.0)% to 21.5 (+/- 6.8)%, and in the 8 h cycle, it decreased from 22.5 (+/- 3.2)% to 23.9 (+/- 3.9)%. This finding showed the potentiality for GFP applications as an EO biosensor. (C) 2009 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 9113: 626-630, 2009

Adequacy of Cold Rolling Models to Upgrade Set-up Generation Systems

This paper presents two strategies for the upgrade of set-up generation systems for tandem cold mills. Even though these mills have been modernized mainly due to quality requests, their upgrades may be made intending to replace pre-calculated reference tables. In this case, Bryant and Osborn mill model without adaptive technique is proposed. As a more demanding modernization, Bland and Ford model including adaptation is recommended, although it requires a more complex computational hardware. Advantages and disadvantages of these two systems are compared and discussed and experimental results obtained from an industrial cold mill are shown.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

A stable MPC with zone control

Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

Stable MPC for tracking with maximal domain of attraction

In this work, a stable MPC that maximizes the domain of attraction of the closed-loop system is proposed. The proposed approach is suitable to real applications in the sense that it accounts for the case of output tracking, it is offset free if the output target is reachable and minimizes the offset if some of the constraints are active at steady state. The new approach is based on the definition of a Minkowski functional related to the input and terminal constraints of the stable infinite horizon MPC. It is also shown that the domain of attraction is defined by the system model and the constraints, and it does not depend on the controller tuning parameters. The proposed controller is illustrated with small order examples of the control literature. (C) 2011 Elsevier Ltd. All rights reserved.

MPC for tracking zone regions

This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables - possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column. (C) 2010 Elsevier Ltd. All rights reserved.

Infinite horizon MPC with non-minimal state space feedback

In the MPC literature, stability is usually assured under the assumption that the state is measured. Since the closed-loop system may be nonlinear because of the constraints, it is not possible to apply the separation principle to prove global stability for the Output feedback case. It is well known that, a nonlinear closed-loop system with the state estimated via an exponentially converging observer combined with a state feedback controller can be unstable even when the controller is stable. One alternative to overcome the state estimation problem is to adopt a non-minimal state space model, in which the states are represented by measured past inputs and outputs [P.C. Young, M.A. Behzadi, C.L. Wang, A. Chotai, Direct digital and adaptative control by input-output, state variable feedback pole assignment, International journal of Control 46 (1987) 1867-1881; C. Wang, P.C. Young, Direct digital control by input-output, state variable feedback: theoretical background, International journal of Control 47 (1988) 97-109]. In this case, no observer is needed since the state variables can be directly measured. However, an important disadvantage of this approach is that the realigned model is not of minimal order, which makes the infinite horizon approach to obtain nominal stability difficult to apply. Here, we propose a method to properly formulate an infinite horizon MPC based on the output-realigned model, which avoids the use of an observer and guarantees the closed loop stability. The simulation results show that, besides providing closed-loop stability for systems with integrating and stable modes, the proposed controller may have a better performance than those MPC controllers that make use of an observer to estimate the current states. (C) 2008 Elsevier Ltd. All rights reserved.

Development and fabrication of an optimized thermo-electro-optic device using a Mach-Zehnder interferometer

The development and fabrication of a thermo-electro-optic sensor using a Mach-Zehnder interferometer and a resistive micro-heater placed in one of the device`s arms is presented. The Mach-Zehnder structure was fabricated on a single crystal silicon substrate using silicon oxynitride and amorphous hydrogenated silicon carbide films to form an anti-resonant reflective optical waveguide. The materials were deposited by Plasma enhanced chemical vapor deposition technique at low temperatures (similar to 320 degrees C). To optimize the heat transfer and increase the device response with current variation, part of the Mach-Zehnder sensor arm was suspended through front-side bulk micromachining of the silicon substrate in a KOH solution. With the temperature variation caused by the micro-heater, the refractive index of the core layer of the optical waveguide changes due to the thermo-optic effect. Since this variation occurs only in one of the Mach-Zehnder`s arm, a phase difference between the arms is produced, leading to electromagnetic interference. In this way, the current applied to the micro-resistor can control the device output optical power. Further, reactive ion etching technique was used in this work to define the device`s geometry, and a study of SF6 based etching rates on different composition of silicon oxynitride films is also presented. (C) 2007 Elsevier B.V. All rights reserved.

Control of Two-Photon Absorption in Organic Compounds by Pulse Shaping: Spectral Dependence

In this work, we investigate the control of the two-photon absorption process of a series of organic compounds via spectral phase modulation of the excitation pulse. We analyzed the effect of the pulse central wavelength on the control of the two-photon absorption process for each compound. Depending on the molecules` two-photon absorption position relative to the excitation pulse wavelength, different levels of coherent control were observed. By simulating the two-photon transition probability in molecular systems, taking into account the band structure and its positions, we could explain the experimental results trends. We observed that the intrapulse coherent interference plays an important role in the nonlinear process control besides just the pulse intensity modulation.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

Economic design of an X chart for short-run production

The aim of this paper is to present an economical design of an X chart for a short-run production. The process mean starts equal to mu(0) (in-control, State I) and in a random time it shifts to mu(1) > mu(0) (out-of-control, State II). The monitoring procedure consists of inspecting a single item at every m produced ones. If the measurement of the quality characteristic does not meet the control limits, the process is stopped, adjusted, and additional (r - 1) items are inspected retrospectively. The probabilistic model was developed considering only shifts in the process mean. A direct search technique is applied to find the optimum parameters which minimizes the expected cost function. Numerical examples illustrate the proposed procedure. (C) 2009 Elsevier B.V. All rights reserved.

Cyclic Fatigue Resistance of Rotary Nickel-Titanium Instruments Submitted to Nitrogen Ion Implantation

Introduction: The aim of this study was to assess cyclic fatigue resistance in rotary nickel-titanium instruments submitted to nitrogen ion implantation by using a custom-made cyclic fatigue testing apparatus. Methods: Thirty K3 files, size #25, taper 0.04, were divided into 3 experimental groups as follows: group A, 12 files exposed to nitrogen ion implantation at a dose of 2.5 x 10(17) ions/cm(2), accelerating voltage of 200 kV, currents of 1 mu A/cm(2), 130 degrees C temperature, and vacuum conditions of 10 x 10(-6) torr for 6 hours; group B, 12 nonimplanted files; and group C, 6 files submitted to thermal annealing for 6 hours at 130 degrees C. One extra file was used for process control. All files were submitted to a cyclic fatigue test that was performed with an apparatus that allowed the instruments to rotate freely, simulating rotary instrumentation of a curved canal (40-degree, 5-mm radius curve). An electric motor handpiece was used with a contra-angle of 16:1 at an operating speed of 300 rpm and a torque of 2 N-cm. Time to failure was recorded with a stopwatch in seconds and subsequently converted to number of cycles to fracture. Data were analyzed with the Student t test (P < .05). Results: Ion-implanted instruments reached significantly higher cycle numbers before fracture (mean, 510 cycles) when compared with annealed (mean, 428 cycles) and nonimplanted files (mean, 381 cycles). Conclusions: Our results showed that nitrogen ion implantation improves cyclic fatigue resistance in rotary nickel-titanium instruments. Industrial implementation. of this surface modification technique would produce rotary nickel-titanium instruments with a longer working life. (J Endod 2010;36:1183-1186)