Framework for sustainability performance assessment for manufacturing processes- A Review

Manufacturing industries are facing tough competition due to increasing raw material cost and depleting natural resources. There is great pressure on the industry to produce environmental friendly products using environmental friendly processes. To address these issues modern manufacturing industries are focusing on sustainable manufacturing. To develop more sustainable societies, industries need to better understand how to respond to environmental, economic and social challenges. This paper proposed some framework and tools that accelerate the transition towards a sustainable system. The developed framework will be beneficial for sustainability assessment comparing different plans alongside material properties, ultimately helping the manufacturing industries to reduce the carbon emissions and material waste, besides improving energy efficiency. It is expected that this would be highly beneficial for determination of environmental impact of a process at early design stages. Therefore, it would greatly help the manufacturing industries for selection of process plan based on sustainable indices. Overall objective of this paper would have good impact on reducing air emissions and protecting environment. We expect this work to contribute to the development of a standard reference methodology to help further sustainability in the manufacturing sector

Sustainable manufacturing modelling : a case for milling process

In manufacturing industries, metal machining is very important process due to the competitiveness. Every manufacturer needs quick, effective and optimized processes. The experience of the operator plays a major role, but even for a skilled operator it is very difficult to attain the optimum values each time. Sustainability Analysis has attracted growing interests from industry, as an optimum cost estimation system analysis method, and energy consumption progress has been achieved. In this work, scrap production as well as production lead time have to be reduced and machining cost per kg of material is target. To reduce the cost, energy consumption and material wastage impact of the milling process worldwide many aspects of the process are investigated. In the present work, a system has been proposed, which can be used to determine various components of Sustainability analysis of milling process

Design Simulation and Perfomance Analysis of Efficient Low Energy Adaptive Clustering Hierarchy Protocol in Wireless Sensor Network

Network life has been defined by the use of nodes to store, process and distribute information, which have restricted energy usage. In other words, all aspects of the node must be designed for extremely energy-efficient applications from sensor module to hardware and protocol. Diminished energy consumption by a factor of two will increase the system's overall utility by doubling the device life. In addition, the protocols should be robust against node failures, tolerant of defects and scalable to optimise device life to minimise energy dissipation. LEACH is the first protocol for network networks that utilises hierarchical routing to enhance network life. All nodes in a network are grouped into local cluster groups, with the cluster head being one node. Although all non-cluster head nodes transmit their data to the cluster head, the cluster head node collects data from all the cluster members, conducts data signal processing (e.g. , data aggregation) functions and transmits data to the remote baseline. As a cluster-head node, it thus takes much more resources than a non-cluster-head node. So all nodes that belong to the cluster lose communication power if a cluster-head node dies. In this research, we introduced clustering as a means of overcoming this energy efficiency problem. Detailed description on the process of LEACH protocols is available. The information on the simulation and the findings have also been discussed

OUTCOMES OF CIRCUMFERENTIAL V/S ANTERIOR TUCKING TYMPANOPLASTY TECHNIQUE IN INACTIVE MUCOSAL CHRONIC OTITIS MEDIA WITH SUBTOTAL PERFORATIONS: A PROSPECTIVE OBSERVATIONAL STUDY

Objective: The objective of the study is to compare circumferential versus anterior tucking underlay tympanoplasty technique. Methods: In this prospective observational study, 100 patients with chronic otitis media (Inactive mucosal type) were included, who were randomly allocated in two groups; Group I which comprised of 50 patients in which tympanoplasty with anterior tucking was done, and Group II comprised of 50 patients in which circumferential flap tympanoplasty was done. Improvement in the hearing gain and graft uptake success rate was compared. Results: The mean air-bone gap (ABG) changed from 28.74 dB to 11.52 dB after anterior tucking with a mean change of 17.22 dB and this change was found to be statistically significant (p<0.001). Similarly, the mean ABG changed from 28.92 dB to 11.86 dB after a circumferential flap with a mean change of 17.06 dB and this change was also found to be statistically significant (p<0.001). There was a slightly better improvement (17.22 dB) in the anterior tucking group as compared to the circumferential flap (17.06 dB). This difference was, however, not found to be statistically significant (p=0.830). Three-month graft uptake rate in the anterior tucking group was found 92% and in the circumferential group was 94%. (p>0.05). Conclusions: Our study concluded that both techniques have almost the same results with good graft uptake. Results of hearing improvements in both techniques were also comparable

Design Analysis and Implementation of Stock Market Forecasting System using Improved Soft Computing Technique

In this paper, a stock market prediction model was created utilizing artificial neural networks. Many people nowadays are attempting to predict future trends in bonds, currencies, equities, and stock markets. It is quite challenging for a capitalist and an industry to forecast changes in stock market prices. Due to the numerous economic, political, and psychological aspects at play, forecasting future value changes on the stock markets is quite challenging. In addition, stock market forecasting is a difficult endeavor because it relies on a wide range of known and unknown variables. Many approaches, including technical analysis, fundamental analysis, time series analysis, and statistical analysis are used to attempt to predict the share price; however, none of these methods has been demonstrated to be a consistently effective prediction tool. Artificial neural networks (ANNs), a subfield of artificial intelligence, are one of the most modern and promising methods for resolving financial issues, such as categorizing corporate bonds and anticipating stock market indexes and bankruptcy (AI). Artificial neural networks (ANN) are a prominent technology used to forecast the future of the stock market. In order to understand financial time series, it is often essential to extract relevant information from enormous data sets using artificial neural networks. An outcome prediction neural network with three layers is trained using the back propagation method. Analysis shows that ANN outperforms every other prediction technique now available to academics in terms of stock market price predictions. It is concluded that ANN is a useful technique for predicting stock market movements globally

Genetic Variability in Sorghum Exotic Accessions for Nutritional Attributes and Methane Emission Potential

Sorghum an important fodder crop grown for multiple uses as fodder, food and fuel constitute major chunk of forage produced in India. Over the past years Indian farmer’s preference to dual purpose sorghum has changed. Introduction of dual-purpose sorghum varieties to sustain rural development, enhance renewable energy production and improve food security has been stressed Genetic variability of sorghum may be exploited to bred dual purpose hybrids/varieties for higher fodder yield without compromising grain yield.Substantial variations in the fodder value of sorghum stovers have been reported that supports the concept of genetic enhancement to improve dual-purpose sorghum cultivars. Under the present study exotic accessions of sorghum were evaluated for their genetic variability in nutritive value and methane production potential

Production and Reproductive Performance of Bhadawari Buffaloes in Uttar Pradesh, India

Bhadawari is one of the recognized buffalo breeds of India and is famous for high fat content in their milk. Data on production and reproductive traits were collected under Network Project on Bhadawari buffaloes, at Indian Grassland and Fodder Research Institute, Jhansi, Uttar Pradesh, India. The overall least squares means (±SE) for peak yield, days to attain peak yield, lactation milk yield, lactation length, 305 days milk yield, milk yield per day of lactation, service period, calving interval and dry period were 6.96±0.10 kg, 52.8±4.1 days, 1250.5±24.6 kg, 291.4±4.9 days, 1213.5±21.6 kg, 4.30±0.06 kg, 172.4±7.7 days, 522.1±12.1 days and 241.80±11.3 days, respectively. Period of calving had a significant (p<0.05) to highly significant (p<0.01) effect on all the traits studied except service period and dry period, where it was not significant. Season of calving had a significant (p<0.05) effect or lactation length and highly significant (p<0.01) effect on lactation milk yield, 305 days milk yield and all the reproductive traits under study. The lowest calving interval, service period and dry period were observed in rainy season calvers and they differed significantly (p<0.01) with winter and summer calvers. Parity had a significant effect (p<0.05) on lactation milk yield, 305 days milk yield and milk yield per day of lactation. Pair-wise comparison revealed that lactation milk yield was highest in the 2nd lactation followed by 3rd and 4th lactation. Large coefficient of variation observed for different traits under study indicates that there is enough scope for improvement in the production and reproduction traits. Better breeding management and selection for increased performance is needed for genetic improvement of these traits

Advanced strategies for optimization of primary nutrients requirement in rice-A review

The Green Revolution led to India's food independence mostly through the inclusion of supply-driven technologies, such as the introduction of high-yielding cultivars, improved access to water, agrochemicals, and mechanization. The present and future needs target agricultural sustainability without endangering the ecosystem. In this regard, the adoption of precision agriculture is required to meet this expected objective. In developed nations, precision farming has already experienced tremendous growth. However, precision farming methods have taken a while for emerging nations in Asia to comprehend, create, and embrace. Moreover, precision farming is frequently misunderstood as a sophisticated technological intervention intended for extensive agricultural fields. However, it is essentially a science that involves using the "right input" in the "right quantity," at the "right time," and in the "right place," to improve input use efficiency. In the case of primary nutrients such as nitrogen, phosphorus, and potassium, so-called recommendations for nutrient management based on soil tests have improved food grain output which increased the nutrient use efficiency up to a certain extent. Moreover, the recommendations are made for a given agroclimatic region and crops irrespective of site-specific soil fertility, cultivars, and agronomic management levels resulting in excess or scanty use to crop needs. At this juncture, assessing the nutritional requirements of plants proves to be a superior method, as it takes into account the cumulative impact of nutrient availability from various sources on plant growth at any specific stage, making it a reliable indicator of nutrient accessibility. Rice, the most important food crop, is grown in diverse agroclimatic regions at different management levels. Hence, there is an urgent need to adopt a precision nutrient management strategy to optimize the yield output. The article offers an overview of several precision instruments available for managing nutrients at specific sites and aids in choosing the most appropriate one for each circumstance

Buffalo Rearing System in Bhadawari Breeding Tract

Bhadawari buffalo is one of the recognized buffalo breeds in India, known for high milk fat content, which may go as high as 14% (Kushwaha et al., 2012). Zachariah (1941) had first described this breed as “Bhadawan” buffalo – the best breed of buffaloes in Uttar Pradesh and found in the districts of Agra and Etah (Central India). Presently Bhadawari Buffaloes are found in the ravines of Yamuna and Chambal rivers spread over in the states of Uttar Pradesh and Madhya Pradesh. These buffaloes have adapted to the harsh conditions of the ravines with undulating topography, thorny and scanty bushes, climatic stress and draught conditions. The buffaloes are of medium size with medium to low milk yield having high fat content. Animals are of copper color, have two white rings on the lower side of the neck and legs are comparatively shorter. Indiscriminate crossbreeding with Murrah buffaloes, for increasing milk production, during the last 3-4 decades has reduced the number of Bhadawari buffaloes in the region. Looking into the need to conserve this gene pool, Indian Council of Agricultural Research has initiated efforts on conservation and improvement of Bhadawari buffaloes at Indian Grassland and Fodder Research Institute, Jhansi (IGFRI) under Network program in the year 2001. The present study was conducted to collect the information regarding existing buffalo rearing practices adopted by the farmers in the Bhadawari breeding tract