低价中标总承包项目成本管理探讨

南港工业区一期东五区吹填造陆工程为设计一施工总承包项目,作为公司在南港工业区经营战略的首个承揽工程,属低价中标。工程中标后,由于预期的外海防护未及时完成,造成工程开工延误。工程开工时,受寒流、大风和冰冻的影响,加上燃油费上涨,导致直接施工成本大幅上涨,成本压力巨大。为扭转亏损,在项目实施过程中,充分利用了“设计-施工总承包”的平台,进行了方案优化和设计细化。同时,在实施过程中,加强现场管理,保证了成本管理目标的实现。项目实施后与原中标成本相比较,节约成本1116．77万元,最后达到扭亏,略有盈余。     

以精细化管理促进机电工程项目降本增效

本文结合项目实施的过程，从项目实施的前期策划、项目实施过程中的精细化管理、项目竣工后的总结三个阶段阐述了降低各种成本、提高项目经济效益的措施。     

WBS分解在成本全过程管控的应用

本文阐述了WBS结构分解在项目成本管理中的应用,通过WBS分解,将一个庞大的项目分解成若干个小部分,以化大为小、化繁为简的方式从前期策划、目标制定、过程控制实施项目,全过程成本管控,从而实现预期利润目标。     

智能建筑典型工程案例解析——世贸奥临花园社区智能化系统规划与实施

本文记述了北京世茂奥临花园前期规划、产品及方案优化设计、项目实施阶段等方面的技术实践工作。通过项目实施过程的总结，分析了方案设计的部分实际效果，证明前期规划阶段技术方提前介入的重要性。结合工程实例介绍工程实施阶段方案调整、过程及技术管理的部分经验。     

试谈市政公用工程投标前后施工组织设计的编制特点和要点

随着我国建筑业市场经济的发展和完善,建筑施工企业通过招标的方式承揽工程是一个主要途径。高水平的标前施工组织设计将能给企业中标增加制胜的筹码。而项目一旦中标,标后的实施性施工组织设计将在中标项目从旅工准备和施工实施全过程管理中指导施工生产,降本增效等方面发挥作用。弄清两类施工组织设计的特点,根据不同时期的需要编制出科学、合理、实用的旋工组织设计十分重要。     

浅谈钢结构工程施工项目管理

随着社会的进步,近十几年来工程项目管理在国内为受到人们的普遍重视,逐渐形成一门成熟的学科,成为国内外管理领域中的一大热点。在工程的全过程控制中,前期的策划、决策很重要,在工程实施阶段,它主要从进度、成本、质量、合同、信息、组织协调、风险、安全等几个方面对工程进行全方面的管理。在此我在工程实施阶段中的进度、成本、质量发表一点见解。     

浅谈建设工程项目的科学管理

建设工程项目管理是通过工程项目委托的管理公司对拟建工程项目预先进行周密细致的前期策划和工程立项以后的详细计划及工程实施阶段严格控制而达到对工程建设全过程的掌控。     

BIM技术在机电安装工程创优中的应用

本文以湖北省医养康复中心项目为例,在机电安装工程前期创优策划阶段进行全方位的BIM建模和深化设计,完成机电管线的综合布局、成品支架及型钢支架的设计图纸、机房深化方案、管井优化调整、屋面管线优化、装配式机房、施工交底等,大大提高了机电安装策划的精细度和深度,减少了大量不必要的拆改返工,使很多大体量、高难度、抢工期的项目能够实现一次成优,为实现精细化施工、高品质建造打下了坚实的基础。     

关于房地产开发项目前期的成本控制研究

房地产开发商为了获得经济效益的最大化,对工程的各个项目环节进行成本控制十分重要。由此可见,房地产开发项目的成本控制工作贯穿于整个房地产开发项目的始末,其中前期成本控制因为会影响后续工作的成本,是整个项目顺利实施的有利保证,所以成为成本控制的基础和关键环节。本文从房地产开发项目成本控制的内涵人手,详细分析了房地产开发项目前期成本的构成及其重要性,并就控制房地产开发项目前期成本的有效途径进行了深入的探讨,以期为促进我国房地产开发行业的健康快速发展做出贡献。     

石油天然气工程设计阶段的文控管理

西部原油成品油管道工程初步设计项目部通过细致完善的前期策划。合理的组织配置，明确的部门职责，通畅清晰的管理流程，达到了项目文件的获取、处理、下发等运作的高效、准确，加快了项目进度，节约了项目成本之目的。     

Improving manufacturing lead time using holistic approach to planning and execution with integrated data structures: numerical simulation and comparison

Manufacturing planning and control (MPC) plays a significant role in effective planning of requirements and execution of those plans. It also influences various performance measures, in particular on-time delivery, which is dependent on many factors including manufacturing lead time. This paper aims to address key issues of infinite loading of resources, lack of forward planning, and limited simultaneous planning capabilities of MRP through a holistic approach to planning of various components and execution of those plans, based on integrated data structures. It is shown that integrated data structures, combining hierarchical single-level BOMs and sequential operations routings using a holistic approach to planning and execution enable reducing lead time by eliminating slack times associated with traditional methods. Furthermore, manufacturing lead time, based on integrated data structures is a true representation of operation times and is shorter compared with traditional lead time. Sensitivity analysis on lead-time with bills-of-materials (BOM) levels and floats shows that the holistic approach to planning and execution with integrated data structures is an effective way of improving lead-time, in particular when product structures involve many levels of BOMs and floats (slack times). The proposed holistic approach provides forward planning, simultaneous planning of components, and finite loading of resources. It is expected that the concept of integrated data structures be extended to model transaction data with process functions (e.g. production order cycle), which would improve overall cycle times by eliminating manual functions associated with current methods.     

Fuzzy multiple-goal programming for analysing outsourcing cost-effectiveness in hi-tech manufacturing

Given high-tech industry trends such as limited production, diverse model range, short product life cycle, and high customer responsiveness, issues related to recognitive core vs. non-core operations in internal vs. external environments are crucial in hi-tech production systems planning. This work elucidates the relationship between capacity planning and suppliers with a focus on quantity allocation, manufacturing quantity, capacity limit, warehouse space, and time period for hi-tech production planning. A fuzzy multiple-goal programming approach is adopted to model total cost, holding cost, and rework cost in order to analyse the relative cost-effectiveness of different factors. The proposed model was examined via the fuzzy analysis of its application to an actual building-integrated photovoltaic (BIPV) manufacturer with variable characteristics. The proposed model of cost-effectiveness accommodates variables such as multiple components, quality, and responsiveness, it integrates multi-stage functions, and a specific implementation is demonstrated. Various scenarios are designed to analyse the transaction options for outsourcing under combined schemes. The analytical results in this study can help decision makers to systematically analyse the cost effectiveness of outsourcing during capacity planning in practical applications.     

地铁线网规划中几个值得商榷的问题

我国城市正在经历地铁建设大发展的时期,一个十分紧迫且十分重要的问题是在进行线路建设前如何做好地铁线网布局规划。文章结合近年来国内开展地铁线网规划的实践,探讨了地铁线网规划中的几个关键问题,包括线网合理规模的论证、线网空间形态与构架以及地铁线网与城市其它交通方式的衔接等问题。     

Two-stage stochastic master production scheduling under demand uncertainty in a rolling planning environment

This paper proposes a scenario-based two-stage stochastic programming model with recourse for master production scheduling under demand uncertainty. We integrate the model into a hierarchical production planning and control system that is common in industrial practice. To reduce the problem of the disaggregation of the master production schedule, we use a relatively low aggregation level (compared to other work on stochastic programming for production planning). Consequently, we must consider many more scenarios to model demand uncertainty. Additionally, we modify standard modelling approaches for stochastic programming because they lead to the occurrence of many infeasible problems due to rolling planning horizons and interdependencies between master production scheduling and successive planning levels. To evaluate the performance of the proposed models, we generate a customer order arrival process, execute production planning in a rolling horizon environment and simulate the realisation of the planning results. In our experiments, the tardiness of customer orders can be nearly eliminated by the use of the proposed stochastic programming model at the cost of increasing inventory levels and using additional capacity.     

Applying a risk assessment approach for cost analysis and decision-making: a case study for a basic design engineering project

Abstract

Many uncertainties and cost variations occur in the work activities of a project, thereby causing many possibilities of under-estimating or over-estimating for a bid price. A comprehensive study for each process of risk management should be investigated to achieve project objectives. However, a limited number of studies have a comprehensive viewpoint to indicate the benefits of risk management and the effect on project performance for the engineering design stage of engineering–procurement–construction (EPC) projects, especially in the basic design stage. This research was conducted to identify and analyze the risks associated with a Basic Design Engineering (BDE) project for a high value-added petrochemical plant in Taiwan. First, a project risk management work flow was proposed as an effective tool to minimize the project risks and maximize the management capacity of practitioners. Second, the cost effect of project risks was described by conducting a case study for the design process of a high value-added petrochemical plant using a Monte Carlo simulation. A risk register was identified to support the data required for conducting simulation analysis. The results of this paper provide reference points for risk management planning of project execution and help project managers evaluate particular risks at the engineering design stage of EPC projects to avoid cost overruns.     

Integration of manufacturing and distribution networks in a global car company – network models and numerical simulation

Global supply chain practices and their effects have received considerable attention over the last two decades. In the recent past, the need for integration across supply chains has been identified as a key for effective and efficient operations of supply chains. This is observed with the increasing trend of collaborative partnerships among supply chain partners. This paper presents an integrated approach for manufacturing and distribution networks within the supply chain system of a global car company. The paper shows that the integration of manufacturing and distribution networks creates the environment for effective planning of many components and execution/follow-up of those plans. These components include materials, resources, operations/activities, suppliers and customers. The main features of the integration include component integration at individual networks via use of a central warehouse. This integration reduces various interfacing steps between partners and enables representations of relationships (component precedence, parent-component and component-component). The proposed integrated model is numerically tested using past data from one of Japan's auto-makers, based in the emerging economy of Thailand. The paper concludes that the integrated supply network eliminates the need for interfacing of individual networks and enables simultaneous planning of many components as well as forward planning of supply components in global supply chain operations. It also shows that the integrated approach is capable of providing visibility, flexibility, and maintainability for further improvement in the supply network environment.     

A stochastic dynamic programming based model for uncertain production planning of re-manufacturing system

Re-manufacturing is recycling by manufacturing as-good-as-new products from used products, often involving disassembly, cleaning, testing, part replacement/repair, and re-assembly operations. Production planning and inventory control is one of the most important research issues for re-manufacturing system, which are faced with a greater degree of uncertainty and complexity. This leads to a critical need for planning and control systems designed to deal with the added uncertainty and complexity. We formulate a stochastic dynamic programming based model to study the production planning, i.e. dynamic lot sizing problem, of re-manufacturing systems. In the model the demand and return amounts are stochastic over the finite planning horizon. The objective is to determine the quantities that have to be re-manufactured at each period in order to minimise the total cost, including re-manufacturing cost, holding cost for returns and re-manufactured products and backlog cost. The optimal production plan of the re-manufacturing system over a finite planning horizon can be obtained with the policy iteration method. In the end, a numerical example is performed to illustrate how the model is applied and to prove its feasibility.     

Capacity and material requirement planning modelling by comparing deterministic and fuzzy models

A model for the capacity and material requirement planning problem with uncertainty in a multi-product, multi-level and multi-period manufacturing environment is proposed. An optimization model is formulated which takes into account the uncertainty that exists in both the market demand and capacity data, and the uncertain costs for backlog. This work uses the concept of possibilistic programming by comparing trapezoidal fuzzy numbers. Such an approach makes it possible to model the ambiguity in market demand, capacity data, cost information, etc. that could be present in production planning systems. The main goal is to determine the master production schedule, stock levels, backlog, and capacity usage levels over a given planning horizon in such a way as to hedge against the uncertainty. Finally, the fuzzy model and the deterministic model adopted as the basis of this work are compared using real data from an automobile seat manufacturer. The paper concludes that fuzzy numbers could improve the solution of production planning problems.     

基于机器视觉的轴承盖外形轮廓分类方法

目的 为提高花卉类包装的自动化程度,解决运动冲击、低执行率等问题,以包装机械手为研究对象,设计一种花卉包装机械手时间和冲击最优轨迹规划方法。方法 采用5次B样条插值函数实现关节曲线构建。采用改进遗传算法实现机械手运动过程优化,不仅可以提高机械手执行效率,而且能够确保其运行过程中不会出现冲击问题。通过改进罚函数和自适应交叉变异概率来解决不等式约束和局部最优问题。另外,设计花卉包装机械手的运动控制系统,包括基于STM32芯片的控制器以及触摸屏控制界面。结果 通过仿真和实验验证了所述方法的有效性,结果表明包装机械手执行效率大约提高了10%,抓取速度可以达到60次/min;机械手抓取迅速、运转平稳,并没有出现明显的冲击问题。结论 所述轨迹规划方法和控制系统可以提高包装机械手控制性能,能够满足花卉包装、分拣要求。     

Comparing dynamic risk-based scheduling methods with MRP via simulation

It is well known that material requirements planning (MRP) is a deterministic planning tool which heavily relies on accurate demand forecast, and that its performance under perturbed, constantly changing environment becomes questionable. Although many companies still use basic MRP as a planning tool, there are other alternative tools available. For example, Factory Physics Inc. has developed a tool called dynamic risk-based scheduling (DRS), which creates a set of policy parameters (e.g. work in process (WIP) level, lot sizes, re-order point, and re-order quantity) that work for a range of situations. The main objective of this paper is to compare DRS and MRP scheduling systems for single-machine and multi-machine systems via simulation. Their performance measures are compared for various systems assuming three levels of demand uncertainty. The simulation results suggest that DRS outperforms MRP in terms of robustness, fill rate and inventory level.