120 resultados para Embedded Case Study
Resumo:
A case study of the response of two buildings to the construction of a 12 m diameter tunnel excavated by conventional method, in Italy, is studied. The 12 m diameter tunnel was constructed carrying out reinforcement of the tunnel face and around the crown prior to excavation and installation of the temporary sprayed concrete lining and the permanent reinforced concrete lining. Reflective prisms, placed at first floor level around the perimeter of the building facades, allowed building settlements to be measured. Ground settlements between the two buildings were measured using BRE type settlement studs. Extensive protective measures were adopted to maintain stability of the tunnel excavation and to reduce ground movements. The number of horizontal jet grout columns installed into the tunnel face was reduced over the course of the project. Results from CPT tests indicate that the undrained shear strength at the tunnel axis is around 120 kPa. SPT and undrained unconsolidated (UU) triaxial tests indicate lower strengths of around 80 kPa, although this may be due to sample disturbance.
Reducing Motor Vehicle Greenhouse Gas Emissions in a Non-California State: A Case Study of Minnesota
Resumo:
Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.
Resumo:
Purpose - In recent years there has been increasing interest in Product Service Systems (PSSs) as a business model for selling integrated product and service offerings. To date, there has been extensive research into the benefits of PSS to manufacturers and their customers, but there has been limited research into the effect of PSS on the upstream supply chain. This paper seeks to address this gap in the research. Design/methodology/approach - The research uses case-based research which is appropriate for exploratory research of this type. In-depth interviews were conducted with key personnel in a focal firm and two members of its supply chain, and the results were analysed to identify emergent themes.b Findings - The research has identified differences in supplier behaviour dependent on their role in PSS delivery and their relationship with the PSS provider. In particular, it suggests that for a successful partnership it is important to align the objectives between PSS provider and suppliers. Originality/value - This research provides a detailed investigation into a PSS supply chain and highlights the complexity of roles and relationships among the organizations within it. It will be of value to other PSS researchers and organizations transitioning to the delivery of PSS. © Emerald Group Publishing Limited.
Resumo:
Purpose - The purpose of this paper is to develop a framework of total acquisition cost of overseas outsourcing/sourcing in manufacturing industry. This framework contains categorized cost items that may occur during the overseas outsourcing/sourcing process. The framework was tested by a case study to establish both its feasibility and usability. Design/methodology/approach - First, interviews were carried out with practitioners who have the experience of overseas outsourcing/sourcing in order to obtain inputs from industry. The framework was then built up based on combined inputs from literature and from practitioners. Finally, the framework was tested by a case study in a multinational high-tech manufacturer to establish both its feasibility and usability. Findings - A practical barrier for implementing this framework is shortage of information. The predictability of the cost items in the framework varies. How to deal with the trade off between accuracy and applicability is a problem needed to be solved in the future research. Originality/value - There are always limitations to the generalizations that can be made from just one case. However, despite these limitations, this case study is believed to have shown the general requirement of modeling the uncertainty and dealing with the dilemma between accuracy and applicability in practice. © Emerald Group Publishing Limited.
Resumo:
Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.