Process Monitoring Control Research Articles

Linear Technology Corp.

AbstractIT & Technology (MIC: 10.2 SIC: 3674 NAIC: 334413)Linear Technology designs, manufactures and markets a variety of standard linear integrated circuits. Applications for Co.'s products include telecommunications, cellular telephones, networking products, notebook computers, computer peripherals, video/multimedia, industrial instrumentation, security monitoring devices, consumer products, medical devices, automotive electronics, factory automation, process control, and military and space systems. Co.'s principal product categories are: Amplifiers, High Speed Amplifiers, Voltage regulators, Voltage References, Interface, Data Converters, Radio Frequency Circuits, and Other.

A PCA-Based PCM Data Analyzing Method for Diagnosing Process Failures

In an IC process line, after a process is finished, the process control module or monitor (PCM) is tested and the data are examined so that the status of the process quality is known. In the case of a process failure, the root cause of the failure must be analyzed, and relevant actions must be taken to correct it. In this paper, we describe a novel way of diagnosing process failures. First, the tested PCM parameters, which are correlated to each other, are analyzed and transformed to a new set of independent parameters using principal component analysis (PCA). In the second step, the most important eigenvectors from PCA calculation are identified, and the causes of the process failures can therefore be extracted. Furthermore, using the PCA eigenvectors as a coordinate base, the state space of a process can be constructed. As a result, the process states from different lots of wafers can be compared; thus, it is possible to trace the IC processes, or even to predict a possible process failure, before it happens

Recent Development in Optical Chemical Sensors Coupling with Flow Injection Analysis

Optical techniques for chemical analysis are well established and sensors based on thesetechniques are now attracting considerable attention because of their importance in applications suchas environmental monitoring, biomedical sensing, and industrial process control. On the other hand,flow injection analysis (FIA) is advisable for the rapid analysis of microliter volume samples and canbe interfaced directly to the chemical process. The FIA has become a widespread automatic analyticalmethod for more reasons; mainly due to the simplicity and low cost of the setups, their versatility, andease of assembling. In this paper, an overview of flow injection determinations by using opticalchemical sensors is provided, and instrumentation, sensor design, and applications are discussed. Thiswork summarizes the most relevant manuscripts from 1980 to date referred to analysis using opticalchemical sensors in FIA.

Biological denitrification in drinking water using Glycyrrhiza glabra and Arunda donax as the carbon source

In this research, two natural organic substances; liquorice ( Glycyrrhiza glabra) and giant reed ( Arundo donax) were investigated as a carbon source in the biological denitrification of drinking water. These materials act as a solid substrate and bio-film carrier. The experiments were carried out in batch, semi-batch and continuous processes. Complete denitrification was achieved with G. glabra. The removal efficiency of A. donax varied between 87 and 100% according to the type of process used. It was found that the nitrate removal rate of G. glabra was 6.96 mg/(L day) N-NO 3 and the nitrate removal rate of A. donax was 4.23 mg/(L day) N-NO 3. Results showed that these organic substrates could be used as an alternative carbon source for denitrification with complex process control and continuous monitoring. It should be noted that carbon source should be changed periodically for the continuation of the process.

Using the stress response to monitor process control: pathways to more effective bioremediation

Environmental contamination with a variety of pollutants has prompted the development of effective bioremediation strategies. But how can these processes be best monitored and controlled? One avenue under investigation is the development of stress response systems as tools for effective and general process control. Although the microbial stress response has been the subject of intensive laboratory investigation, the environmental reflection of the laboratory response to specific stresses has been little explored. However, it is only within an environmental context, in which microorganisms are constantly exposed to multiple changing environmental stresses, that there will be full understanding of microbial adaptive resiliency. Knowledge of the stress response in the environment will facilitate the control of bioremediation and other processes mediated by complex microbial communities.

On‐Line Measurement of Gas Production Rates

Gas evolution rates represent an important variable to track in biological and certain electrochemical processes. Accurate gas flow rate sensors exist for gas streams possessing a pressure head, such as when pressurized air or oxygen is delivered to a fermentation process. However, these devices impose pressure heads that can inhibit gas production and, therefore, yield false measurements. Examples of effected processes would include electrochemical production of a gas at the electrode (e.g., electrolysis) or anaerobic fermentation (e.g., anaerobic production of methane). In this work, we present an on-line gas measurement technique that measures on-line gas production from an anaerobic microbial process that is continuously fed simulated food waste over a 6-month period. Commentary is given on the sensor's accuracy and ease of use within the context of long-term operation, ability to measure both low and high gas production rates, as well as its potential for process control and system-health monitoring.

An SPC monitoring system for cycle-based waveform signals using haar transform

Due to the rapid development of computer and sensing technology, many measurements of process variables are readily available in manufacturing processes. These measurements carry a large amount of information about process conditions. It is highly desirable to develop a process monitoring and diagnosis methodology that can utilize this information. In this paper, a statistical process control monitoring system is developed for a class of commonly available process measurements-cycle-based waveform signals. This system integrates the statistical process control technology and the Haar wavelet transform. With it, one can not only detect a process change, but also identify the location and estimate the magnitude of the process mean shift within the signal. A case study involving a stamping process demonstrates the effectiveness of the proposed methodology on the monitoring of the profile-type data. Note to Practitioners-Cycle-based signal refers to an analog or digital signal that is obtained through automatic sensing during each operation cycle of a manufacturing process. The cycle-based signal is very common in various manufacturing processes (e.g., forming force in stamping processes, the holding force, and the current signals in spot welding processes, the insertion force in the engine assembly process). In general, cycle-based signals contain rich process information. In this paper, cycle-based signal monitoring will be accomplished by monitoring the wavelet transformation of the signal, instead of monitoring the raw observations themselves. Further, a decision-making technique is developed using the SPC monitoring system to locate where the mean shift occurred and to estimate magnitudes of mean shifts. Thus, this paper presents a generic framework for the enhanced statistical process control technique of cycle-based signals.

Sub-ppbv nitric oxide concentration measurements using cw thermoelectrically cooled quantum cascade laser-based integrated cavity output spectroscopy

A nitric oxide (NO) gas sensor based on a thermoelectrically cooled, continuous-wave, distributed feedback quantum cascade laser operating at 5.45 μm (1835 cm-1) and off-axis integrated cavity output spectroscopy combined with a wavelength-modulation technique was developed to determine NO concentrations at the sub-ppbv levels that are essential for a number of applications, such as medical diagnostics, environmental monitoring, and industrial process control. The sensor employs a 50-cm-long high-finesse optical cavity that provides an effective path length of ∼700 m. A noise equivalent (SNR=1) minimum detection limit of 0.7 ppbv with a 1-s observation time was achieved.

Water safety plans for piped urban supplies in developing countries: a case study from Kampala, Uganda

The World Health Organisation (WHO) promote the use of water safety plans (WSPs) in the 3rd edition of the Guidelines for Drinking-Water Quality (2004). WSPs place an emphasis on risk assessment coupled with risk management, with simple indicators to monitor process control and periodic verification through audit and microbial indicators. A WSP was developed for the Kampala piped water supply in Uganda by the National Water and Sewerage Corporation. The use of risk maps was found to greatly aid the identification of hazardous events in the distribution system. A validation exercise was performed that showed the WSP was properly designed. The study shows WSPs can be successfully developed for utilities in developing countries and offer significant cost savings in water quality control. Senior management endorsement was found to be essential to provide the authority to develop and implement the activities required for effective water safety management.

DNA microarray detection of nitrifying bacterial 16S rRNA in wastewater treatment plant samples

A small scale DNA microarray containing a set of oligonucleotide probes targeting the 16S rRNAs of several groups of nitrifying bacteria was developed for the monitoring of wastewater treatment plant samples. The microarray was tested using reference rRNAs from pure cultures of nitrifying bacteria. Characterization of samples collected from an industrial wastewater treatment facility demonstrated that nitrifying bacteria could be detected directly by microarray hybridization without the need for PCR amplification. Specifically, the microarray detected Nitrosomonas spp. but did not detect Nitrobacter. The specificity and sensitivity of direct detection was evaluated using on-chip dissociation analysis, and by two independent analyses—an established membrane hybridization format and terminal restriction fragment length polymorphism fingerprinting (T-RFLP). The latter two analyses also revealed Nitrospira and Nitrobacter to be contributing populations in the treatment plant samples. The application of DNA microarrays to wastewater treatment systems, which has been demonstrated in the current work, should offer improved monitoring capabilities and process control for treatment systems, which are susceptible to periodic failures.

Refined Raman Spectroscopy: Bringing New Insight into Industrial Processes

Fiber probes and ease of use make Raman spectroscopy systems attractive for monitoring process control in a range of industries from pharmaceuticals to petrochemicals. The authors describe the Raman effect and discuss system and monitoring basics.

In situ and on-line monitoring of CO in an industrial glass furnace by mid-infrared difference-frequency generation laser spectroscopy

A compact mid-infrared (MIR) laser spectrometer based on difference-frequency generation (DFG) is applied as a portable and sensitive gas sensor for industrial process control and pollutant monitoring. We demonstrate the performance of such a MIR DFG gas sensor by recording the absorption spectra of the carbon monoxide (CO) P(28) absorption line in the atmosphere of a gas-fired glass melting furnace. For a gas temperature of approximately 1100 degrees C, the CO concentration in the recuperator channel is measured to be 400 parts per million.

Principal‐component analysis of multiscale data for process monitoring and fault diagnosis

AbstractAn approach is presented to multivariate statistical process control (MSPC) for process monitoring and fault diagnosis based on principal‐component analysis (PCA) models of multiscale data. Process measurements, representing the cumulative effects of many underlying process phenomena, are decomposed by applying multiresolution analysis (MRA) by wavelet transformations. The decomposed process measurements are rearranged according to their scales, and PCA is applied to these multiscale data to capture process variable correlations occurring at different scales. Choosing an orthonormal mother wavelet allows each principal component to be a function of the process variables at only one scale level. The proposed method is discussed in the context of other multiscale approaches, and illustrated in detail using simulated data from a continuous stirred tank reactor (CSTR) system. A major contribution of the paper is to extend fault isolation methods based on contribution plots to multiscale approaches. In particular, once a fault is detected, the contributions of the variations at each scale to the fault are computed. These scale contributions can be very helpful in isolating faults that occur mainly at a single scale. For those scales having large contributions to the fault, one can further compute the variable contributions to those scales, thereby making fault diagnosis much easier. A comparison study is done through Monte Carlo simulation. The proposed method can enhance fault detection and isolation (FDI) performance when the frequency content of a fault effect is confined to a narrow‐frequency band. However, when the fault frequency content is not localized, the multiscale approaches perform very comparably to the standard single‐scale approaches, and offer no real advantage. © 2004 American Institute of Chemical Engineers AIChE J, 50: 2891–2903, 2004

Statistical Process Control Charts for Batch Operations Based on Independent Component Analysis

A significant step forward in recent years, in regard to multivariate statistical process control (MSPC) for operational condition monitoring and fault diagnosis, has been the introduction of principal component analysis (PCA) for the compression of process data. An alternative technique that has been studied more recently for data compression is independent component analysis (ICA). Published work has shown that, in some applications of statistical process monitoring, ICA-based methods have exhibited advantages over those based on other data compression techniques. However, it is inappropriate to use ICA in the same way as PCA to derive Hotelling's T2 and SPE (squared prediction error) charts, because the independent components are separated by maximizing their non-Gaussianity, whereas the satisfying Gaussian distribution is the basis of T2 and SPE monitoring charts, as well as univariate statistical process control (SPC) charts. In this paper, we propose a new method for deriving SPC charts based on ICA...

Measurement of protein-like fluorescence in river and waste water using a handheld spectrophotometer

Protein-like fluorescence intensity in rivers increases with increasing anthropogenic DOM inputs from sewerage and farm wastes. Here, a portable luminescence spectrophotometer was used to investigate if this technology could be used to provide both field scientists with a rapid pollution monitoring tool and process control engineers with a portable waste water monitoring device, through the measurement of river and waste water tryptophan-like fluorescence from a range of rivers in NE England and from effluents from within two waste water treatment plants. The portable spectrophotometer determined that waste waters and sewerage effluents had the highest tryptophan-like fluorescence intensity, urban streams had an intermediate tryptophan-like fluorescence intensity, and the upstream river samples of good water quality the lowest tryptophan-like fluorescence intensity. Replicate samples demonstrated that fluorescence intensity is reproducible to ±20% for low fluorescence, ‘clean’ river water samples and ±5% for urban water and waste waters. Correlations between fluorescence measured by the portable spectrophotometer with a conventional bench machine were 0.91; (Spearman's rho, n=143), demonstrating that the portable spectrophotometer does correlate with tryptophan-like fluorescence intensity measured using the bench spectrophotometer.

Germanium profile design options for SiGe LEC HBTs

Silicon–Germanium (SiGe) heterojunction bipolar transistors (HBTs) with a low emitter doping concentration (LEC) are investigated with respect to their electrical characteristics in dependence of the Germanium profile shape. The study is based on one-dimensional (1D) device simulation using a realistic doping and Ge profile as baseline. While keeping the doping profile unchanged the Ge profile is modified to evaluate its impact on major electrical figure of merits such as transit frequency, ideality factor, early voltage, noise figure, as well as on process control monitors (PCMs) such as internal base sheet resistance and area specific depletion capacitances. The variations in electrical characteristics and PCMs are briefly explained on a theoretical basis with regard to the impact on compact and statistical modeling.

Biosensor for rapid phosphate monitoring in a sequencing batch reactor (SBR) system

A thick-film phosphate biosensor based on hydrogel immobilized pyruvate oxidase (POD) has been developed for rapid phosphate process control monitoring in an experimental sequencing batch reactor (SBR) system. We have employed a phosphate biosensor in an off-line monitoring of phosphate concentrations in a bench scale SBR. Measurements with biosensor show a good correlation (r 2=0.98) with those of commercial colorimetric phosphate testing kits. The signal response time was 1 min with a detection limit of 5 μM. The biosensor method showed a good operational stability, needed less experimental procedures and a small sample size (∼20 μl). This allows its practical application for rapid phosphate measurements to obtain real time process data in a SBR system.

The advent of MEMS in space

An overview of the MEMS activity at the French Space Agency (CNES) is presented. At present, MEMS are in the introduction phase and failure analysis and quality assurance (FA/QA) activities are underway for a large variety of MEMS technologies. This paper presents the CNES roadmap and methodology developed to assess the reliability of MEMS for space applications. The presented approach focuses, in particular, on the use of advanced analytical models, test vehicles, process control monitoring test structures and simulation tools to control and validate the quality of a technology. It also discusses the FA know-how and associated techniques acquired by CNES to observe, characterize, prepare and test in controlled environment MEMS processes. Finally, case studies illustrating the CNES MEMS FA/QA strategy are presented.

Multivariate statistical process control for continuous monitoring of networked early warning fire detection (EWFD) systems

Sensor array networks provide much information concerning an environment if the data is adequately used. However, monitoring large networks of sensor arrays can be data intensive. Multivariate statistical process control (MSPC) methods allow monitoring of an entire system at a supervisory level. These methods are demonstrated for fire detection using the early warning fire detection (EWFD) system. The EWFD system comprised of four sensors that included photoelectric and ionization smoke detectors, as well as carbon monoxide and carbon dioxide sensors. Fourteen sensor arrays were distributed in 10 compartments and passageways throughout the ex-USS SHADWELL, the advanced damage control fire research platform of the Naval Research Laboratory. Data was collected for a series of smoldering and flaming fire sources as well as nuisance sources in different compartments over two decks. The network of sensor responses, location and temporal data are used to identify events, determine source location and monitor fire rate of growth. Hotelling’s statistic and the Q-statistic are employed initially for event detection. Subsequently, contribution plots are used to determine source location, rate of growth and to discriminate between actual fires and their byproducts in adjacent compartments. The response times of the MSPC method are compared to the commercial smoke detectors co-located with the EWFD systems. MSPC is shown to be an efficient method for continuous monitoring of EWFD systems.

Surface quality monitoring for process control by on-line vibration analysis using an adaptive spline wavelet algorithm

The dynamic behaviour of wood machining processes affects the surface finish quality of machined workpieces. In order to meet the requirements of increased production efficiency and improved product quality, surface quality information is needed for enhanced process control. However, current methods using high price devices or sophisticated designs, may not be suitable for industrial real-time application. This paper presents a novel approach of surface quality evaluation by on-line vibration analysis using an adaptive spline wavelet algorithm, which is based on the excellent time–frequency localization of B-spline wavelets. A series of experiments have been performed to extract the feature, which is the correlation between the relevant frequency band(s) of vibration with the change of the amplitude and the surface quality. The graphs of the experimental results demonstrate that the change of the amplitude in the selective frequency bands with variable resolution (linear and non-linear) reflects the quality of surface finish, and the root sum square of wavelet power spectrum is a good indication of surface quality. Thus, surface quality can be estimated and quantified at an average level in real time. The results can be used to regulate and optimize the machine's feed speed, maintaining a constant spindle motor speed during cutting. This will lead to higher level control and machining rates while keeping dimensional integrity and surface finish within specification.