7 resultados para Desktop manufacturing

em University of Connecticut - USA


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Through the correct implementation of lean manufacturing methods, a company can greatly improve their business. Over a period of three months at TTM Technologies, I utilized my knowledge to fix existing problems ans streamline production. In addition, other trouble areas in their production process were discovered and proper lean methods were used to address them. TTM Technologies saw many changed in the right direction over this time period.

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This paper investigates the trends in inventory management in the automobile manufacturing industry during recessionary vs. non-recessionary periods. It is an empirical approach to testing the validity of the hypothesis that firms which carry leaner inventories perform better throughout the business cycle and are less affected by variability in the economy than less lean firms. The research also hopes to shed some light on how firm's financial statements can be manipulated through discretionary adjustments made by management pertaining to the valuation of inventories.

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We measure the capacity output of a firm as the maximum amount producible by a firm given a specific quantity of the quasi-fixed input and an overall expenditure constraint for its choice of variable inputs. We compute this indirect capacity utilization measure for the total manufacturing sector in the US as well as for a number of disaggregated industries, for the period 1970-2001. We find considerable variation in capacity utilization rates both across industries and over years within industries. Our results suggest that the expenditure constraint was binding, especially in periods of high interest rates.

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A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.

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In this paper we use the 2004-05 Annual Survey of Industries data to estimate the levels of cost efficiency of Indian manufacturing firms in the various states and also get state level measures of industrial organization (IO) efficiency. The empirical results show the presence of considerable cost inefficiency in a majority of the states. Further, we also find that, on average, Indian firms are too small. Consolidating them to attain the optimal scale would further enhance efficiency and lower average cost.

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Input congestion occurs at a given input bundle when the assumption of free disposability of inputs does not hold and an increase in input leads to a decline in output. In this paper we employ the nonparametric method of Data Envelopment Analysis (DEA) to examine the question on input congestion with respect to labor, using state level data from the Annual Survey of Industries for the period 1986-87 through 1999-2000. When the standard assumption of strong disposability is relaxed for the labor inputs, the nonparametric analysis of state-level data from Indian manufacturing shows considerable measure of labor input congestion. While in selected states congestion comes from non-production workers as well, the principal source of labor congestion is production labor. There is no evidence that the problem of labor congestion has become less severe during the post-Reform years. It appears that market forces without any major institutional changes in enforcement of labor discipline cannot eliminate congestion.

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In this paper we analyze state level data for total manufacturing constructed from the Annual Survey of Industries for the period 1986-2000 using the nonparametric method of Data Envelopment Analysis (DEA). We assess the extent of surplus labor in the manufacturing sector in the individual states in India. The study also investigates whether the same states show the maximum incidence of surplus labor every year in the sample period and if there any evidence that the extent of surplus labor in manufacturing has been reduced or eliminated in the post-reform era. Our study shows the presence of considerable measure of surplus labor in all of the years in a majority of the states. Things have worsened rather than improved after the reform. Also, the regional distribution of surplus labor has remain fairly unchanged with the same states performing inefficiently both before and after the reform.