畢業(yè)設(shè)計(jì)外文翻譯—成本管理計(jì)劃支持系統(tǒng)——工程造價(jià)控制策劃和規(guī)劃的新范例(可編輯)

1、畢業(yè)設(shè)計(jì)外文翻譯成本管理計(jì)劃支持系統(tǒng)工程造價(jià)控制策劃和規(guī)劃的新范例COMPASS-NEW PARADIGM FOR PROJECT COST CONTROL STRATEGY AND PLANNINGBy Makarand Hastak/ Associate Member, ASCE,Daniel WHalpin,2 Member,ASCE,and Jorge Vanegas/ Associate Member, ASCEABSTRACT: The need to remain competitive while generating profit requires management to

2、 develop innovative. cost management strategies that will allow them to distinguish and control early-on factors that might adversely. impact the cost of a projectThis paper describes a decision support system, COMPASCSost ManagementPlanning Support System for project cost control strategy and plann

3、ing. Throughout the life cycle of a project, COMPASS methodology assists managementin evaluating the potential degree of cost escalation. It also identifies attributes such as management errors, regulatory approval, and error/rework, that might be the cause for project cost escalation. Furthermore,

4、COMPASS assists managementin formulating a cost control strategy while utilizing their experience and past project performance data. The attributes identified by the cost control strategy, if controlled, would minimize the expected loss.INTRODUCTIONProjecot st scalation and cost managementare clearl

5、y two of the most important management concernsin the intensely competitive environment of the construction industryConsequently, it s very important for management to detect at an early stage of a project the actual or potential cost overruns. To remain competitive while generating profit, manageme

6、nt needs to identifyand adopt in novative cost management strategiesThese strategiesshould allow them to identify and control early on factors that might adversely impact the cost of a projectTo date, various methodologies have been developed for project cost control such as earned value system mana

7、gementexception reporting,and cost trendanalysis However, none of these methods considers at a macro level the influence of many important factors or attributes such aswaste, project management practices, change orders, and error/rework on the project costExisting methods of cost control focus on id

8、entifying and controlling line items cost components that havealready experienced a cost escalationIn other words, existing methodsof cost control relate to symptoms rather than the causeWhat is required, however, is a paradigm shiftA new method is needed that, in addition to recognizing he symptoms

9、, identifies and focuses our attention on the attributes that are a potential cause for escalation in the line items for a given projectThe new paradigmshould have the capability to analyze a given project while incorporating the past project performance data and the experienceof the project team. T

10、his analysis should identify and suggestcontrol of attributes such asmanagement errors,regulatoryapproval, and error/rework, which have a potential to instigatecost escalation in the line item estimateMoreover, it is of importance to identify and control these attributes before they influence the pr

11、oject cost.Identification of attributes that might be responsible forproject cost escalation is not sufficient in itselfWhat isequally important is to control the influence of the identified attributes on the project costThis would require developing a projectcost control strategy to either eliminat

12、e or reduce the impact of identified attributes on the line items, thereby minimizing the expected loss.Existing methods of cost control do not assist management in developing a cost control strategy to minimize the impact of all such attributes on the project cost. The optimum strategy would identi

13、fy and suggest control of a set of attributes to minimize the probable project cost escalation.To analyze and control the impact of these attributes on the project cost, it is important to collate the past project performance data available with the user firmFurthermore, thesedata should be analyzed

14、 with respect to the new project characteristics by using an appropriate analytical mediumA computerized decision support system DSS would therefore be advantageous to assist the user in developing a suitable project cost control strategyATTRIBUTE VERSUS LINE ITEMSThe tenn "attribute"as us

15、ed in the present paper does notrefer to the conventional tenn"line items." However,it pertainsto the factors that might be responsible for generating cost escalation in the line items of a project. The difference is emphasized to delineate the point of departure for this researchIn recent

16、 years, many researchers have addressed theissue of cost control by using techniques such as Monte Carlo simulation, management exception reporting, and probabilistic estimatingNonetheless, their research fothe variance in line itemsHowever, from the cost management perspective, it would be more ben

17、eficial to identify the cause of variance in the line items, which, when controlled, would minimize the overall project cost escalation.During the estimating process for a given project, we might assume a certain state for attributessuch as managementerrors, regulatoryapproval, error/rework, worker

18、morale, and crew balanceThe underlying concept of this research is that during the course of the project the assumed state of these attributes might change due to one reason or anotherThe change in state or loss ofequilibrium of an attribute might not only influence certain other attributes but also

19、 might influence the line items thatwere estimated based on the assumed state of the attribute. This, in turn, might cause a percentage escalation in the estimated project cost.An attribute is considered to be in the active state if,over thecourseof theproject,thecost orstatus of anattribute differs

20、 from what was assigned to it at the estimating stage. For example, the labor productivity obtained during the course of the project might differ from what was assumed at the es timating stageSimilarly, at the estimating stage, a nonactivestatus might be assigned to the attribute, management, or pro

21、ject team. However, there is a possibility that during the course of the projectthe management or project team might make a decision error, influencing many other attributesThis would change the nonactive status of the attribute, management, or project team,to an active stateThe probability and the

22、resulting cost impact of these events cannot be neglected.Attribute state is defined byusing a binary mode, where state 1 implies that the attribute was in active state inthat project, whereas state 0 implies otherwise. The complex in terrelationship between the attributes suggests that even a minor

23、 change in the assumed equilibrium state of anattribute has thepotential to trigger a domino effectThis effect could not only influence some other attributes but could also influence theproject costTherefore, the binary mode of representation was considered to be most appropriate for this research,

24、since any intennediate state between active and nonactive would not provide any additional infonnation.THE ATTRIBUTESFor the purpose of this research, attributes that have apotential to cause project cost escalation were identifiedIn the past, several authors have examined the impact of isolated att

25、ributes on project cost However, no projectmanagementtool is availableto account for the collective impact of all possible attributesThe attributes weredividedinto two groups, quantifiableand nonquantifiable attributes. Attributes that have a cost value associated with them in the project estimate w

26、ere defined as quantifiable attributes, e.g., total material cost, total labor cost, total equipment cost, project management cost, and total cost of the project at end of workAttributes that do not have a costvalue associated with them in the projectestimatewereThe need to differentiatedefinedas no

27、nquantifiableattributes.between quantifiable and nonquantifiable attributes is elaborated later under modeling assumptionsFIG 1 Example Influence PatternRefers to the percentage cost escalation over the estimated project costTo satisfy these requirements, a DSS such as COMPASS would be most suitable

28、MODELING ASSUMPTIONSThe interrelationships between attributes, the resulting influence pattern, and the impact of attributes on the project cost have been structured by defining the five following modeling assumptions:Assumption 1If an attribute, e.g., F refer to Fig. 1 is influenced by a set of att

29、ributes, i.e., C and D, then the individual influence of the attributes in that set on F i.e., the influence of C on F and the influence of D on F is considered to be independent, i.e.pF n CIF n D pF n C Ia:. pF n C n F n D -;- pF n D pF n C I b: pF n C n F n D pF n C X pF n D IeAssumption 2All nonq

30、uantifiable attributes are conditionally dependent on their preceding attributes, i.e., a nonquantifiable attribute can attain the active state only if at least one of its preceding attributes is in theactive state; e.g., attribute F refer to Fig. 1 can attain the active state i.e., F 1 only if at l

31、east one of its preceding attributes C or D is in the active state i.e., C 1 or D 1.However, this constraint is not applicable for quantifiable attributes, i.e., X, Y, and Z refer to Fig. I, because quantifiable attributes, apart from being influenced by their preceding attributes, are also directly

32、 related with certain line items e.g., quantifiable attributetotal materialcost would be related with materialcostassociated with various other line items, some of which might be influencedby other active attributes that would define the state of thatquantifiable attribute e.g., total material cost

33、as activeAssumption 3Only the starting attributes, i.e., A and B refer to Fig. 1, can be influenced by factors external to the system, whereas other attributes within the system can only be influenced by attributes preceding them in the influence pattern refer to Fig. 1. The system represents all of

34、 the attributes included in the influence patternAssumption 4There is a probability that, although an attribute is in the activestate, the attributes influenced by it might not get into the active state, i.e., C 1 and D 1 but F 0 refer to Fig. 1 A corollary to assumption 4 would be that the active s

35、tate probability of an attribute is a function of the independent influence of its preceding attributes, as defined in the influence pattern, e.g., pF 1 fpC 1 n F 1, pD 1 n F I. It is important to note that the accuracy of the active state probability of attributes is contingent upon the interrelati

36、onships defined in the influence pattern by the user. For example, if attribute F were influenced by a third attribute say, H in addition to C and D as defined in Fig. 1, then pF 1 fpC 1 n F 1, pD 1 n F 1, pH 1 n F I. However, since only C and D have been defined as the attributes preceding F, pF 1

37、will only reflect the influence of C and D.Assumption 5If an attribute gets into the active state, it has an independent capacity to cause a certain percentage cost escalation % CE in the estimated project cost, i.e., if an attribute gets into the active state, it might influence the attributes foll

38、owing it, and also independently cause a % CE by influencing certain line items that were estimated based on an assumed state of the attributeAll the assumptions have been carefully considered to provide an ease in computation and modeling of the complex nature of the problem.The first assumption is

39、 necessary to create a situation that would provide ease in computing the active state probability of attributes and in modeling the interrelationship between the attributes.It might be argued that in the construction context, all theattributes are interrelated under one situation or another and are

40、 thus dependent. However, it is computationally tedious and unproductive to consider the labyrinth of relationships existing between the attributes. Thus, it is imperative to define a structured and computationally manageable approach, as defined in the assumption.The second and third assumptions ar

41、e derived from1 the definition of the system defined earlier; refer to Fig. 1;2 the interrelationships between attributes established in the influence pattern;and 3 the need to create a structured environment for computing the influence of attributes on each other and also on the project costThe fou

42、rth assumption has been included to establish the fact that, although the attributes preceding a particular attribute might have attained the active state, there exists a probability that the attribute in question may not attain the active state, i.e., 1-pCIA 2: 0 refer to Fig. 1.The fifth assumptio

43、n was derived from the definition of the influence pattern and the active state of attributes; i.e., the influence pattern is a "shadow" network of attributes and these attributes are significant only when they attain the active state. This would imply that there has been a change in the s

44、tatus or value of the attribute from what was assumed at the estimating stageThis change in state of an attribute would thus directly influence the cost of certain line items that were estimatedbased on an assumed status or value of the attribute. These assumptions collectively provide a structured

45、environment for modeling the complex interrelationship between the attributes and to make the DSS more responsive to the user.THE DSS COMPASSA DSSis defined as a computer-based system for decision support, with an ability to improve the effectiveness and productivity of the decision maker by utilizi

46、ng the built-in analytical, situation modeling, and database management facilities Ghiaseddin 1987.Accordingly, COMPASwSas developed in three modules refer to Fig. 2:1 module I-to isolate pertinent information from past project performance data and to calibrate the data for a new project with respec

47、t to the project characteristics;2 module 2-to determine the probable cost influence of attributes in a new project;and 3 module 3to develop a project cost control strategy to minimize the expected loss.FRAMEWORK OF COMPASSThe accuracy of a system depends to a large extent on the validityof the inpu

48、t data provided by the user. Therefore, it is important to properly analyze past project performance data before the data are used in identifying the potential risk attributes and in developing a project cost control strategy for a new project. The DPM was developed to assist the user in this aspect

49、 and to isolate the necessary information from the available past project performance dataDPM However, since every construction project is unique, the historical data cannot be used in analyzing a new project without giving proper consideration to the newproject characteristicsThe GDM was developed

50、to take into account this important aspect and to calibrate the past project performance data as analyzed in the DPM before the data are used in analyzing a new project.The calibration is performed by soliciting subjective input from the team members with respect to the unique characteristics of the

51、 new projectrefer to Fig. 2.The PWPCE model assists the user in calculating the probability ofan attribute influencing the cost of a project and also the percentagecost escalation with respect to the estimated project cost due to thatinfluence. This model utilizes the input provided by the DPM and the GDM to calculate the expected percentage cost escalation in a new project and also the individual cost influence of attributes in that project.Theoutput of the PWPCEmodel i.e.,the individual cost influence ofattributesand their probability of influencing the