• 论文 •    

基于关键链的多项目计划编制

陈友玲,张晓丽,覃承海,   

  1. 1.重庆大学 机械工程学院,重庆400030;2.重庆工学院 重庆汽车学院,重庆400050;3.太原科技大学 经济与管理学院,山西太原030024
  • 出版日期:2009-07-15 发布日期:2009-07-25

Multi-project planning based on critical chain

CHEN You-ling, ZHANG Xiao-li, QIN Cheng-hai,   

  1. 1.School of Mechanical Engineering, Chongqing University, Chongqing 400030, China;2.Chongqing Automobile College, Chongqing Institute of Technology, Chongqing 400050, China;3.School of Economics & Management, Taiyuan University of Science & Technology, Taiyuan 030024, China
  • Online:2009-07-15 Published:2009-07-25

摘要: 传统计划方法只考虑关键路径不注重不确定性因素等约束对计划的影响,从而造成生产周期长、完工率低、交货延误等。为此,利用网络技术、约束理论、关键链等知识,提出了基于关键链的面向多项目计划编制新方法——关键链计划方法。在项目管理中,该方法考虑了人为因素和资源约束等不确定性因素,提出通过改进工序预估时间、剔除工序缓冲时间,设置项目缓冲、能力缓冲等措施来规避人为因素和其他风险因素对计划的影响,运用关键链计划方法编排了瓶颈与非瓶颈项目计划,并通过Crystal Ball软件对基于传统的关键路径法/计划评审技术的项目计划,以及关键链计划方法的项目计划进行了Monte Carol模拟仿真。仿真结果验证了该关键链计划方法的可行性。

关键词: 项目管理, 关键链, 多项目计划, 不确定因素, 仿真

Abstract: Traditional planning methods focus on critical path but neglect some uncertain factors which affected production planning. This would extend production cycle, decrease finishing rate and delay products delivery. To solve these problems, a new multi-project planning method called Key Chain Planning (KCP) was proposed by combining theory of constrains, critical chain and Web technology. This method considered human factors and resources constrains in the project management. To avoid influences caused by human or other risk factors, ideas of improving process pre-calculating time, eliminating process buffer time, as well as setting up project buffer and ability buffer were proposed. Then the KCP method was used to conduct scheduling in the bottleneck and non-bottleneck flexibly. The Monte arol simulation models were constructed for Critical Path Method (CPM)/Project Evaluation Review Technique (PERT)-based project planning and KCP-based project planning by the Crystal Ball software. The simulation result verified KCP's feasibility.

Key words: project management, key chain, multi-project planning, uncertain factors, simulation

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