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The use of biofuels in the United States has increased dramatically in the last few years. The largest source of feedstock for ethanol to date has been corn. However, corn is also a vitally important food crop and is used commonly as feed for cattle and other livestock. To prevent further diversion of an important food crop to production of ethanol, there is great interest in developing commercial-scale technologies to make ethanol from non-food crops, or other suitable plant material. This is commonly referred to as biomass. A review is made of lignocellulosic sources being considered as feedstocks to produce ethanol. Current technologies for pretreatment and hydrolysis of the biomass material are examined and discussed. Production data and cost estimates are culled from the literature, and used to assist in development of mathematical models for evaluation of production ramp-up profiles, and cost estimation. These mathematical models are useful as a planning tool, and provide a methodology to estimate monthly production output and costs for labor, capital, operations and maintenance, feedstock, raw materials, and total cost. Existing credits for ethanol production are also considered and modeled. The production output in liters is modeled as a negative exponential growth curve, with a rate coefficient providing the ability to evaluate slower, or faster, growth in production output and its corresponding effect on monthly cost. The capital and labor costs per unit of product are determined by dividing the monthly debt service and labor costs by that month’s production value. The remaining cost components change at a constant rate in the simulation case studies. This methodology is used to calculate production levels and costs as a function of time for a 25 million gallon per year capacity cellulosic ethanol plant. The parameters of interest are calculated in MATLAB with a deterministic, continuous system simulation model. Simulation results for high, medium, and low cost case studies are included. Assumptions for the model and for each case study are included and some comparisons are made to cost estimates in the literature. iv While the cost per unit of product decreases and production output increases over time, some reasonable cost values are obtained by the end of the second year for both the low and medium cost case studies. By the end of Year 2, total costs for those case studies are $0.48 per liter and $0.88 per liter, respectively. These cost estimates are well within the reported range of values from the reviewed literature sources. Differing assumptions for calculations made by different sources make a direct cost comparison with the outputs of this modeling methodology extremely difficult. Proposals for reducing costs are introduced. Limitations and shortcomings of the research activity are discussed, along with recommendations for potential future work in improving the simulation model and model verification activities. In summary, the author was not able to find evidence—within the public domain—of any similar modeling and simulation methodology that uses a deterministic, continuous simulation model to evaluate production and costs as a function of time. This methodology is also unique in highlighting the important effect of production ramp-up on monthly costs for capital (debt service) and labor. The resultant simulation model can be used for planning purposes and provides an independent, unbiased estimate of cost as a function of time.

No description available.

The purpose of this study is to describe how competency modeling and knowledge management can support a ramp-up of an existing complex production. An abductive study approach is used, to keep the study open for new directions to generate new theories. A case study is done at ABB Machine, followed by two reference cases at Scania and Volvo. Semi-structured interviews are used together with observations to get qualitative data. A conceptual framework is used in the interviews to easier connect the data to the theoretical framework. The data is compiled and analyzed with a thematic approach. Empirical and theoretical data is separately analyzed, followed by a discussion how they could support a ramp-up process. Results showed that competency modeling and knowledge management together support a ramp-up better by improving knowledge transfer and flexibility. Flexibility is created from strategic modeling where personnel hold several competencies which enable for greater adoption to existing production. With proper knowledge transfer, new staff can be introduced more efficiently, and experienced ones can broaden their competencies furthermore. Also, it gives effects such as better work mood, new approaches on matters and less ergonomic injuries. The results also showed the importance of time required for transfer, which if not respected can effect ramp-up quality negatively. The recommendations for complex factory production is to use more competence broadening, comply with the time needed, have skilled trainers, and collective goals for the whole organization. / Syftet med denna studie är att undersöka hur kompetensmodellering och kunskapshantering kan stödja upprampningen i en komplex och befintlig produktionsindustri. I studien användes en abduktiv ansats. En fallstudie genomfördes hos ABB Machines samt två referensstudier hos Scania och Volvo för att kunna jämföra data. Datainsamlingen gjordes genom semistrukturerade intervjuer för att få kvalitativ data. Operationalisering användes i intervjuerna för att enkelt kunna koppla data till teori. Data som samlats in sammanställdes och analyserades med en tematisk modell. Empirisk och teoretisk data som samlats in gällande kompetensmodellering och kunskapshantering i komplex produktion analyserades först separat för att i nästa steg diskuteras hur de kombinerat kan stödja en upprampningsprocess. Resultatet av studien visade att kompetensmodellering och kunskapshantering tillsammans kan främja en bättre upprampning i en produktion, genom förbättrad kunskapsöverföring samt strukturerad flexibilitet. Med högre flexibilitet kan produktionslag enklare anpassa sig mot ett ändrat produktionsläge, genom att personal innehar ett flertal kompetenser. Detta bidrar till att interna resurser kan utnyttjas mer effektivt. Kvalitativ och effektiv kunskapsöverföring bidrar till att ny personal kan introduceras snabbt samt att erfaren personal kan bredda och fördjupa sina kunskaper för ökad flexibilitet. Vid upplärning är det viktigt att personal ges tid för att kunna ta emot ny kunskap. Detta leder till flera positiva effekter såsom bättre arbetsmiljö, nya synsätt och färre belastningsskador. Rekommendationerna från studien är att satsa på kompetensbreddning, utbildade mentorer, samt gemensamma mål för hela organisationen.

[pt] O crescente uso de modelos integrados de produção (MIP) na indústria de petróleo como solução para representar o potencial de uma jazida se justifica pelos atuais cenários encontrados para o desenvolvimento de novos projetos, caracterizado por baixos preços de venda do petróleo e conceitos de produção de alta complexidade. Esta abordagem, em que diferentes partes de um sistema de produção são integradas, permite ao usuário um entendimento detalhado das interações entre reservatório, poços e rede de escoamento, e facilita a detecção de gargalos e consequentemente a otimização do plano de explotação. Neste contexto, é fundamental obter uma modelagem satisfatória do fluido em todo o sistema de produção. O modelo deve honrar tanto o escoamento no meio poroso, isotérmico, quanto o escoamento nos poços e dutos, que precisa ser caracterizado em várias temperaturas. Além disso, o modelo deve ter tempo de simulação adequado. Uma maneira criteriosa de modelar as propriedades de um fluido é através do ajuste de uma equação de estado (EOS). Uma EOS detalhada com 24 componentes determinada por cromatografia gasosa e EOS simplificadas com 14, 9, 7, 6, 5 e 4 pseudocomponentes foram geradas para avaliar este problema. As EOS foram usadas para representar as propriedades PVT em um MIP e ao final foram comparadas as respostas das EOS simplificadas e detalhadas, a fim de estabelecer resultados adequados com um tempo computacional adequado. Os resultados obtidos mostram que o uso de EOS excessivamente simplificadas, apesar da melhoria no tempo computacional, podem gerar resultados insatisfatórios em modelos integrados de produção. / [en] The growing use of integrated production models (IPM) in the oil industry as a solution to represent the potential of a field is justified by the current scenarios found for the development of new projects, characterized by low oil prices and high complexity production concepts. This approach, where different parts of a production system are integrated, allows the user to have a detailed understanding of the interactions between reservoir, wells and gathering system, and facilitates the detection of bottlenecks and consequently the optimization of the exploitation plan. In this context, it is essential to obtain a satisfactory fluid model in the entire production system. The model must honor both the flow in the porous media, isothermal, and the flow in the wells and pipelines, which must be characterized at various temperatures. In addition, the model must have adequate simulation time. A rigorous way to model the properties of a fluid is by adjusting an equation of state (EOS). A detailed EOS with 24 components determined by gas chromatography and simplified EOS with 14, 9, 7, 6, 5 and 4 pseudocomponents were generated to evaluate this problem. The EOS were used to represent the PVT properties in a IPM and the responses of the simplified and detailed EOS were compared, in order to establish an adequate results with an adequate computational time. The results obtained show that the use of excessively simplified EOS, despite the improvement in computational time, can generate unsatisfactory results in integrated production models.