Engineering of Xinjiang Non Electricity Area and the Project Risk Assessment

2013 ◽  
Vol 411-414 ◽  
pp. 2537-2541
Author(s):  
Yuan Sheng Huang ◽  
Chun Yan Jia
Keyword(s):  
Risk Assessment ◽  
Economic Development ◽  
Analytic Hierarchy Process ◽  
Daily Life ◽  
Good Choice ◽  
Analytic Hierarchy ◽  
Project Risk ◽  
New Energy ◽  
The Stability ◽  
Hierarchy Process

By the end of 2010, Xinjiang has 2754 000 families (10753 000 population) who are not allowable to use electricity. This project is related to the economic development of these areas and is of great importance to enhance people,s welfare. It is also an important project in the Twelfth Five-Year plan. This paper supplies us two realization modes for non electricity area through electric grid extension and new energy power. It is appropriate to seek help from the main grid to extend electricity problems and ensure the stability and security of the electricity in these areas, in which population is relatively dense, or places are good prospects for the development or mineral rich. But for a considerable number of scattered or not fixed farmers and herdsmen, the utilization of new energy to realize the power of their daily life is a good choice. On this basis, this paper carried out the risk assessment of the implementation of the project by using fuzzy analytic hierarchy process.

scholarly journals Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

2018 ◽  
Vol 10 (12) ◽  
pp. 4780 ◽  
Author(s):  
Min-Sung Kim ◽  
Eul-Bum Lee ◽  
In-Hye Jung ◽  
Douglas Alleman
Keyword(s):  
Risk Assessment ◽  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Raw Materials ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Project Risk ◽  
Inference System ◽  
Hierarchy Process

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.

A Novel Approach to Evaluate the Stability of Production Manufacturing System Based on Petri-Net and Analytic Hierarchy Process

2012 ◽  
Vol 605-607 ◽  
pp. 336-340
Author(s):  
Hou Xing You
Keyword(s):  
Analytic Hierarchy Process ◽  
Petri Net ◽  
Manufacturing System ◽  
New Method ◽  
System Stability ◽  
Production Factor ◽  
Analytic Hierarchy ◽  
The Stability ◽  
Whole Life Cycle ◽  
Hierarchy Process

In the whole life cycle of production process, the stability of production manufacturing system is an important production factor. However, there were a few researches about the system stability in the past years. In this paper, for the stability of production manufacturing system, a new method is proposed based on Petri-net and analytic hierarchy process. In the proposed method, the reachability of manufacturing system is judged by using Petri-net, and the system stability is calculated by the successful probability of the key production nodes. Finally, evaluation steps of the new method are given, and the new evaluation method is applied in case study.

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