Aluminum metal matrix composites, which exhibit significantly high compressive strength, were produced through the squeeze casting process using aluminum 7075 alloy as the matrix material and 2.5 wt% alumina as reinforcement. The process parameters of squeeze casting were prudently selected based on the literature in order to obtain better mechanical properties such as compressive strength and hardness. Samples were examined using an optical microscope, energy dispersive spectroscopy, a scanning electron microscope, and X-ray diffraction analysis. The optical micrograph showed low porosity in the produced composite, which matched the porosity measured using the Archimedes principle. The scanning electron microscope showed uniform distribution of reinforcement in the grain boundaries of the matrix. An X-ray diffraction analysis confirmed the presence of Al 2 O 3 particles in the composite. The hardness of the composite improved from 44 to 59 HRB. The compressive strength of the composite improved significantly with the addition of alumina reinforcement to 587 MPa when compared to Al 7075 alloy as well as other aluminum metal matrix composites reported in the literature.
Today's greater product variety, shorter product life cycle, and lower production costs are pushing companies to look beyond their own boundaries, thereby, creating complexity in the management of the supply chain. To manage such complexity, it is imperative that the management understand the associated complexity drivers and their interrelationships. This study identified twenty-three drivers responsible for supply chain complexity and classified them by using various criteria. In addition, the study presents a structural model using interpretive structural modelling (ISM) methodology to understand the inter-relationships between one driver to another. The research findings showed that drivers such as customer need, competitor action, and government regulation are beyond the control of supply chain partners, and have found the highest dominance with respect to supply chain complexity. Conversely, drivers related to tactical issues such as production planning and control, logistics and transportation, forecasting error, and marketing and sales are found to be the dependent drivers. Remaining drivers, such as company culture, number of suppliers, product variety, and organizational structure fall between the former two classifications. These drivers are related to strategic issues and require action from the upper level of the management hierarchy.
Purpose
– The purpose of this paper is to develop a mathematical model of a make-to-order manufacturing company simultaneously negotiating multiple contingent orders that possess conflicting issues in order to achieve order acceptance decisions (OADs).
Design/methodology/approach
– The paper developed a mathematical model by incorporating probabilistic theory and some theories of negotiation in the OAD problem. The model helps to harness the relationship between the manufacturer and customers of contingent orders on conflicting issues. A numerical example is enumerated to illustrate the working mechanism and sensitivity of the model developed.
Findings
– In the negotiation-based OAD system, if more than one customer is willing to negotiate on the offer of manufacturer, rather than engaging in one-to-one negotiation, the manufacturer has to negotiate with all the customers simultaneously to maximize the expected contribution and acceptance probability from all the orders. Also, the numerical example illustrates that, sometimes, rejecting an order/orders from the order set gives better results in terms of the expected contribution than continuing negotiations on them.
Originality/value
– Through continuing research efforts in this domain, certain models and strategies have been developed for negotiation on a one-to-one basis (i.e. negotiation by the manufacture with only one customer at a time). One-to-one negotiation will neither help companies to streamline their production systems nor will it maximize the expected contribution. To the best of the author’s knowledge, so far, this is the first instance of research work in the domain of a joint OAD and negotiation framework that attempts to develop a simultaneous negotiation method for arriving at OADs.
Bone drilling is a well-known process in operative fracture treatment and reconstructive surgery. The cutting ability of the drill is lost when used for multiple times. In this study, the effect of different levels of drill wear on bone temperature, drilling force, torque, delamination around the drilling region and surface roughness of the hole was investigated using a series of experiments. Experimental results demonstrated that the wear of the drill is strongly related to the drilling force, torque, temperature and surface roughness of the drilled hole. Statistical analysis was performed to find the effect of various factors on multiple response variables in the bone drilling process. The favorable conditions for bone drilling are obtained when feed rate, drill speed and the roughness of the cutting edge of the drill were fixed at 30 mm, 2000 rpm and up to 2 mm, respectively. Further, analysis of variance (ANOVA) was performed to determine the factor with a significant impact on the response variables. F-test and p-value indicated that the feed rate had the highest effect on grey relational grade followed by the roughness of the drill. This study suggests that the sharp drill along with controlled drilling speed and feed rate may be used for safe and efficient surgical drilling in bone.
The purpose of this research was to study the recognition, application and quantification of the risks associated in managing projects. In this research, the management of risks in an oil and gas project is studied and implemented within a case company in Oman. In this study, at first, the qualitative data related to risks in the project were identified through field visits and extensive interviews. These data were then translated into numerical values based on the expert's opinion. Further, the numerical data were used as an input to Monte Carlo simulation. RiskyProject Professional TM software was used to simulate the system based on the identified risks. The simulation result predicted a delay of about 2 years as a worse case with no chance of meeting the project's on stream date. Also, it has predicted 8% chance of exceeding the total estimated budget. The result of numerical analysis from the proposed model is validated by comparing it with the result of qualitative analysis, which was obtained through discussion with various project managers of company.
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