Process Monitoring Strategy Research Articles

Potential strategies for process control and monitoring of stabilization of dairy wastewaters in batch aerobic treatment systems

This research was conducted to study the relationships between pH, dissolved oxygen (DO), and oxidation–reduction potential (ORP) during low-intensity aeration of dairy wastewaters and to determine potential strategies for monitoring and/or control of this treatment process. The results of this study ascertained that, close to the detection limit of commercially available DO probes (0.1 mg/l), DO is a poor indicator of the oxidation–reduction status of the dairy wastewater during this treatment processes. All the three parameters (ORP, DO, and pH) displayed features defining stabilization of the wastewater and hence all three can be used singly or in combination to monitor and/or to control this treatment process. The study also established strong linear relations between ORP and the log of DO; manifest in the high-correlation coefficients of 0.98 and 0.95 at the aeration rates of 0.067 and 0.034-l [air] l −1 [manure] min −1, respectively. The latter observation confirms the higher sensitivity of ORP over DO at very low-oxygen levels; a fact which indicates the superiority of ORP in the monitoring and control of oxidation–reduction status of the wastewater close to DO detection limit. Finally, both total volatile solids (TVS) and chemical oxygen demand (COD), which are common measures of wastewater stabilization; correlated well with pH, DO, and ORP during the entire treatment process. However, because the measurements of DO are erratic close to the DO detection limit, and because ORP and pH measurements are much more consistent than the DO in the entire range of treatment, these two parameters will be more suitable for monitoring and control especially of extended aeration treatments.

TDDB Data Generation for Fast Lifetime Projections Based on $V$-Ramp Stress Data

Reduced failure rates required by the industry lead to increased costs and time loss for the chip manufacturer since the efforts for continuous process improvements, qualification, screening, and increased test coverage are generally not paid by the customer. However, related costs can be reduced by improved/accelerated reliability testing methods and an approach to a knowledge-based and application-specific qualification and process monitoring strategy. One example of saving time (and costs) during gate oxide reliability testing is given in this paper, showing that time-dependent dielectric breakdown (TDDB) data for lifetime extrapolation and quality assessment can be generated from linear ramped voltage test (RVT) data with high accuracy. Given the parameter of the RVT stress profile, the concept of equivalence is successfully applied to convert stress time data at each ramp stress level to corresponding accumulated equivalent ages at any one stress level. Taking into account these ages until breakdown, failure probabilities with the model parameters of the stress-life relationship being the only fitting parameters can directly be computed and converted to TDDB failure distributions.

COMBINING ON-LINE PROCESS MEASUREMENTS AND MODELS TO EMPIRICALLY TEST STRATEGIES FOR PROCESS MONITORING, DIAGNOSIS AND CONTROL

Testing strategies for process monitoring, diagnosis and control is expensive, and usually requires either complex pilot plant facilities or to deal with the hard constraints posed by experimentation in real plants. The experience developing hybrid systems in the mineral processing area is discussed and its application to flotation columns and solvent extraction processes is presented. The main idea is that the essential phenomena underlying a process can be divided in two aspects: the hydrodynamics and the metallurgy. The first can be experimentally implemented in pilot plants where the main streams are mixed and separated, at a low cost. However, the process metallurgy requires expensive instrumentation, store facilities, chemical reagent consumptions. The use of metallurgic models, on-line fed with operating measured variables describing the hydrodynamics, are proposed as a sustitute.

Monitoring of Dynamic Mechanical Parameters in Resistance Spot Welding of Aluminium

Dynamic electrode displacement and force were characterized during resistance spot welding of aluminium alloy 5182 sheets using a medium-frequency direct welding current. It was found that rates of increase in electrode displacement and force were both proportional to welding current. Both electrode displacement and force experienced a sudden drop when weld metal expulsion occurred. However, the rate of increase in electrode displacement did not reach zero during welding even for joints with sufficient nugget diameter, while electrode force peaked for the same nugget diameters. Possible strategies for process monitoring and control are also discussed.

Broaching of Ti-6-4 – Detection of Workpiece Surface Anomalies on Dovetail Slots through Process Monitoring

Surface anomalies induced by abusive broaching represent a concern for the safety of critical components of aero-engines. Using acoustic emission and force signals, the paper reports on process monitoring techniques to detect surface anomalies when abusively broaching dovetail slots in Ti-6-4. Parallel surface inspection helped in defining the correlation between the occurrence of uneven events in the output signals and the appearance/location of anomalies on the broached surfaces. The findings support the definition of process monitoring strategies to detect workpiece surface anomalies including surface deformation/ overheating, directed scoring and smearing of parent material.

Dynamic Electrode Force and Displacement in Resistance Spot Welding of Aluminum

Dynamic electrode displacement and force were characterized during resistance spot welding of aluminum alloy 5182 sheets using a medium-frequency direct-current welder. It was found that both electrode displacement and force increased rapidly at the beginning of the welding stage and then at a reducing rate. Rates of increase in electrode displacement and force were both proportional to welding current. And both electrode displacement and force experienced a sudden drop when weld metal expulsion occurred. However, the rate of increase in electrode displacement did not reach zero during welding even for joints with sufficient nugget diameter, while electrode force peaked when a large nugget diameter was produced. Possible strategies for process monitoring and control were also discussed.

Process monitoring strategies for surface mount manufacturing processes

Establishing reliable surface mount assemblies requires robust design and assembly practices, including stringent process control schemes for achieving high yield processes and high quality solder interconnects. Conventional Shewhart-based process control charts prevalent in today's complex surface mount manufacturing processes are found to be inadequate as a result of autocorrelation, high false alarm probability, and inability to detect process deterioration. Hence, new strategies are needed to circumvent the shortcomings of traditional process control techniques. In this article, the adequacy of Shewhart models in a surface mount manufacturing environment is examined and some alternative solutions and strategies for process monitoring are discussed. For modeling solder paste deposition process data, a time series analysis based on neural network models is highly desirable for both controllability and predictability. In particular, neural networks can be trained to model the autocorrelated time series, learn historical process behavior, and forecast future process performance with low prediction errors. This forecasting ability is especially useful for early detection of solder paste deterioration, so that timely remedial actions can be taken, minimizing the impact on subsequent yields of downstream processes. As for the automated component placement process where very low fraction nonconforming frequently occurs, control-charting schemes based on cumulative counts of conforming items produced prior to detection of nonconforming items is more sensitive in flagging process deterioration. For the reflow soldering and wave-soldering processes, the use of demerit control charts is appealing as it provides not only better control when various defects with a different degree of severity are encountered, but also leads to an improved ARL performance. Illustrative examples of actual process data are presented to demonstrate these approaches.

Process Monitoring during Normal Operations at Canadian Nuclear Power Plants

This paper summarizes the findings from several observational studies to characterize the basis for a process monitoring strategy used by operators in ‘normal’ operations at CANDU nuclear power plants. These studies were undertaken in support of projects to develop improved control room displays and information systems to better support operators in both normal and abnormal operating situations. With the assistance of operators from several plants, an underlying basis for process monitoring was defined and a ‘generic’ strategy for monitoring process conditions in ‘normal’ operations has been established.

The Tennessee Eastman Problem as a Process Monitoring Benchmark

Abstract By specifying a number of possible faults and by incorporating a control scheme due to McAvoy, Ye and Gang, the Tennessee Eastman problem is extended to provide a benchmark with which to assess process monitoring strategies. A simple G2-implemented monitor is then used to categorize the various faults and disturbances into those that might be detected and subsequently localized by the application of either a heuristic approach or a mass balance approach due to Kramer

The Baroreceptor Reflex: A Biological Control System with Applications in Chemical Process Control

Many industrial chemical processes are difficult to control effectively using existing techniques because they are complex, interconnected, nonlinear systems which lack reliable on-line measurements of key process variables. Due to increasingly stringent demands on product quality, energy utilization, and environmental responsibility, more effective control strategies are needed for these processes. By contrast, extremely complex biological systems routinely operate under more stringent requirements on product quality and failure tolerance as a result of the robust, high performance computation and control functions provided by the brain. Thus, studying and understanding these biological control systems, and ultimately reverse engineering their functions, should provide ample alternative techniques for developing effective control systems for chemical processes. The objective of the paper is to present one such biological control system - the baroreceptor reflex, which provides short-term regulation of arterial blood pressure - and identify potential applications in chemical process control. Novel process monitoring, modeling, and control strategies which are currently being developed by reverse engineering the architectural and computational properties of this reflex are discussed. Preliminary results on techniques for sensor fusion based control, nonlinear modeling, and control of multiple-input, single-output systems which have been abstracted from the reflex are also presented

Modeling and Control of Polymerization Reactors

The current state and key issues in the modeling and control of polymerization reactors are surveyed. The physical phenomena, types of reactor models, sensor hardware, process monitoring strategies, critical control problems, and control system design strategies are among the issues discussed. Extensive references are provided for further reading.