905 resultados para Handicap Inventory
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Inventory management (IM) has a decisive role in the enhancement of manufacturing industry's competitiveness. Therefore, major manufacturing industries are following IM practices with the intention of improving their performance. However, the effort to introduce IM in SMEs is very limited due to lack of initiation, expertise, and financial constraints. This paper aims to provide a guideline for entrepreneurs in enhancing their IM performance, as it presents the results of a survey based study carried out for machine tool Small and Medium Enterprises (SMEs) in Bangalore. Having established the significance of inventory as an input, we probed the relationship between IM performance and economic performance of these SMEs. To the extent possible all the factors of production and performance indicators were deliberately considered in pure economic terms. All economic performance indicators adopted seem to have a positive and significant association with IM performance in SMEs. On the whole, we found that SMEs which are IM efficient are likely to perform better on the economic front also and experience higher returns to scale.
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We present a generic study of inventory costs in a factory stockroom that supplies component parts to an assembly line. Specifically, we are concerned with the increase in component inventories due to uncertainty in supplier lead-times, and the fact that several different components must be present before assembly can begin. It is assumed that the suppliers of the various components are independent, that the suppliers' operations are in statistical equilibrium, and that the same amount of each type of component is demanded by the assembly line each time a new assembly cycle is scheduled to begin. We use, as a measure of inventory cost, the expected time for which an order of components must be held in the stockroom from the time it is delivered until the time it is consumed by the assembly line. Our work reveals the effects of supplier lead-time variability, the number of different types of components, and their desired service levels, on the inventory cost. In addition, under the assumptions that inventory holding costs and the cost of delaying assembly are linear in time, we study optimal ordering policies and present an interesting characterization that is independent of the supplier lead-time distributions.
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In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.
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Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.
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This dissertation develops a strategic management accounting perspective of inventory routing. The thesis studies the drivers of cost efficiency gains by identifying the role of the underlying cost structure, demand, information sharing, forecasting accuracy, service levels, vehicle fleet, planning horizon and other strategic factors as well as the interaction effects among these factors with respect to performance outcomes. The task is to enhance the knowledge of the strategic situations that favor the implementation of inventory routing systems, understanding cause-and-effect relationships, linkages and gaining a holistic view of the value proposition of inventory routing. The thesis applies an exploratory case study design, which is based on normative quantitative empirical research using optimization, simulation and factor analysis. Data and results are drawn from a real world application to cash supply chains. The first research paper shows that performance gains require a common cost component and cannot be explained by simple linear or affine cost structures. Inventory management and distribution decisions become separable in the absence of a set-dependent cost structure, and neither economies of scope nor coordination problems are present in this case. The second research paper analyzes whether information sharing improves the overall forecasting accuracy. Analysis suggests that the potential for information sharing is limited to coordination of replenishments and that central information do not yield more accurate forecasts based on joint forecasting. The third research paper develops a novel formulation of the stochastic inventory routing model that accounts for minimal service levels and forecasting accuracy. The developed model allows studying the interaction of minimal service levels and forecasting accuracy with the underlying cost structure in inventory routing. Interestingly, results show that the factors minimal service level and forecasting accuracy are not statistically significant, and subsequently not relevant for the strategic decision problem to introduce inventory routing, or in other words, to effectively internalize inventory management and distribution decisions at the supplier. Consequently the main contribution of this thesis is the result that cost benefits of inventory routing are derived from the joint decision model that accounts for the underlying set-dependent cost structure rather than the level of information sharing. This result suggests that the value of information sharing of demand and inventory data is likely to be overstated in prior literature. In other words, cost benefits of inventory routing are primarily determined by the cost structure (i.e. level of fixed costs and transportation costs) rather than the level of information sharing, joint forecasting, forecasting accuracy or service levels.
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Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.
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This article reports the greenhouse gas emissions of anthropogenic origin by sources and removals by sinks of India for 2007 prepared under the aegis of the Indian Network for Climate Change Assessment (INCCA) (note 1). The emission profile includes carbon dioxide (CO(2)), methane and nitrous oxide. It also includes the estimates of hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride at the national level from various sectors, viz, energy, industrial process and product use, agriculture, land-use, land-use change and forestry (LULUCF), and waste. In 2007, emissions were of the order of 2008.67 Tg (note 2) of CO(2) equivalents without emissions from the LULUCF sector. Whereas with LULUCF the emissions were about 1831.65 Tg CO(2) equivalents. The energy sector accounted for 69% of the total emissions, the agriculture sector contributed 19% of the emissions, 9% of the emissions was from the industrial processes and product use, and only 3% of the emissions was attributable to the waste sector. The LULUCF sector on the whole was net sink category for CO(2). The study tracks the improvements made in inventory estimates at the national level through the years, in terms of the expanding coverage of sources, reducing uncertainties and inclusion of new methodologies, including some elements of future areas of work.
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Ethnopharmacological relevance: Traditional remedies used for treating diabetic ailments are very important in the primary health care of the people living in rural Dhemaji district of Assam, north-east India. Novel information gathered from the current survey is important in preserving folk indigenous knowledge. Materials and methods: Interviews were conducted amongst 80 households comprising of 240 individuals using semi-structured questionnaires. The focus was on plants used in treating diabetes mellitus. Results: The current survey documented 21 plant species (20 families) which are reportedly used to treat diabetes mellitus by the rural people in the study area. To the best of our knowledge, Amomum linguiforme, Cinnamomum impressinervium, Colocasia esculenta, Dillenia indica, Euphorbia ligularia, Garcinia pedunculata, Solanum indicum, Sterculia villosa and Tabernaemontana divaricata are recorded for the first time based on globally published literature as medicinal plants used for treating diabetes mellitus and related symptoms. Conclusions: The wide variety of plants that are used to treat diabetes mellitus in this area supports the traditional value that medicinal plants have in the primary health care system of the rural people of Dhemaji district of Assam. The finding of new plant uses in the current study reveals the importance of the documentation of such ethnobotanical knowledge. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
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One of the causes of lower artesian pressure, water waste and aquifer contamination is the misuse and insufficient care of artesian wells. In 1953, Senate Bill No. 57, entitled "An Act to Protect and Control the Artesian Waters of the State" (see Appendix) became a law. This law was passed through the efforts exerted by leading members of the Senate and the House of Representatives, who understood the need for a wise and controlled expenditure of our most valuable natural resource. The State Geologist and his authorized representatives were designated by this law to enforce this conservation measure; however, no financial provision was included for the 1953-55 biennium. The proposed program of the Florida Geological Survey for this biennium did not include the funds nor provide any full-time personnel for the enforcement of this statute. As a result, little actual work was accomplished during these two years, although much time was given to planning and discussion of the problem. Realizing that this program could provide additional basic data needed in the analysis of the water-supply problem, the State Geologist sought and was granted by the 1955 Legislature adequate funds with which to activate the first phase of the enforcement of Florida Statute No. 370.051-054. Enumerated below is a summary of the progress made on this investigation as outlined previously: 1. Data have been collected on 967 wildly flowing wells in 22 counties. 2. Chloride determinations have been run on 850 of the 967 wells. 3. Of the 967 wells, 554 have chlorides in excess of the 250 ppm, the upper limit assigned by the State Board of Health for public consumption. 4. Water escapes at the rate of 37, 762 gallons per minute from these 967 wells. This amounts to 54, 377, 280 gallons per day. The investigation is incomplete at this time; therefore, no final conclusions can be reached. However, from data already collected, the following recommendations are proposed: 1. That the present inventory of wildly flowing wells be completed for the entire State. 2. That the current inventory of wildly flowing wells be expanded at the conclusion of the present inventory to include all flowing wells. 3. That a complete statewide inventory program be established and conducted in cooperation with the Ground Water Branchof the U.S. Geological Survey. 4. That the enforcement functions as set down in Sections 370.051/.054, Florida Statutes, be separated from the program to collect water-resource data and that these functions be given to the Water Resources Department, if such is created (to be recommended by the Water Resources Study Commission in a water policy law presented to the 1957 Legislature). 5. That the research phase (well inventory) of the program remain under the direction of the Florida Geological Survey. (PDF contains 204 pages.)