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The purpose of this paper is to carry out a systematic energy analysis for predicting the first and second law efficiencies and the entropy generation during a laser…
The purpose of this paper is to carry out a systematic energy analysis for predicting the first and second law efficiencies and the entropy generation during a laser surface alloying (LSA) process.
A three‐dimensional transient macroscopic numerical model is developed to describe the turbulent transport phenomena during a typical LSA process and subsequently, the energy analysis is carried out to predict the entropy generation as well as the first and second law efficiencies. A modified k–ε model is used to address turbulent molten metal‐pool convection. The phase change aspects are addressed using a modified enthalpy‐porosity technique. A kinetic theory approach is adopted for modelling evaporation from the top surface of the molten pool.
It is found that the heat transfer due to the strong temperature gradient is mainly responsible for the irreversible degradation of energy in the form of entropy production and the flow and mass transfer effects are less important for this type of phase change problem. The first and second law efficiencies are found to increase with effective heat input and remain independent of the powder feed rate. With the scanning speed, the first law efficiency increases whereas the second law efficiency decreases.
The top surface undulations are not taken care of in this model which is a reasonable approximation.
The results obtained will eventually lead to an optimized estimation of laser parameters (such as laser power, scanning speed, etc.), which in turn improves the process control and reduces the cost substantially.
This paper provides essential information for modelling solid–liquid phase transition as well as a systematic analysis for entropy generation prediction.
Process flexibility (PF) is seen as a hedging instrument against demand uncertainty. This paper aims to examine capacity decisions for both flexible and dedicated…
Process flexibility (PF) is seen as a hedging instrument against demand uncertainty. This paper aims to examine capacity decisions for both flexible and dedicated processes under production policies such as make-to-order and make-to-stock. The study identifies some relative benefits, in terms of expected profit, of the process flexible plant over the dedicated ones. Furthermore, the advantage appears to be contingent upon the decision on the preset service level.
Using the sample-based optimization procedure, a detailed computational analysis is undertaken to identify the conditions under which a flexible plant is preferred over a dedicated plant. A combination of genetic algorithm and sample-based optimization procedure is used to capture the effects of preset service level. The factors controlled in this paper include the demand variance, demand correlation, capacity investment cost and the product price.
According to this study, in a dedicated process changing to a flexible process is not justified for the same level of demand correlation even with high demand variance. In fact, a strict control on the preset service level prefers the dedicated strategy. The advantage of a flexible plant increases as the demand correlation decreases, product price decreases, price asymmetry increases or capacity investment cost increases. With a preset service level constraint, a flexible process should be preferred to a dedicated one only when the capacity investment cost is high or the products have low contribution margins.
The PF index is introduced in this paper to measure the benefit of a flexible plant over a group of dedicated plants. The benefits were found to be contingent upon the decision on the required service level.
Prior research suggests that there is enough residual uncertainty in conflict situations so that a person's attitude towards risk may influence his or her conflict…
Prior research suggests that there is enough residual uncertainty in conflict situations so that a person's attitude towards risk may influence his or her conflict behavior. This paper explores the level of dyadic conflict arising from negotiation between partners having different combinations of risk propensities. Dyadic conflict was measured as the sum of each dyadic partner's conflict score using the Rahim Organizational Conflict Inventory‐I. Risk propensities of negotiators were induced The results from the experiment provide clear evidence in support of the research hypothesis that in a dyad, the greater the disparity between the negotiating partners in their risk‐taking propensities, the greater will be the levels of dyadic conflict. The result suggests that conflict models of negotiating under uncertainty need to include risk propensities of the players to expand their descriptive power.
The purpose of this paper is to present a multi criterion failure mode effect and criticality analysis for coal-fired thermal power plants using uncertain data as well as…
The purpose of this paper is to present a multi criterion failure mode effect and criticality analysis for coal-fired thermal power plants using uncertain data as well as substituting the traditional risk priority number estimation method.
Grey-complex proportional assessment (COPRAS-G) method, a multi criteria decision making tool is applied to evaluate the criticalities of the failure modes (alternatives). In this model the criteria (criticality factor) against each alternative are expressed in grey number instead of crisp values.
Rupture failure of the straight tube of economizer (ECO) due to erosion is the highest critical failure mode whereas rupture failure of the stub of ECO due to welding defect is the lowest critical failure mode.
This paper incorporates human and environmental factors as additional factors which also influence the failure modes significantly. The COPRAS-G method is modified according this problem. Uncertainty in the scoring of criticality factors against each failure mode by various maintenance personnel is expressed in grey numbers.