APPLICATION OF STATISTICAL PROCESS CONTROL (SPC) IN THE RUBBER INDUSTRY

Statistical Process Control (SPC) is a more powerful tool available toimprove the manufacturing processes, to reduce scrap and rework, andultimately make the production more competitive in terms of productivityand preventing pollution. In this study, variable and range charts are used toevaluate the process of controlling drying tower temperature in the process oflatex crepe rubber production. The charts have upper and lower control limitsand the process is in control if sample measurements are between the controllimits. R chart was used to evaluate the variation of temperature within thedrying tower. In the case of charts for individuals, moving range charts and Xcharts were used in monitoring the process of daily chemical applicationssuch as sodium bisulphate, bleaching agents, and acids. Lack of control isidentified by the points laying outside the control limits on either the X-bar, Xchart, R-bar chart or R charts. Pattern of the time series interprets thevariation of the process. Runs test was applied to check up whether the timeseries is in the expected random order or not. Then Process Capability indexand the Process Performance Indexes were calculated to evaluate thecapability and the precision of the process. Therefore in the competitiveenvironment, statistical process control is a 'must' for achieving sustainabledevelopment in the rubber industry with high efficiency and effectiveness

Multivariate process variability monitoring for high dimensional data

In today’s competitive market, the quality of a product or service is no longer measured by a single variable but by a number of variables that define the quality of the final product or service. It is known that these quality variables of products or services are correlated with each other, and it is therefore important to monitor these correlated quality characteristics simultaneously. Multivariate quality control charts are capable of such monitoring. Multivariate monitoring of industrial or clinical procedures often involves more than three correlated quality characteristics, and the status of the process is judged using a sample of one size. The majority of existing control charts for monitoring multivariate process variability for individual observations are capable of monitoring up to three quality characteristics. One of the hurdles in designing optimal variability control charts for large dimension data is the enormous computing resources and time that is required by the simulation algorithm to estimate the charts parameters. In this research, a novel algorithm based on the parallelised Monte Carlo simulation has been developed to improve the ability of the Multivariate Exponentially Weighted Mean Squared Deviation (MEWMS) and Multivariate Exponentially Weighted Moving Variance (MEWMV) charts to monitor multivariate process variability with a greater number of quality characteristics. Different techniques have been deployed to reduce computing space and the time complexity taken by the algorithm. The novelty of this algorithm is its ability to estimate the optimal control limit L (optimal L) for any given number of correlated quality characteristics, size of the shifts to be detected based on the smoothing constant, and the given in-control average run length in a computationally efficient way. The optimal L for the MEWMS and MEWMV charts to detect small, medium and large shifts in the covariance matrix of up to fifteen correlated quality characteristics has been provided. Furthermore, utilising the large number of optimal L values generated by the algorithm has enabled us to develop two mathematical functions that are capable of predicting L values for MEWMS and MEWMV charts. This would eliminate the need for further execution of the parallelised Monte Carlo simulation for high dimension data. One of the main challenges in deploying multivariate control charts is to identify which characteristics are responsible for the out-of-control signal detected by the charts, and what is the extent of their contribution to the signal. In this research, a smart diagnostic technique has been developed by using a hybrid of the wrapper filter approach to effectively identify the variables that are responsible for the process faults and to classify the percentage of their contribution to the faults. The robustness of the proposed techniques has been demonstrated through their application to a range of clinical and industrial multivariate processes where the percentage of correct classifications is presented for different scenarios. The majority of the existing multivariate control charts have been developed to monitor processes that follow multivariate normal distribution. In this thesis, the author has proposed a control chart for a non-normal high dimensional multivariate process based on the percentile point of Burr XII distribution. Geometric distance variables are fitted to the subset of correlated quality characteristics to reduce the dimension of the data, which is then followed by fitting the Burr XII distribution to each geometric distance variable. Since individual distance variables are independent, each can be monitored by individual control charts based on the percentile points of the fitted Burr XII distributions. A simulated annealing approach is used to estimate parameters of the Burr XII distribution. The proposed hybrid is utilised to identify and rank the variables responsible for the out-of-control signals of geometric distance variables

Machine learning classification of human joint tissue from diffuse reflectance spectroscopy data

Objective: To assess if incorporation of DRS sensing into real-time robotic surgery systems has merit. DRS as a technology is relatively simple, cost-effective and provides a non-contact approach to tissue differentiation. Methods: Supervised machine learning analysis of diffuse reflectance spectra was performed to classify human joint tissue that was collected from surgical procedures. Results: We have used supervised machine learning in the classification of a DRS human joint tissue data set and achieved classification accuracy in excess of 99%. Sensitivity for the various classes were; cartilage 99.7%, subchondral 99.2%, meniscus 100% and cancellous 100%. Full wavelength range is required for maximum classification accuracy. The wavelength resolution must be larger than 8nm. A SNR better than 10:1 was required to achieve a classification accuracy greater than 50%. The 800-900nm wavelength range gave the greatest accuracy amongst those investigated. Conclusion: DRS is a viable method for differentiating human joint tissue and has the potential to be incorporated into robotic orthopaedic surgery

Predicting the optimal rotation length of Teak plantations using a simulation model

The traditional problem in Forest Economics has been mainly dealt with the estimation of optimalrotation length for sustainable management. However, given the limitation of the availability of timeseries data on growth and management in forest plantations in Sri Lanka, such estimations are notfeasible. Against this background, this study attempted to develop a simulation model and predictrotational interval of teak plantation under different management conditions.A field survey was conducted to identify the plantation related parameters in the Kurunegala District.Meantime, a simulation model was developed with Microsoft Visual Basic and Microsoft Excel usingthe equations specified in the Teak Management Plan (1997) to supplement the field data. The pastdata obtained from the Forest Department was used to parameterize the model. Using the age andthe height of a plantation at a particular time, the model was capable of predicting the plantationrelated parameters such as dbh and timber volume over the time.According to the values predicted by the simulation model, four different categories were identifiedbased on the site index, which represents the level of growth of a stand. Rotational interval wasestimated using the Faustman rotational model at different discount rates. Thereby it was estimatedthat the rotational intervals for the four categories at discount rates 10%, 15% and 20% as 19, 17 and15 years respectively. The internal rate of return obtained through the simulation was above themarket rate of 12%. Though the model yielded shorter rotational intervals than the present fieldvalues, the approach could be used in future with more reliable field data.

Physiological responses to basic tastes for sensory evaluation of chocolate using biometric techniques

Facial expressions are in reaction to basic tastes by the response to receptor stimulation. The objective of this study was to assess the autonomic nervous system responses to basic tastes in chocolates and to identify relationships between conscious and unconscious responses from participants. Panelists (n = 45) tasted five chocolates with either salt, citric acid, sugar, or monosodium glutamate, which generated four distinctive basic tastes plus bitter, using dark chocolate. An integrated camera system, coupled with the Bio-Sensory application, was used to capture infrared thermal images, videos, and sensory responses. Outputs were used to assess skin temperature (ST), facial expressions, and heart rate (HR) as physiological responses. Sensory responses and emotions elicited during the chocolate tasting were evaluated using the application. Results showed that the most liked was sweet chocolate (9.01), while the least liked was salty chocolate (3.61). There were significant differences for overall liking (p < 0.05) but none for HR (p = 0.75) and ST (p = 0.27). Sweet chocolate was inversely associated with angry, and salty chocolate positively associated with sad. Positive emotion-terms were associated with sweet samples and liking in self-reported responses. Findings of this study may be used to assess novel tastes of chocolate in the industry based on conscious and emotional responses more objectively

Struggling to a monumental triumph : Re-assessing the final stages of the smallpox eradication program in India, 1960-1980

The global smallpox program is generally presented as the brainchild of a handful of actors from the WHO headquarters in Geneva and at the agency's regional offices. This article attempts to present a more complex description of the drive to eradicate smallpox. Based on the example of India, a major focus of the campaign, it is argued that historians and public health officials should recognize the varying roles played by a much wider range of participants. Highlighting the significance of both Indian and international field officials, the author shows how bureaucrats and politicians at different levels of administration and society managed to strengthen—yet sometimes weaken—important program components. Centrally dictated strategies developed at WHO offices in Geneva and New Delhi, often in association with Indian federal authorities, were reinterpreted by many actors and sometimes changed beyond recognition

Water Quality in Selected Locations of the Kalu Ganga

Out of the 103 rivers in the country Kalu Ganga is one of the main rivers in Sri Lanka with a length of 129km and a drainage area of 2720 km2. It has the highest discharge volume with a mean annual discharge volume to sea totaling to 8183 mcm.  Kalu Ganga originates from the central hills of mountain Sri Pada situated 2100 m above sea level and falls to the sea in Kalutara.The purpose of this research is to analyze the current water quality situation of the Kalu Ganga River and its suitability for  human consumption purposes (by comparing with the CEA and SLS standards). It is also the purpose of this research to locate the areas where the river is exposed to massive degradation in water quality and identify the main sources of pollution in those areas.The research study was conducted in the middle and lower reaches of the Kalu Ganga basin. The study was conducted in two phases, the feasibility phase and the detail phase. The water quality of the river was tested using physical, chemical and biological parameters. The water samples from the relevant sampling points were obtained and analyzed in the period between February 2012 and August 2012. For the feasibility study, 13 sampling locations were selected along the main river and at locations where certain tributaries fall to the main river. The sampling points were in a stretch from Ratnapura to Kalutara with approximate distance of about 6-8 km from each sampling point to another. The sampling points for the feasibility study was selected based on  criteria such as regional population, land use pattern along the river basin, water intake points of the NWS&amp;DB and previous studies. The parameters tested in the feasibility study were temperature, turbidity, TDS, E. Conductivity, pH, Chloride, Floride, Nitrate, Nitrite, Sulphate, Total Iron, Total Phosphate, Total hardness, Alkalinity, Heavy Metals, COD, BOD, DO, Total coli form and  E.coli.  The detail study was conducted based on the results of the feasibility study.Based on the results obtained the temperature of the river had an average value of 24̊   C and the pH values were within the range allowed in the CEA standard in most of the locations. The DO levels of the water was greater than the standard values while the BOD values in the river was lower than the standard value prescribed by the CEA standards. The COD values were comparatively higher in the river outfall (46.2mg/l) and in the Nathupana bridge (14.4mg/l) due to the industries located in the surrounding area, but the values were within the standard prescribed by the CEA. The river was not polluted much with the presence of heavy metals. The total coliform count was well below the standard level, while the fecal coliform count was above the standard level especially during the high flow period mainly in sampling points near tributaries. Based on the results obtained from the feasibility study it was decided to concentrate the detail study in the lower reaches of the middle basin and the lower basin of the main river. The sampling points were  located in areas from Horana to Kalutara. When selecting sampling points major effluent discharging industries in the river basin were selected as additional sampling points, to identify the affect of the final effluent on the water quality of the river. In total 11 sampling points were selected for the detail study. In the detail study certain parameters tested in the feasibility study was excluded due to tested results being lower than the minimum allowable levels in the standards. New parameters were included in the detail study based on the industries selected. The newly included parameters were free ammonia, color, sulphides, TOC, oil and grease, surfactants, phenolitic compounds and PAH.Keywords: Water quality, BOD, COD, industry effluent

Water balance and renewal time of rekawa lagoon, Sri Lanka; a restorative approach

Rekawa Lagoon is a chocked and shallow coastal water body located in the southern coast of Sri Lanka. It is relatively unusual in that the major freshwater input, Kirama-oya river connects through the constricted channel much closer to the inlet at seaward end. A causeway was constructed, around 700 m from the lagoon inlet to the inland, across the constricted channel with an effort to link a secluded Kapuhenwala village with the rest of the area which in turn greatly reduced the volume and speed of water entering and leaving the lagoon system. Construction of the causeway led to many environmental problems with poor flushing efficiency and hampering to and fro movement of the prawns in the lagoon. The aim of this study was to evaluate the present situation and propose alternative management scenarios for improvement of water flow and lagoon ecosystem. The implications of different development stages of the causeway were discussed in terms of field measurements supported by modeling to describe the water balance and the water renewal time. The alternative of modifying the existing causeway was proposed to increase the free water flow at the inlet that favors recruitment of juvenile shrimp species

Influence of Fluorination on the Solubilities of Carbon Dioxide, Ethane, and Nitrogen in 1‑n‑Fluoro-alkyl-3-methylimidazolium Bis(n‑fluoroalkylsulfonyl)amide Ionic Liquids

International audienceThe effect on gas solubilities of adding partially fluorinated alkyl side chains either on imidazolium-based cations or on bis(perfluoroalkylsulfonyl)amide anions was studied. The aim was to gain knowledge of the mechanisms of dissolution of gases in fluorinated ionic liquids and, if possible, to improve physical absorption of carbon dioxide in ionic liquids. We have determined experimentally, in the temperature range of 298–343 K and at pressures close to atmospheric pressure, the solubility and thermodynamics of solvation of carbon dioxide, ethane, and nitrogen in the ionic liquids 1-octyl-3-methylimidazolium bis[trifluoromethylsulfonyl]amide ([C8mim][NTf2]), 1-octyl-3-methylimidazolium bis[pentafluoroethylsulfonyl]amide ([C8mim][BETI]), 1-(3,3,4,4,5,5,6,6,7,7,8,8,8-tridecafluorooctyl)-3-methylimidazolium bis[trifluoromethylsulfonyl]amide ([C8H4F13mim][NTf2]), and 1-(3,3,4,4,5,5,6,6,7,7,8,8,8-tridecafluorooctyl)-3-methylimidazolium bis[pentafluoroethylsulfonyl]amide ([C8H4F13mim][BETI]). Ionic liquids with partial fluorination on the cation were found to exhibit higher carbon dioxide and nitrogen mole fraction solubilities but lower ethane solubilities, compared to those of their hydrogenated counterparts. Molecular simulation provided insights about the mechanisms of solvation of the different gases in the ionic liquids