Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach

The business performance of manufacturing organizations depends on the reliability and productivity of equipment, machineries and entire manufacturing system. Therefore, the main role of maintenance and production managers is to keep manufacturing system always up by adopting most appropriate maintenance methods. There are alternative maintenance techniques for each machine, the selection of which depend on multiple factors. The contemporary approaches to maintenance technique selection emphasize on operational needs and economic factors only. As the reliability of production systems is the strategic intent of manufacturing organizations, maintenance technique selection must consider strategic factors of the concerned organization along with operational and economic criteria. The main aim of this research is to develop a method for selecting the most appropriate maintenance technique for manufacturing industry with the consideration of strategic, planning and operational criteria through involvement of relevant stakeholders. The proposed method combines quality function deployment (QFD), the analytic hierarchy process (AHP) and the benefit of doubt (BoD) approach. QFD links strategic intents of the organizations with the planning and operational needs, the AHP helps in prioritizing the criteria for selection and ranking the alternative maintenance techniques, and the BoD approach facilitates analysing robustness of the method through sensitivity analysis through setting the realistic limits for decision making. The proposed method has been applied to maintenance technique selection problems of three productive systems of a gear manufacturing organization in India to demonstrate its effectiveness

Some Spatial and Transform Domain Image Resolution Enhancement Algorithms – A Comparative Study

Image resolution enhancement algorithms, in spatial domain (viz., bicubic, data dependent triangulation and edge directed interpolation) and transform domain (viz., wavelet and DCT) were implemented and their performances were compared. It was concluded that discrete cosine transform (DCT) based image resolution enhancement algorithm performs better than the other methods. DCT based image resolution enhancement algorithm is very simple to implement and has the additional advantage of being able to produce high resolution images whose size need not necessarily be a multiple of two. DCT based video resolution enhancement algorithm was implemented and tested its performance in Simulink. It was concluded that this algorithm would be very suitable for video resolution enhancement

A review of tangible benefits of TPM implementation

Abstract: This short review paper aims to study the tangible benefits of Total Productive Maintenance (TPM) in the manufacturing industry. In this short review, an attempt was made to critically discuss the previous literature related to the TPM. The review was done based on a range of journals related to TPM, published from 1988 up to 2013. A total of 33 papers were studied, specifically related to TPM. The review process starts by studying the TPM papers and identifying the tangible benefits of TPM. Overall Equipment Effectiveness (OEE) improvement is one of the main benefits in TPM implementation and has been discussed in most of the literature. However, TPM implementation methodology is suggested for improvement in the availability, performance efficiency and the quality rate, results in improvement of the overall equipment effectiveness of the equipment. This literature review-based research highlighted a TPM will improve the OEE. Based on this short review, it is suggested that more benefits are addressed by future research related to TPM, in order to solidify its philosophy towards a more realistic practical applications

Transcriptome profiling of rice roots in early response to Bacillus subtilis (RR4) colonization

Bacillus subtilis, a gram-positive soil bacterium, is widely used as a plant growth-promoting agent. However, how Bacillus initially colonizes the rice roots evading the plant primary defense mechanisms and how it influences root secretion of phytochemicals for further colonization remain obscure. To get an insight into how a plant perceives the bacterium upon initial root colonization, a microarray analysis was performed using rice roots treated with a rice rhizosphere isolate, B. subtilis RR4. About 891 transcripts (255 up-regulated and 636 down-regulated) were differentially expressed indicating that the bacteria reprogram the plant for its colonization. RR4 mainly caused the suppression of transcripts encoding defense response enzymes like chitinase, cell wall-modifying enzymes like pectinesterase, and genes associated with transport/exudation of phytochemicals signifying that the bacteria modulate the gene expression of the plant to facilitate its colonization. Genes that regulate secondary metabolite production were up-regulated. Although the defense response genes in rice roots were suppressed initially, they were induced gradually at four and ten days post-treatment. This was accompanied by an increased level of salicylic acid in the colonized rice roots. Thus, our results show that B. subtilis alters the transcriptome of rice roots for initial colonization by lowering plant self-defense, limiting root exudation and active cell growth, while boosting the plant defense in the later stage.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Infant Screening System Based on Cry Analysis

Acoustical investigation of infant cries has been a clinical and research focus in the recent years. Findings of several studies reveal the importance of cry as a useful window for early detection of several diseases and communication difficulties such as hearing impairment, intellectual disabilities, cerebral palsy etc. This motivates us to use a minimal interface system that can automatically classify infant cries into normal and pathological with the help of state-of-the-art machine learning strategies. In this paper, we propose a software program for screening infants based on their cries. The proposed system is able to detect & classify infant cries into normal and pathological based on the acoustic input. To build and train the system, infant cries of normal and Low Birth Weight (LBW) newborn within 7 days of birth were considered. A pain induced cry elicited using the routine intramuscular immunization was recorded using a standard Olympus LS-100 recorder which was held about 10 centimetres away from the infant’s mouth. The acoustic correlates of these cries were used to build the software tool. Artificial Neural Network was employed to improve its functionality. Therefore, we propose a screening tool for further accessibility and large-scale implementation