Monitoring of pigmented surfaces in accelerated ageing process by ATR-FT-IR spectroscopy and multivariate control charts

This work is an extension of a method for monitoring the conservation state of pigmented surfaces presented in a previous paper. A cotton canvas painted with an organic pigment (Alizarin) was exposed to UV light in order to evaluate the effects of the applied treatment on the surface of the sample. The conservation state of the pigmented surface was monitored with ATR–FT-IR spectroscopy and multivariate control charts.

The IR spectra were analysed by principal component analysis (PCA) and the relevant principal components (PCs) were used for constructing multivariate Shewhart, cumulative sums (CUSUM) and simultaneous scores monitoring and residuals tracking (SMART) control charts.

These tools were successfully applied for the identification of the presence of relevant modifications occurring on the surface of the sample.

Finally, with the aim to more deeply investigate what happened to the sample surface during the UV exposure, a PCA of the residuals matrix of degradation analyses only, not present in the previous paper, was performed. This analysis produced interesting results concerning the identification of the processes taking place on the irradiated surface.     

Monitoring of paintings under exposure to UV light by ATR-FT-IR spectroscopy and multivariate control charts

This paper concerns the improvement of a method, already applied for the conservation state monitoring of wooden and painted surfaces, to a system closely simulating a real artwork, namely a canvas painted with mixtures of three organic pigments (Alizarin, Permanent Red, Phtalocyanine Green). Ten mixtures of these pigments, according to an augmented simplex-centroid design, were prepared, mixed with linseed oil and spread on 10 cotton canvas strips. Drying ended, all the samples were analysed by ATR-FT-IR spectroscopy to describe the superficial variability in normal conditions of conservation, i.e. when no degradation is present. Successively, the samples were exposed to artificial UV light simulating the action of an aggressive portion of sunlight. The IR spectra of the surfaces were regularly acquired to monitor the superficial changes due to the UV aggression. Treatment ended, a chemometric study based on the Principal Component Analysis of the spectroscopic data collected both in normal conditions of conservation and during the artificial accelerated ageing, was performed and the multivariate Shewhart and Cusum control charts were built with the scores of the significant PCs (principal components). PCA based control charts showed to be able to identify the presence of significant changes of the painted surfaces, to identify the starting of the degradations and to provide insights about the chemical alterations induced by the UV exposure.     

Monitoring of an industrial process by multivariate control charts based on principal component analysis

The control and monitoring of an industrial process is performed in this paper by the multivariate control charts. The process analysed consists of the bottling of the entire production of 1999 of the sparkling wine "Asti Spumante". This process is characterised by a great number of variables that can be treated with multivariate techniques. The monitoring of the process performed with classical Shewhart charts is very dangerous because they do not take into account the presence of functional relationships between the variables. The industrial process was firstly analysed by multivariate control charts based on Principal Component Analysis. This approach allowed the identification of problems in the process and of their causes. Successively, the SMART Charts (Simultaneous Scores Monitoring And Residual Tracking) were built in order to study the process in its whole. In spite of the successful identification of the presence of problems in the monitored process, the Smart chart did not allow an easy identification of the special causes of variation which casued the problems themselves.     

The state of conservation of painted surfaces in the presence of accelerated ageing processes monitored by use of FT-Raman spectroscopy and multivariate control charts

A new method has been developed for monitoring the degradation of paintings. Two inorganic pigments (ultramarine blue and red ochre) were blended with linseed oil and spread on canvas. Each canvas was subjected to simulated accelerated ageing in the presence of typical degradation agents (UV radiation and acidic solution). Periodically the painted surfaces were analysed by FT-Raman, to investigate the status of the surface. The data obtained were analysed by principal component analysis (PCA). Finally the Shewhart and cumulative sum control charts based on the relevant principal components (PC) and the so called scores monitoring and residuals tracking (SMART) charts were built. The method based on the use of PC to describe the process was found to enable identification of the presence of relevant modification occurring on the surface of the samples studied.Electronic supplementary material Supplementary material is available for this article at     

Monitoring analytical measurements in presence of two component measurement error

Control charts are increasingly adopted by laboratories for effective monitoring of analytical processes. Analytical methods are mostly subject to two types of measurement errors, i—additive and ii—multiplicative, or proportional, error. These errors have been combined in a single model, namely the two component error model (TCME) proposed by [1]. In this study we present a comparison among the performance of three widely used location control charts, i.e. Shewhart, CUSUM and EWMA charts in presence of TCME model. This study will help quality practitioners to choose an efficient chart for the monitoring of analytical measurements.     

Monitoring of the surface of paper samples exposed to UV light by ATR-FT-IR spectroscopy and use of multivariate control charts

The effect of exposure of paper samples to UV light was monitored by use of ATR-FT-IR spectroscopy and multivariate statistical tools. Three types of paper were tested: common laser-printer paper, newsprint, and thermal fax paper. The samples were first characterised by ATR-FT-IR spectroscopy to determine natural experimental variability. They were then exposed to UV light for 30 h and the effects of the exposure were monitored by use of the same spectroscopic technique. Finally, multivariate statistical tools were applied to the final dataset, coupled with construction of multivariate control charts, to identify the effects of UV light on the sample surfaces.     

Development of a technique based on multi-spectral imaging for monitoring the conservation of cultural heritage objects

A new approach for monitoring the state of conservation of cultural heritage objects surfaces is being developed. The technique utilizes multi-spectral imaging, multivariate analysis and statistical process control theory for the automatic detection of a possible deterioration process, its localization and identification, and the wavelengths most sensitive to detecting this before the human eye can detect the damage or potential degradation changes occur. A series of virtual degradation analyses were performed on images of parchment in order to test the proposed algorithm in controlled conditions. The spectral image of a Dead Sea Scroll (DSS) parchment, IAA (Israel Antiquities Authority) inventory plate # 279, 4Q501 Apocryphal Lamentations B, taken during the 2008 Pilot of the DSS Digitization Project, was chosen for the simulation.     

Portable Raman monitoring of modern cleaning and consolidation operations of artworks on mineral supports

Any restoration performed on cultural heritage artworks must guarantee a low impact on the treated surfaces. Although completely risk-free methods do not exist, the use of tailor-made procedures and the continuous monitoring by portable instrumentation is surely one of the best approaches to conduct a modern restoration process. In this work, a portable Raman monitoring, combined sometimes with spectroscopic techniques providing the elemental composition, is the key analysis technique in the three-step restoration protocol proposed: (a) in situ analysis of the surface to be treated (original composition and degradation products/pollutants) and the cleaning agents used as extractants, (b) the thermodynamic study of the species involved in the treatment in order to design a suitable restoration method and (c) application and monitoring of the treatment. Two cleaning operations based on new technologies were studied and applied to two artworks on mineral supports: a wall painting affected by nitrate impact, and a black crusted stone (chalk) altarpiece. Raman bands of nitrate and gypsum, respectively, decreased after the step-by-step operations in each case, which helped restorers to decide when the treatment was concluded, thus avoiding any further damage to the treated surface of the artworks.     

Evaluation of statistical control charts for on-line radiation monitoring

Statistical control charts are presented for the evaluation of time series radiation counter data from flow cells used for monitoring of low levels of ⁹⁹TcO₄⁻ in environmental solutions. Control chart methods consisted of the 3-sigma (3σ) chart, the cumulative sum (CUSUM) chart, and the exponentially weighted moving average (EWMA) chart. Each method involves a control limit based on the detector background which constitutes the detection limit. Both the CUSUM and EWMA charts are suitable to detect and estimate sample concentration requiring less solution volume than when using a 3σ control chart. Data presented here indicate that the overall accuracy and precision of the CUSUM method is the best.     

Portable Raman versus portable mid-FTIR reflectance instruments to monitor synthetic treatments used for the conservation of monument surfaces

This study aims to evaluate the relevance of portable Raman and portable mid-Fourier transform infrared (FTIR) reflectance instruments in monitoring the synthetic treatments applied on plaster substrates, a crucial issue in a conservation work. Some polymeric consolidants and protectives have a relatively short life owing to their degradation, and after some years the surface should be retreated. It follows that any information about the presence and composition of the products applied, their chemical transformations and their distribution on the surfaces is essential. For these purposes, conservation scientists should seek and test new in situ methods, and this is of utmost importance especially in the case of buildings, considering their large dimensions and consequent extensive mapping. The effectiveness of portable Raman and portable mid-FTIR reflectance instruments has been compared by analysing a set of laboratory specimens prepared and treated with variable amounts of products belonging to three classes of polymers; the spectroscopic investigation highlighted, for the first time, the limits and the advantages of portable Raman and portable mid-FTIR reflectance instruments in the detection of small amounts of products commonly employed for the conservation of plasters.     

Fermentation diagnosis by multivariate statistical analysis

During the course of fermentation, online measuring procedures able to estimate the performance of the current operation are highly desired. Unfortunately, the poor mechanistic understanding of most biologic systems hampers attempts at direct online evaluation of the bioprocess, which is further complicated by the lack of appropriate online sensors and the long lag time associated with offline assays. Quite often available data lack sufficient detail to be directly used, and after a cursory evaluation are stored away. However, these historic databases of process measurements may still retain some useful information. A multivariate statistical procedure has been applied for analyzing the measurement profiles acquired during the monitoring of several fed-batch fermentations for the production of erythromycin. Multivariate principal component analysis has been used to extract information from the multivariate historic database by projecting the process variables onto a low-dimensional space defined by the principal components. Thus, each fermentation is identified by a temporal profile in the principal component plane. The projections represent monitoring charts, consistent with the concept of statistical process control, which are useful for tracking the progress of each fermentation batch and identifying anomalous behaviors (process diagnosis and fault detection).     

Robustness testing of control charts employed by analytical laboratories

 The robustness of Shewhart control charts for subgroup means and subgroup ranges was tested by using the Monte Carlo method using training data sets comprising various numbers of points, with two repetitions in each subgroup (as in routine laboratory practice). The following control chart designs were tested: conventional based on the arithmetic mean and standard deviation, robust based on the median and/or the trimmed mean and Winsorized standard deviation, and a two-step design. The methods were applied to the system in the state of statistical control (outliers excluded) and to the system without statistical control (outliers included). Satisfactory results for both cases were only obtained when using the two-stage control charts. The conventional charts led to underestimation of the effect of outliers in the system without statistical control, whereas the robust control charts led to overestimation of the effect of outliers (false alarm) in the system under statistical control. The tests also gave evidence that the training set should include 20 points as a minimum. Received: 13 January 1997 Accepted: 12 February 1997     

Unilateral NMR, 13C CPMAS NMR spectroscopy and micro-analytical techniques for studying the materials and state of conservation of an ancient Egyptian wooden sarcophagus

A multi-technique approach was employed to study a decorated Egyptian wooden sarcophagus (XXV–XXVI dynasty, Third Intermediate Period), belonging to the Museo del Vicino Oriente of the Sapienza University of Rome. Portable non-invasive unilateral NMR was applied to evaluate the conservation state of the sarcophagus. Moreover, using unilateral NMR, a non-invasive analytical protocol was established to detect the presence of organic substances on the surface and/or embedded in the wooden matrix. This protocol allowed for an educated sampling campaign aimed at further investigating the state of degradation of the wood and the presence of organic substances by ¹³C cross polarization magic angle spinning (CPMAS) NMR spectroscopy. The composition of the painted layer was analysed by optical microscopy (OM), scanning electron microscopy–energy dispersive spectroscopy (SEM–EDS), Raman and surface enhanced (resonance) Raman spectroscopy (SERS/SERRS), infrared and GC–MS techniques, evidencing original components such as clay minerals, Egyptian green, indigo, natural gums, and also highlighting restoration pigments and alteration compounds. The identification of the wood, of great value for the reconstruction of the history of the artwork, was achieved by means of optical microscopy.     

Qualitative study of ethanol content in tequilas by Raman spectroscopy and principal component analysis

Using Raman spectroscopy, with an excitation radiation source of 514.5 nm, and principal component analysis (PCA) was elaborated a method to study qualitatively the ethanol content in tequila samples. This method is based in the OH region profile (water) of the Raman spectra. Also, this method, using the fluorescence background of the Raman spectra, can be used to distinguish silver tequila from aged tequilas. The first three PCs of the Raman spectra, that provide the 99% of the total variance of the data set, were used for the samples classification. The PCA1 and PCA2 are related with the water (or ethanol) content of the sample, whereas the PCA3 is related with the fluorescence background of the Raman spectra.     

Effect of gold nanoparticle attached multi-walled carbon nanotube-layered indium tin oxide in monitoring the effect of paracetamol on the release of epinephrine

Raman spectroscopy and control charts based on the net analyte signal (NAS) were applied to polymorphic characterization of carbamazepine. Carbamazepine presents four polymorphic forms: I-IV (dihydrate). X-ray powder diffraction was used as a reference technique. The control charts were built generating three charts: the NAS chart that corresponds to the analyte of interest (form III in this case), the interference chart that corresponds to the contribution of other compounds in the sample and the residual chart that corresponds to nonsystematic variations. For each chart, statistical limits were developed using samples within the quality specifications. It was possible to identify the different polymorphic forms of carbamazepine present in pharmaceutical formulations. Thus, an alternative method for the quality monitoring of the carbamazepine polymorphic forms after the crystallization process is presented.     

Construction of stable multivariate calibration models using unsupervised segmented principal component regression

In multivariate spectral calibration by principal component regression (PCR), the principal components (PCs) are calculated from the response data measured at all employed instrument channels; however some channels are redundant and their responses do not possess useful information. Thus, the extracted PCs possess mixed information from both useful and redundant channels. In this work, we propose a segmentation approach based on unsupervised pattern recognition to identify the most informative spectral region and then to construct a stable multivariate calibration model by PCR. In this method, the instrument channels are clustered into different segments via Kohonen self‐organization map. The spectral data of each segment are then subjected to PCA and the derived PCs are used as input variables for an inverse least square (ILS) regression model employing stepwise selection of the informative PCs. The proposed method was evaluated by the analysis of four simulated and six experimental data sets. It was found that our proposed method can model the above data sets with prediction errors lower than conventional partial least squares (PLS) and PCR methods. In addition, the prediction ability of our method was better than the previously reported models for these data sets. Copyright © 2011 John Wiley & Sons, Ltd.     

Multivariate control charts based on NAS and mid‐infrared spectroscopy for quality control of B5 blends of methyl soybean biodiesel in diesel

In this work, mid‐infrared spectroscopy and multivariate control charts based on net analyte signal were applied for quality control of B5 blends of biodiesel/diesel (5% biodiesel/95% diesel). Control charts were constructed using instrumental signal decomposition, generating three charts: the net analyte signal chart for monitoring the analyte of interest (methyl soybean biodiesel); the interference chart, which corresponds to the contribution of all other compounds in the diesel sample (diesel); and the residual chart, which corresponds to non‐systematic variations. Statistical limits were established for each developed chart, using samples inside quality specifications (normal operation conditions). To validate multivariate control charts, new samples were analyzed. The new samples represented samples in‐control and samples out‐of‐control in relation to the content of biodiesel, adulterated biodiesel with severe vegetable oils and adulterated diesel with residual automotive lubricant oil, kerosene, and gasoline. The results obtained show an excellent distinction between the samples inside and out of the quality specifications, with 91% and 100% correctly classified, respectively, which demonstrates that the methodology developed is a viable alternative for quality monitoring of this type of fuel. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of classical versus bayesian statistical control charts to on-line radiological monitoring

False positive and false negative incidence rates of radiological monitoring data from classical and Bayesian statistical process control chart techniques are compared. The on-line monitoring for illicit radioactive material with no false positives or false negatives is the goal of homeland security monitoring, but is unrealistic. However, statistical fluctuations in the detector signal, short detection times, large source to detector distances, and shielding effects make distinguishing between a radiation source and natural background particularly difficult. Experimental time series data were collected using a 1″ × 1″ LaCl₃(Ce) based scintillation detector (Scionix, Orlando, FL) under various simulated conditions. Experimental parameters include radionuclide (gamma-ray) energy, activity, density thickness (source to detector distance and shielding), time, and temperature. All statistical algorithms were developed using MATLAB™. The Shewhart (3-σ) control chart and the cumulative sum (CUSUM) control chart are the classical procedures adopted, while the Bayesian technique is the Shiryayev–Roberts (S–R) control chart. The Shiryayev–Roberts method was the best method for controlling the number of false positive detects, followed by the CUSUM method. However, The Shiryayev–Roberts method, used without modification, resulted in one of the highest false negative incidence rates independent of the signal strength. Modification of The Shiryayev–Roberts statistical analysis method reduced the number of false negatives, but resulted in an increase in the false positive incidence rate.     

Analysis of lignin from archaeological waterlogged wood by direct exposure mass spectrometry (DE-MS) and PCA evaluation of mass spectral data

The chemical characterisation of waterlogged archaeological wood is of fundamental importance to understand the degradation processes undergone by wooden objects and consequently to develop suitable consolidation and conservation procedures. Lignin extracted from archaeological waterlogged wood samples was characterized using direct exposure electron ionisation mass spectrometry (DE-MS). DE-MS achieves a mass spectral fingerprint of the sample in a few minutes, avoiding any chemical pre-treatment and requiring only few micrograms of material.Mass spectral data were put in relation to the chemical composition of lignin and evaluated by means of principal component analysis (PCA). The preliminary results, presented in this study, demonstrate the feasibility and the potential of DE-MS as a reproducible and rapid screening method for archaeological waterlogged wood samples.