我国矿山企业成本管理创新研究

本文针对矿山企业生产对象的特殊性,提出了成本管理和控制有着不同一般企业的特征,分析了传统矿山企业成本核算仅仅针对产品本身,成本管理只重视企业制造成本,不重视业务流程管理和成本管理平台的构建、企业设计成本以及企业弃置费用等相关问题,最后从整个企业价值链出发,提出了对矿山企业成本控制的相关建议及措施,为我国矿山企业提供高效的成本信息,培育矿山企业长期竞争优势。     

发展以低成本和软技术为核心的江西省绿色建筑

绿色建筑将成为未来建筑的发展趋势。针对本省经济社会发展水平,江西省现阶段应以＂因地制宜＂、＂经济适用＂、＂本土科技＂为原则,大力推广以低成本和软技术为核心的绿色建筑,从而推进绿色建筑的全面发展,实现节能减排的战略目标。     

碾压砼施工技术在高摩赞大坝中的应用

本文阐述了碾压砼筑坝施工技术的概念,及国内外碾压砼坝的发展情况,详细介绍了高摩赞大坝砼运输及入仓方式、碾压砼分仓、碾压砼大坝施工方法和碾压砼施工注意事项,通过高摩赞碾压砼大坝施工分析,体现出了碾压砼施工在降低成本、机械化程度高等方面的优点,得出了值得广泛推广和应用的结论．     

试论井下作业全员成本目标管理体系的构建

江汉油田井下作业处按照全员参与、全面落实、多维管理的原则,事前计划、事中控制和事后分析相统一的原则,PDCA循环体系运转的原则,与全面预算管理互相融合的原则构建了全员成本目标管理体系。全员成本目标管理体系由“指标、执行、监控、考核”四个子体系构成。建立指标体系以明确管理目标;建立执行体系以落实管理指标;建立监控体系以及时发现问题、及时纠偏;建立考核体系以调动、激励员工投身成本管理。通过子体系的有效运行,持续提升成本管理水平。     

浅谈石油地震勘探项目成本管理

石油地震勘探项目成本管理的实质是在项目经理负责下,针对特定的作业环境和技术要求,组建一个作业团队,在规定的时间范围内,为完成项目而合理地利用有限的人力、物力、财力等资源,满足业主、单位、作业团队在时间、费用、质量上的不同要求。其目的是提高效率、减少消耗、降低项目成本,实现经济效益最大化。其原则是目标明确、总额控制、指标分解、动态调节。其关键环节包括项目资源计划、成本估算、成本分解和成本控制。挣得值方法(偏差控制法)是对项目进度和费用进行综合控制的一种有效方法。     

Trade-off between Safety and Cost in Planning Construction Site Layouts

Planning construction site layouts involves identifying the positions of temporary facilities on site, and accordingly it has a significant impact on the safety and efficiency of construction operations. Although available models are capable of minimizing the travel cost of resources on site, they do not consider safety as an important and separate objective in the optimization of site layouts. This paper presents the development of an expanded site layout planning model that is capable of maximizing construction safety and minimizing the travel cost of resources on site, simultaneously. The model incorporates newly developed concepts and performance criteria that enable the quantification of construction safety and travel cost of resources on site. The present model is developed in three main phases: (1) formulating decision variables and optimization objectives in this site layout planning problem; (2) identifying and satisfying all practical constraints in this optimization problem; and (3) implementing the model as a multiobjective genetic algorithm. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing construction site layouts and generating optimal trade-offs between safety and travel cost of resources on site.     

Using Weibull Analysis for Evaluation of Cost and Schedule Performance

Large amounts of money are lost each year in the construction industry because of poor schedule and cost control. Few contractors specify and follow systematic schedule monitoring practices. Traditionally, the earned value method (EVM) is used to control and monitor schedule performance using the schedule and cost performance indices which compare the budgeted cost of work performed to what was originally scheduled or what is actually expended. This paper presents a statistical approach, namely Weibull analysis, to evaluate stochastically the schedule performance of construction or design projects. The approach can be used in conjunction with the EVM to enhance the evaluation and control of schedule performance. Weibull analysis is a common method for failure analysis and reliability engineering used in a wide range of applications. In this paper, the applicability of Weibull analysis for evaluating and comparing the reliability of the schedule performance of multiple projects is presented. The various steps in the analysis are discussed along with an example in which two projects are analyzed and compared. The authors conclude that Weibull analysis has several advantages and provides a relatively robust and effective method for construction managers to better control and monitor their projects.     

Stochastic Time–Cost Optimization Model Incorporating Fuzzy Sets Theory and Nonreplaceable Front

In a real construction project, the duration and cost of each activity could change dynamically as a result of many uncertain variables, such as weather, resource availability, productivity, etc. Managers/planners must take these uncertainties into account and provide an optimal balance of time and cost based on their own experience and knowledge. In this paper, fuzzy sets theory is applied to model the managers’ behavior in predicting time and cost pertinent to a specific option within an activity. Genetic algorithms are used as a searching mechanism to establish the optimal time–cost profiles under different risk levels. In addition, the nonreplaceable front concept is proposed to assist managers in recognizing promising solutions from numerous candidates on the Pareto front. Economic analysis skills, such as the utility theory and opportunity cost, are integrated into the new model to mimic the decision making process of human experts. A simple case study is used for testing the new model developed. In comparison with the previous models, the new model provides managers with greater flexibility to analyze their decisions in a more realistic manner. The results also indicate that greater robustness may be achieved by taking some risks. This research is relevant to both industry practitioners and researchers. By incorporating the concept of fuzzy sets, managers can represent the range of possible time–cost values as well as their associated degree of belief. The model presented in this paper can, therefore, support decision makers in analyzing their time–cost optimization decision in a more flexible and realistic manner. Many novel ideas have also been incorporated in this paper to benefit the research community. Examples of these include the use of fuzzy sets theory, nonreplaceable front concept, utility theory, opportunity cost, etc. With suitable modifications, these concepts can be applied to model to other similar optimization problems in construction.     

Quantifying Engineering Project Scope for Productivity Modeling

A poor scope definition in an engineering design project disrupts project rhythm, causes rework, increases project time and cost, and lowers the productivity and morale of the workforce. A quantitative measurement of the project scope is the basis for productivity modeling that involves the measurement, estimation, control, and evaluation of productivity. This paper proposes a conceptual model, the quantitative engineering project scope definition (QEPSD), to standardize the measurement of engineering project scope in construction projects, within a computer aided design environment. The QEPSD quantitatively measures engineering project scope, in terms of the complexity of design items by defining design categories and complexity functions appropriate to the particular discipline. The proposed method was originally verified and implemented specifically for steel drafting projects. Actual data was analyzed and used to demonstrate the benefits of historical data prepared using QEPSD for project scope definition. It was found that the new method led to increased utilization of previously untapped values in historical data, improving the accuracy of project scope definition, and productivity modeling. The paper concludes with a discussion of the potential benefits of adopting the QEPSD method, and its implications upon various project management functions.     

Estimating the development cost of custom software

In this paper an approach for the estimation of software development costs is presented. The method is based on the characterization of the software to be developed in terms of project and environment attributes and comparison with some similar completed project(s) recovered from a historical database. A case study is also presented, focusing on the calibration and application of the method on 59 information systems implementing supply chain functions in industry. Various strategies are explored, the best of which predicted effort quite effectively, with a mean estimation error of 24% with respect to the actual effort.