834 resultados para Manufacturing industry
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The main objective of this study is to verify the influence of Environmental Management (EM) on Operational Performance (OP) in Brazilian automotive companies, analyzing whether Lean Manufacturing (LM) and Human Resources (HR) interfere in the greening of these companies. Therefore, a conceptual framework listing these concepts was proposed, and three research hypotheses were presented. A questionnaire was elaborated based on this theoretical background and sent to respondents occupying the highest positions in the production/operations areas of Brazilian automotive companies. The data, collected from 75 companies, were analyzed using structural equation modeling. The main results are as follows: (a) the model tested revealed an adequate goodness of fit, showing that overall, the relations proposed between EM and OP and between HR, LM and EM tend to be statistically valid; (b) EM tends to influence OP in a positive and statistically weak manner; (c) LM has a greater influence on EM when compared to the influence HR has over EM; (d) HR has a positive relationship over EM, but the statistical significance of this relationship is less than that of the other evaluated relationships. The originality of this paper lies in its gathering the concepts of EM, LM, HR and OP in a single study, as they generally tend not to be treated jointly. This paper also provided valid empirical evidence for a littlestudied context: the Brazilian automotive sector. © 2012 Elsevier Ltd. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Due to globalization, is increasingly common for companies to make their products more competitive. With this background, the industries seek more efficient ways to produce. This paper aims to examine the tools of Lean Manufacturing applied in an industry luminaries ,addressing the positive aspects. Were applied tools like value stream mapping, Kanban, setup reduction and 5S program. With the application of these tools obtained improvements in processes, reducing lead time from factory and reducing the cost of the luminaries
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Waste effluents from the forest products industry are sources of lignocellulosic biomass that can be converted to ethanol by yeast after pretreatment. However, the challenge of improving ethanol yields from a mixed pentose and hexose fermentation of a potentially inhibitory hydrolysate still remains. Hardboard manufacturing process wastewater (HPW) was evaluated at a potential feedstream for lignocellulosic ethanol production by native xylose-fermenting yeast. After screening of xylose-fermenting yeasts, Scheffersomyces stipitis CBS 6054 was selected as the ideal organism for conversion of the HPW hydrolysate material. The individual and synergistic effects of inhibitory compounds present in the hydrolysate were evaluated using response surface methodology. It was concluded that organic acids have an additive negative effect on fermentations. Fermentation conditions were also optimized in terms of aeration and pH. Methods for improving productivity and achieving higher ethanol yields were investigated. Adaptation to the conditions present in the hydrolysate through repeated cell sub-culturing was used. The objectives of this present study were to adapt S. stipitis CBS6054 to a dilute-acid pretreated lignocellulosic containing waste stream; compare the physiological, metabolic, and proteomic profiles of the adapted strain to its parent; quantify changes in protein expression/regulation, metabolite abundance, and enzyme activity; and determine the biochemical and molecular mechanism of adaptation. The adapted culture showed improvement in both substrate utilization and ethanol yields compared to the unadapted parent strain. The adapted strain also represented a growth phenotype compared to its unadapted parent based on its physiological and proteomic profiles. Several potential targets that could be responsible for strain improvement were identified. These targets could have implications for metabolic engineering of strains for improved ethanol production from lignocellulosic feedstocks. Although this work focuses specifically on the conversion of HPW to ethanol, the methods developed can be used for any feedstock/product systems that employ a microbial conversion step. The benefit of this research is that the organisms will the optimized for a company's specific system.
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This thesis is composed of three life-cycle analysis (LCA) studies of manufacturing to determine cumulative energy demand (CED) and greenhouse gas emissions (GHG). The methods proposed could reduce the environmental impact by reducing the CED in three manufacturing processes. First, industrial symbiosis is proposed and a LCA is performed on both conventional 1 GW-scaled hydrogenated amorphous silicon (a-Si:H)-based single junction and a-Si:H/microcrystalline-Si:H tandem cell solar PV manufacturing plants and such plants coupled to silane recycling plants. Using a recycling process that results in a silane loss of only 17 versus 85 percent, this results in a CED savings of 81,700 GJ and 290,000 GJ per year for single and tandem junction plants, respectively. This recycling process reduces the cost of raw silane by 68 percent, or approximately $22.6 and $79 million per year for a single and tandem 1 GW PV production facility, respectively. The results show environmental benefits of silane recycling centered around a-Si:H-based PV manufacturing plants. Second, an open-source self-replicating rapid prototype or 3-D printer, the RepRap, has the potential to reduce the environmental impact of manufacturing of polymer-based products, using distributed manufacturing paradigm, which is further minimized by the use of PV and improvements in PV manufacturing. Using 3-D printers for manufacturing provides the ability to ultra-customize products and to change fill composition, which increases material efficiency. An LCA was performed on three polymer-based products to determine the CED and GHG from conventional large-scale production and are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA study indicate that the CED of manufacturing polymer products can possibly be reduced using distributed manufacturing with existing 3-D printers under 89% fill and reduced even further with a solar photovoltaic system. The results indicate that the ability of RepRaps to vary fill has the potential to diminish environmental impact on many products. Third, one additional way to improve the environmental performance of this distributed manufacturing system is to create the polymer filament feedstock for 3-D printers using post-consumer plastic bottles. An LCA was performed on the recycling of high density polyethylene (HDPE) using the RecycleBot. The results of the LCA showed that distributed recycling has a lower CED than the best-case scenario used for centralized recycling. If this process is applied to the HDPE currently recycled in the U.S., more than 100 million MJ of energy could be conserved per annum along with significant reductions in GHG. This presents a novel path to a future of distributed manufacturing suited for both the developed and developing world with reduced environmental impact. From improving manufacturing in the photovoltaic industry with the use of recycling to recycling and manufacturing plastic products within our own homes, each step reduces the impact on the environment. The three coupled projects presented here show a clear potential to reduce the environmental impact of manufacturing and other processes by implementing complimenting systems, which have environmental benefits of their own in order to achieve a compounding effect of reduced CED and GHG.
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While revenue management (RM) is traditionally considered a tool of service operations, RM shows considerable potential for application in manufacturing operations. The typical challenges in make-to-order manufacturing are fixed manufacturing capacities and a great variety in offered products, going along with pronounced fluctuations in demand and profitability. Since Harris and Pinder in the mid-90s, numerous papers have furthered the understanding of RM theory in this environment. Nevertheless, results to be expected from applying the developed methods to a practical industry setting have yet to be reported. To this end, this paper investigates a possible application of RM at ThyssenKrupp VDM, leading to considerable improvements in several areas.
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The automotive industry is confronted with increasing competition, leading to higher cost pressures and the demand to optimize production processes and value chains. Here the RFID technology promises to improve a range of processes in logistics and manufacturing. Despite its promising potential in the automotive industry, RFID has not yet made a decisive step from pilots to real-life implementations in the supply chain. Building on existing models of technology adoption, we analyze RFID adoption dynamics in the automotive industry. Building on existing IOS adoption models tailored to RFID specifics and based on ten semi-structured interviews with OEMs and suppliers, we evaluate main drivers of RFID adoption in the automotive industry. Our key findings are that the use of a coercive approach by the OEM could be redundant because of the market-driven RFID adoption among many suppliers. Furthermore, suppliers implementing RFID can now gain an early mover competitive advantage by developing higher trust in their relationship with the OEM as well as accumulating unique expertise in this area.
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Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The production equipment used gives rise to various technological constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technological and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.