No. 2010-127

STREAMLINING DEMAND FULFILMENT CHAIN IN CONSTRUCTION PROJECTS:

THE CASE OF A PRE ENGINEERED STEEL BUILDING MANUFACTURER

By Keyvan van Roosmalen, Arjan van Weele, Jalal Ashayeri

December 2010

ISSN 0924-7815

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Streamlining Demand Fulfilment Chain in Construction Projects:

The Case of a Pre Engineered Steel Building Manufacturer

Keyvan van Roosmalen and Arjan van Weele1 Faculty of Technology Management, Technische Universiteit Eindhoven, The Netherlands

Jalal Ashayeri

Department of Econometrics and Operations Research, Tilburg University, The Netherlands

Abstract Purpose - The construction industry is known for the application of traditional production and project management methods. This paper overall aims to demonstrate that the adoption of Supply Chain Management (SCM) concepts in construction industry can lead to significant improvements of planning and control performance of construction projects.

Methodology/Approach – Multiple construction projects of a pre-engineered steel building supplier are explored using a research approach that is based on the previous literature from construction industry, Critical Chain project management and SCM concepts.

Findings – After detailed mapping of construction projects and processes, using the critical chain approach the case company’s supply chain was examined quantitatively and a solution was devised to improve its performance. The simulation studies of the new supply chain planning and control system demonstrated a productivity improvement of at least 7%,

Research Limitations/implications – The paper investigated one company and the results are simulated. Findings are being implemented in an ERP and MRPII system.

Practical implications – The results of this paper clearly verify the need for mind change among Pre Engineered and Structural Steel Building firms operating in the Middle-East. Supply chain management methods should be used to improve competitiveness.

Originality of the Paper - This paper is one of the few research works on construction projects that combines the use of SCM concepts with other classical literature on project and production management

Keywords: Construction Industry, Pre Engineered, Steel Building, Supply chain management, Planning and Control. Paper type: Case Study JEL Code: L740, L600, L610, M110

1 Corresponding author: email a.j.v.weele@tue.nl

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Introduction Across the globe the construction industry represents a large sector of the economy in terms of GDP and employment. The construction industry plays an important role in the physical and social development of countries and economic regions. It is known for a wide array of products (project) like houses, apartments, bridges, warehouses, offices, tunnels, and high ways. The different market segments in the industry (i.e. general contracting, heavy and civil engineering and functional subcontracting) all face many challenges in their daily business, due to the diverse nature of participants. The key participant within a construction project, often the general contractor, is normally specialized in one type of construction like commercial or industrial. This general contractor takes full responsibility of the project but will outsource specific portions of the project to specialized construction companies or sub contractors. This is a longstanding practice in the sector. In general, some contemporary concepts such as vendor managed inventory or lean supply have been practiced in construction industry without being called as such. However, these practices have not been examined thoroughly. The different sub contractors and/or specialized construction companies engaged in a construction project have to be selected to provide the different goods/services against the right specifications and within specific, tight time constraints. In case of complex projects like large buildings, bridges, or oil platforms, large parts of the project have to be supplied and manufactured by suppliers. This supplier may have different roles in such large projects. It could either act as a main contractor or as a manufacturer of the structure or could act as both. Within large construction projects such a main supplier is a key player since its supply is the main link for all other stakeholders in the project. Such a supplier usually deals with three key issues: supply chain management, quality management, and knowledge management (Oakland and Marosszeky, 2006). This paper studies the operational and supply chain processes of a main contractor, i.e. a Pre Engineered Steel Building (PEB) manufacturer. The company is one of the leading sellers of Pre Engineered Steel Buildings of the Middle East, located in the United Arabic Emirates (UAE). The company designs, develops, manufactures, and constructs pre-engineered steel building and polyurethane sandwich panels for one the fastest growing construction markets in the world. At time of study the company was growing over 25% annually and faced many problems in planning and controlling its customer orders throughout its supply chain. The planning activity within the company mainly focused on completing the internal processes within each department. But construction projects are reputed for their internal and external dependencies. The current way of planning has resulted in inefficient use of resources and capacities, incorrect focus on orders, and poor sales and operations planning. In this study we conducted a detailed quantitative mapping of all PEB’s processes. The results were used to develop a new planning framework, that allows the company to meet customer requirements i.e. customer completion schedules better at lower operational costs. Our suggested process redesign resulted in impressive service improvements, cost savings and efficiency gains. Our study is limited to examining internal supply chain practices of the company up to its exchange points with its immediate suppliers, customers, and subcontractors. However, in our study all types of customer orders, except claim orders, have been considered. A methodology is presented which allows construction firms to dramatically improve their customer service levels, whilst reducing their operations and supply chain costs at the same time.

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This paper is organized as follows: first PEB’s supply chain is described. Next, the approach that was adopted for investigating the current sales and operations planning is discussed. Thirdly, the method to decide the repositioning of the customer order decoupling point in the company's chain of operational processes is described and substantiated. Fourthly, the detailed implications for future planning and control activities are presented. Fifthly, the results related to the quantitative simulation and validation process of our proposed framework are summarized. Finally, an overview of our conclusions is provided. The Supply Chain Mapping of the Pre-Engineered Steel Structure Manufacturer

Given the massive demand for pre-engineered and structural steel buildings in the Middle East, customers of PEB construction firms usually are represented by either governmental institutions that are responsible for industrial development, or large firms which are seeking for additional room for housing their fast growing manufacturing and trade activities. In many cases, the orders of these customers are defined in detail through blueprints. Based upon these blueprints, the detailed engineering and construction of these buildings is carried out by the PEB manufacturer. The remainder of this paragraph addresses the case company’s (hereafter: PEB) supply chain processes. See Figure 1 for more details of this company. Figures PEB 2007 Turnover +/- 100 Million Euro per year Number of employees 700 People (400 labour) Production capacity 10,000 MT/Month Markets Asia, Africa and Middle-East Entities Production: United Arabic Emirates

Engineering: Unites Arabic Emirates and India Sales: United Arabic Emirates (2x), India, Iran, Iraq, Pakistan, Jordan, Saudi Arabia, Philippines,

Figure 1: Basic characteristics of PEB Current situation (buyer and supplier relationships) – downstream/upstream Projects enter PEB as a customer order and are processed until they are delivered to customers or constructed at the construction site. The supply chain of the company (see Figure 2) can be typified as a typical Engineer-to-order (ETO) chain as described in Van Weele (2003) since all buildings as requested by PEB’s customers are customer specific. The customer order decoupling point is located at the moment that the steel structure drawings are approved by the customer. The production process can be typified as an Assembly to Order (ATO), in which the different parts of the building are constructed out of different produced steel components. In contrast to ETO’ companies, raw materials at PEB are purchased based on forecasts due to the long lead times of raw materials in the Middle East region. In most cases standard sizes of raw material in PEB industry are required, namely steel plates and bars. Only specific customer materials and components (e.g. doors, cranes etc.) are bought based on customer orders. Hence, PEB needs to effectively manage different types of supply chains in parallel in order to meet customer requirements. As a consequence, it needs to deal with different kinds of planning logics required for the high degree of customization and outsourcing in construction industry in contrast to traditional manufacturing sectors (see Kornelius and Wamelink, 1998).

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3Prepare Approvaldrawings

4Approval bycustomer

9Shop-Loading

plan

6Make Ship & Construction

plans

7Make shop &construction

drawings

12Production

14Shipping

16Construction

2Sold Jobs

10Raw

Materials

11Released

components/Phases

13Components/

phases FG

15FG

at site

5Approveddrawings

8Shop

drawings17

CompletedJob

Engineering Activities

Operational Activities

1New order

arrival

Decoupling Point

Figure 2 Supply Chain of the PEB steel manufacturer. Development of steel structure designs The development of a building always requires several approvals (local municipality, civil construction authorities, and others) regarding the structure of the building. Once these approvals, which may take considerable time due to the multiple stakeholders involved, are provided the other companies within the overall construction project (subcontractors like foundation construction companies) can start their work at the site of the construction. Downstream Flow Clearance Signals (DFCS) PEB’s supply chain has several milestones (see Figure 2), the completion of which is dependent on external as well as internal factors. Apart from the formal approvals, other important external dependencies are represented by the actual customer payments. Payment has to occur at or in advance of different milestones along the demand fulfilment chain. The first payment is made as soon as the contract is signed. The second payment should be made by the customer before starting the first production batch, turning the status of the job order from NC (No Clearance) into PC (Production Clearance). The final payment should be received before the actual shipment of all materials, turning the job from PC to SC (Shipping Clearance). As a consequence, payments have a significant influence on the efficiency of the PEB supply chain. Planning process Manufacturing processes are planned from the Customer Order Decoupling Point (CODP) which is located at the moment when an approval drawing is returned and signed by the customer. The CODP at PEB is placed at this position due to the unpredictable arrival time of the approved drawings. Based on the returned approved drawings, the detailed shop and construction drawings are prepared according to the First in First out (FIFO) principle. The shop drawings, including Bill of Materials (BOM), are required for releasing a production order. Besides these drawings, also material availability, financial production clearance (PC), sufficient production and man-capacity are required for releasing a production order.

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Product delivery process Once production is finished, the finished goods are placed into the finished goods yard. The shipping department will check the DFCS status of the customer orders that are ready for shipping (SC) and will prioritize accordingly. When the final payment is received, the finished goods will be shipped to the customer's construction site. Process Control When reviewing the processes within the company, it appears that the actual control of processes can be divided into two parts, i.e. the control of the engineering activities and the control of the operations activities (see Figure 2). The control of engineering activities is very important because of the many revisions and variations that may occur. These revisions may include the design, but also may relate to the planning and materials schedules downstream within the PEB supply chain. The control of the operations activities starts from the moment that approval drawings have been returned. At that moment the operations department will plan for material requirements, resulting in a planning cycle with a 3 months horizon. When managing PEB's demand fulfilment chain, it is crucial to manage and plan these different internal and external factors in parallel to reduce “waste” within their processes. There are several internal as well as external factors influencing the planning process. Due to the multi-project, multi-site, and the multi-tasks nature of this business, factors like the number of components, the coordination and planning of activities of the main contractor, subcontractors or main suppliers is an extremely complicated task. In addition to these factors, the numerous uncontrollable external factors as well as the significant role of the internal DFCS, makes customer order planning a main value driver for the success of this business. Therefore it is required to have a streamlined and flexible operations planning and control process. At the moment of this research, PEB faced many problems with their current inefficient planning process. This has resulted into a high finished goods inventory compared to raw material inventory (1:1), a high number of rush orders, inefficient use of resources, a high working capital position and frequent short lead time local sourcing activities resulting in high prices for materials and services. In the next paragraph, we will propose a methodology which can help PEB to improve its operational and planning processes resulting in superior customer service. Hereafter, we will apply this methodology, resulting in a new planning process for PEB and significant productivity gains. Research Methodology: Design of Supply Chain Planning and Control Systems in Construction

Literature on improving the supply chain planning of construction industry and in particular Pre Engineered and Structural Steel Buildings manufacturers is limited. Most of the existing literature deals with either defining the roles and benefits of SCM concepts in this sector (Akintoye et al., 2000; Green et al., 2005; Hastak and Syal,, 2004; Jiang et al., 2003; Koskela, 1999; Love et al., 2004; Naim and Barlow, 2003; O’Brien, 1999; O’Brien et al., 2002; Vaidyanathan et al., 2007a; Vaidyanathan et al., 2007b; Vrijhoef, 1998; Vrijhoef and Koskela, 1999; Vrijhoef and Koskela., 2000; Vrijhoef et al., 2002), or discussing the use of ICT to enable collaboration processes in the industry (Brewer et al., 2005; Cutting-Decelle et al., 2007; Tucker et al., 2001; Turk et al., 2001;

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Xue et al., 2007) or addressing information technology based solutions for managing material delivery processes (see e.g. Ala-Risku and Kärkkäinena (2006)). Part of the literature deals with reengineering of the construction industry (Koskela and Huovila, 1997; Perši, 2007). To our knowledge only few authors address planning issues and characteristics in construction industry. Most contributions are limited to operational planning like Tserng et al. (2006), Sobotka and Czarnigowska, (2005), and Walsh et al. (2002). It is not without reason that the construction industry has not been too keen in adopting SCM concepts. An engineer-to-order (ETO) demand chain similar to the PEB-case must cope not only with competitive challenges and the complexities inherent in coordinating supply chain, engineering, and manufacturing activities. It must also coordinate customer relationships in parallel throughout the entire design, manufacturing, and construction process. This point has been cited by a few authors such as Douglas et al. (2005), Iskanius and Haapasalo (2004), Kumar and Viswanadham (2007), Sandhu and Helo (2006), Tommelein et al. (2003), and Whelton et al. (2002). Adding to this complexity, the number of components required to construct a building is at least four times larger than for assembling a car (Gann and Salter, 2000), its assembly process nature is a project-orientated business, and the location of assembling is fixed. These features limit the freedom of outsourcing, supplier selection, or even labour choice among others. This leaves construction companies in general with fewer options to standardize, routinize and focus their activities. The literature alludes to difficulties related to planning, as each construction company is always part of a larger chain, i.e. the external supply chain (Vrijhoef and Koskela, 1999). In general, in any construction projects many internal processes are dependent on external processes from other companies. This means that each step within the process cannot be managed as a separate step on its own, which is typical for the conversion view (Koskela and Huovila, 1997). Inclusion of lean concepts and a strong focus on meeting customer demands are required, which is typical for the flow and value chain view (Koskela and Huovila, 1997). Yeo and Ning (2002) argue that project planning and control practices are too limited in scope to be able to manage a construction firm's operations and supply chain processes. They therefore have proposed their critical chain approach for this purpose. We have adopted this approach to deepen our understanding and analysis. The many internal and external interdependencies and the project-based character of the construction supply chain prevent in our view the application of traditional SCM principles. Therefore, based on our past experience, we propose a unified approach that combines supply chain principles, project management techniques and classical production planning techniques. Crucial in our approach is the decision where to locate the customer order decoupling point (CODP), which is dependent on the construction firm’s specific product/market strategy. In literature on supply chain management in construction industry this topic is barely addressed. Walsh et al. (2004) do address the strategic positioning of inventory to match demand in construction projects. However, their paper does not tackle two important issues: (a) the construction firm’s market orientation, which calls for different order decoupling points for different customers and products, and (b) the capacity planning and allocation processes which require deciding on man capacity and materials requirements needed to meet project production schedules. Our proposed solution addresses these points and spans across long-, medium- and short-term planning horizons (Ashayeri and Selen, 2005)(see Figure 3). Our unified Supply Chain Planning and Control System (SCPC), see Figure 3, starts with positioning the CODP, based upon an extensive market analysis. This stage focuses on deciding the best position to separate operations performed to produce parts and components to stock, from the operations performed to make the products to order. There are several papers that discuss

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different formats of CODP. Ashayeri and Selen (2005) addressed the basic literature behind the generic CODP concept. However, two closely relevant works, which have advanced the basic CODP concepts and include the CODP literature, (Wikner and Rudberg 2005-a; Rudberg and Wikner 2004) present the essence of introducing the new two dimensional CODP in the adopted study approach. These two papers make it clear that the demand driven fulfilment chain requires both the market-based and the resource-based views to position the CODP. For the design of the demand fulfilment chain in the case study, these dimensions have to be modelled in coherence. This results in several possible positions of CODPs as was indicated earlier. A number of methodologies have been applied for determining the most appropriate CODP, such as multi-criteria ABC analysis as discussed by Flores and Whybark (1986), supply chain process productivity and process variability measurements (Ballard, 2000), and Critical Chain Analysis as suggested by Goldratt (1997).

Historical Demand

Market TrendsFuture Forecasts

Bill of MaterialInformation

Supply ChainProcess

ProductivityAssessment

Required ServiceDegree

RequiredLead Times

Multi-Criteria A/B/C AnalysisTechniques

Identify the Crucial Class of Products

CommonalityAnalysis

Process FlowAnalysis

IdentifyCODP

Shop-loadingPlanning Model

Part-SchedulingProduction Unit

Model

FeasibleSchedule

ExecutableSchedule

Determine “Optimal”Master Project Scheduleat CODP

Determine “Detailed”Schedule at Bottleneck Process

No

Yes

Determine Customer Order Decoupling Point (CODP)

Supply ChainProcess VariabilityAssessmentIdentify Critical

Path (TOC based)

Conduct the Operations Planning & Control

Order FinancialStatus (DFCS)

Shipment & ErectionPlan

Figure 3: The Study Approach adopted from Ashayeri and Selen (2005).

Having determined the CODP, the unified planning and control approach turns towards supporting optimal medium-, and short-term decisions for shop-loading and scheduling in order to streamline the demand fulfilment process. Although in some demand chains the upstream and downstream activities could be separated, in general there are dependencies between them. This is particularly relevant for PEB since a customer order release (i.e. performing the next process step) at different stages of the chain is subject to payment dates agreed upon during the order acceptance negotiations. In order to take this issue into account, only orders that meet the payment conditions are released for the “optimal” use of constraint resources. For this reason we have used constraint based resource planning as suggested by the Critical Chain concept. This concept is discussed briefly in the section on Operations Planning and Control. Literature on medium-, and short-term decisions in customized construction firms is limited but for repetitive construction projects more literature is available. Interested readers are referred to (Yang and Chang, 2005) who developed a stochastic resource-constrained scheduling for

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construction projects that repetitively had to be performed using the same resources (labour and equipment). Artigues et al. (2008) discuss the resource-constrained project scheduling problem and present an overview of models and algorithms dedicated to solving this type of problems. In the following section each of the steps to arrive at the right CODP for the PEB manufacturer are elaborated. This section is followed by an extensive discussion on how to apply the operations planning and control framework. Identify CODP for the Pre-Engineered Steel Structure Manufacturer

The customer order decoupling points determination is both a strategic and tactical issue (see Wikner and Rudberg 2005-a), requiring extensive computation as shown in Figure 3. The highlighted parts of Figure 3 are used to derive this new CODP. Appropriate and in-depth knowledge of design engineering and manufacturing resource planning are required. Here, we provide only a sample of computational analysis performed to determine this point by describing the empirical research method. To collect all necessary historical data, the planning schedules of each part of PEB’s supply chain of seven months were analyzed. We chose a time span of 8 weeks as the survey period. Within this horizon the numbers of jobs per process were about 74 (or 718 subtasks). Supply Chain Process Productivity Assessment To assess the internal supply chain productivity, a simple measure was used i.e. Planned Percentage Completed (PPC) (Ballard, 2000). The PPC is calculated as follows:

PPC = (Actual completed tasks in period t /Scheduled tasks in period t)

The key idea here is to investigate for each process activity why PPC is low and to find out the reasons for not completing all tasks that were scheduled. The analysis was carried out for PEB's main internal activities, namely 3, 7, 9-10-11, 12-13, 14 (see Figure 2). PPC for each department/process was carefully examined for a representative period of two months and the reasons for non-completion were tracked down. The results of the study are described into two parts. The first part presents the average PPC percentages of the different processes, as is shown in Figure 4. The second part (Figure 5) presents the various reasons for not being able to meet the schedule for a certain activity within a certain period.

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87.04%

66.86%

46.53% 49.93%

55.63%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

100.00%

Make approvaldraw ing (3)

Make shop andconstruction dw g

(7)

Aggregate Planning(9-10-11)

Production UnitPlanning (12-13)

Shipping (14)

Figure 4: PPC result per process during 2-months survey (process-steps of Figure 2 are shown within brackets). Figure 4 clearly indicates that the company is facing some serious problems in planning its jobs. None of the processes is achieving a reasonable level of completion like 90% of its planned schedule. Another point worth mentioning is that, if we exclude the shipping process, the completed percentage of scheduled jobs downstream is decreasing, showing a sort of Bullwhip effect (better performance closer to the customer and worse the farther away). Note that for all the measurements the plan made in week t-1 for realization in week t is used. Shipment planning is not considered within this view because its schedule is made on a daily basis. Supply Chain Process Variability Assessment The different internal and external disturbances causing process variability (PPC performance) are identified during a period of two months and presented in Figure 5. As can be seen each process has numerous sources of variability. Some significant reasons are highlighted and discussed here.

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Figure 5: Sources of process variability within the supply chain. a) Planning process (3) Within the production planning process, there are several dependencies. One of these is the availability of the shop drawings required for production. When investigating this aspect in more detail, it turned out that jobs were scheduled according to the FIFO principle. However, for

Overloaded

20%

Cust omer

Revision

20%

Incomplet e

Inf ormat ion

20%

Await ing

Clar if icat ion

40 %

Incomplete Information

9%

Unexpected

Complication

9%

Overloaded

20%Customer Revis ion

6.4%

Other

29.4%

Finished Earlier

5.9 %

1. Make Approval Drawing 2. Make Shop and construction drawing

3. Aggregate planning

Shop drawingsnot released

31.4 %

Other4.4%

No Raw M aterial20%

No payment received

21.9%

RescheduledEarlier5.4%

Previous Building phase not f inished

12.6%Site not ready

0.6%

Site not ready

7.2%

Previous Building

phase

not finished

9.1%

Rescheduled

Earlier

9.9%

No payment

received

NC-PC

5.4%

No Raw Material

30.3%

Other

33.3%

No payment

recieved

PC-SC

11.3%

Revision 3.5%

4. Production Unit Planning

Not Released

by

Planning

6.5%

Other

12.2%

No Raw Material

30.1%

No payment

received

PC-SC

5.4%

Construction

Site is not ready

9.7%

Production

not finished

18.9%

5. Shipping

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Production Planning a different scheduling method is used. Both schedules and planning paradigms need to be aligned in order to be able to create a better workflow. b) Procurement process (3, 4 and 5) The second major source of variability within the chain is the low availability of raw material. One of the reasons for the lack of raw material is the inventory management process that currently is used by PEB. The incumbent inventory management process only recognizes the consumption of raw materials during the past three months. It does not take into account the high level of variability within the supply chain due to customer due date changes. In order to cope with this variability it could be suggested to build additional safety stock. c) Payment process (3, 4 and 5) The last major source of variability is payments made by customers. Payments within construction project are often delayed. Remember that the downstream flow clearance signals (DFCS) are only triggered when the respective payment milestone is made. Within PEB, the triggering process is not always respected with the result that a project may reach a next stage when the payment of an earlier stage is not made. To be able to handle this, proper risk-assessment needs to be put into place aimed at screening customers carefully and managing customer payments more effectively. Identify Critical Path (TOC based) To understand the impact of process variability on the entire PEB manufacturer supply chain, the average lead times through the processes were calculated. These lead times were collected from the current ERP and Master tracking report within the company during a period of 6 months in which the case study was conducted. Using this information the Critical Chain and bottleneck areas have been identified (Steyn, 2000). A simple approach for this calculation is to measure the coefficient of variation, Cυ, which shows the effect of the variation on the mean. The processes, which are analyzed, were identical as during the first step in our analysis, namely 3, 7, 9-10-11, 12-13, 14 (see Figure 2). Step 4-5 of Figure 2 is also analyzed separately in this analysis since it is a separate step from a Critical chain perspective. The Critical Chain Analysis is provided in Table 1 for the fiscal study year. As a result of this analysis, the critical chain is presented in Figure 6 within a PERT diagram.

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Table 1: Times of different process steps per job in days. Critical Chain Step (see Figure 5)

Process Step(s)

Figure 1

Time (days)

σ Cυ Count Std Skewness

Std Kurtosis

Approval drawing release

3 13.90 9.199 66.15% 64 1.2711 -0.75129

Payment NC→ PC DFSC* 70.03 40.33 57.60% 69 0.960153 -0.439074 Return of Approval Drawing

4-5 12.91 11.62 90.02% 85 2.85551 0.018112

Release of Shop Drawings

6-7 32.48 12.33 32.03% 79 -0.637296 -0.801883

Release of Construction Drawings

6-7 23.84 22.58 94.75% 123 3.25284 0.0359643

Release Job to Shop 9-10-11 11.62 11.55 99.42% 21 1.75615 -.0601565 Production 12 14.90 3.57 23.98% 35 0.0942037 -0.560523 Payment PC→ SC DFSC* 6.29 4.87 77.37% 24 1.55746 0.041324 Shipment 14 2.86 2.11 73.74% 14 1.82857 0.206875 * Financial control steps

1 2 3

4

5

6

7 8

9

10 11

0

InquiryJob

Proposal

Job Acceptance

& Order Entry

Approval Drawing release

t = 13.9 ,σ = 9.2

Production ClearanceNC�PC

t = 70.0 , σ = 40.3

Return of Approval Drawing t = 12.9 σ = 11.6

Release of Shop Drawingst = 32.5, σ = 12.3

Job Planning –Release of Job to

Shop

t = 11.6 ,σ = 11.6

Shipping Clearance

PC�NC

t = 6.3 ,σ = 4.9

Productiont = 14.9 σ = 3.6

Return of Construction Drawingt = 23.8, σ = 22.6

Shipment t = 2.9, σ = 2.1

Delivery and

construction

Figure 6: A PERT look diagram of the critical chain depicted with the timings of table 3 (time, t, and σ is shown in days). Once more it can be seen that the DFCS, triggered by the payment of the customer, has a high influence on the whole project lead-time. The critical path in Figure 6 (bold line) takes 101.9 days, with a standard deviation of 42.53 days. Out of these 101.9 days, 70.1 days are due the DFCS, equal to 68.7 % of the total time. To explore this high level of variability within the process more thoroughly, in Table 2 the Cυ, both per Metric Ton (MT) as well as per job are summarized. It is common practice in the Middle East construction industry to use MT as the Key Performance Indicator throughout the company. Therefore, we have decided to also analyze timing and effect of variability per MT to understand whether and to what extent the variability is influenced by the job size.

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Table 2: Cυ per MT and per Job.

Approval drawing release

Payment NC-> PC

Return of Approval Drawing

Release of Shop

Drawings

Release of Construction

Drawings

Release Job to Shop

Production Payment PC-> SC

Shipment

Per MT

119.72% 100.00% 100.00% 71.69% 82.72% 122.39% 68.10% 80.73% 158.06%

Per Job

66.15% 57.60% 90.02% 32.03% 94.75% 99.42% 24.93% 77.37% 73.74%

Some interesting conclusions can be drawn when comparing the Cυ of the different phases per MT and per job. By looking at the data in Table 2, some columns clearly show that variability is high, irrespective of job size. The processes with the highest variability appear to have strong dependencies with the external supply chains i.e. suppliers. This high interdependency of several sources contributes to the high overall variability. Multi-criteria ABC analysis and commonality analysis One of the prerequisites for continuous flow of a customer order through the chain is availability of raw materials. To address the analysis of raw material availability, a detailed study with a 3-Dimensional ABC analysis was conducted. Here, a commonality analysis and a new inventory method were applied to decide about optimal targeted stock levels. Our analysis and suggestions for the raw material analysis resulted in an improvement of 0.122 in P1 (probability that during replenishment cycle no stock out occurs).In this manner the overall inventory (finished goods and raw materials) was reduced with 13% Our discussion shows that having a fully synchronized internal supply chain, in fact, is impossible. Hence, we need to redefine the right CODP for different market segments. Table 2 indicated that some cases actually have a high standard deviation only per MT but not per job. Although a job could be huge in size, in practice it could be very easy to manage. On the other hand, small volume jobs could be very complex and therefore difficult to manage. This would then lead to small jobs having long process times and large project short times, resulting in the major difference in processing times and thus to a high standard deviation per MT. Based upon the different CODP analyses2 we conclude that the apparent lack of coordination at the Planning department has resulted in: 1) poor PPC performance; and 2) low demand chain productivity at this stage of the chain. In essence, most of the decisions made at the planning stage influence the required resources further downstream in the manufacturing department. This is also in line with Wikner and Rudberg (2005-a), who reported on the importance of this stage in the supply chain where the ETO decisions of engineering department and MTO decisions of manufacturing department can be coordinated and improved. The poor performance at the planning stage relate to not meeting the prerequisites required at the planning department to work on a customer order: 1) the shop drawings availability, 2) due date requirements of customer, 3) payments, 4) production capacity, and 5) raw material availability. The uncertainty related to each of these factors should be reduced in order to improve PEB’s supply chain performance. In order to reduce the uncertainty i.e. improve the predictability of each of these factors, the position of the CODP should be reconsidered. Our simulations showed

2 i.e. ( 1) Supply Chain Process Productivity Assessment, 2) Supply Chain Process Variability assessment, and 3) Identifying the Critical Path, and 4) Multi-criteria ABC analysis and commonality analysis

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that when the CODP would be positioned further downstream, i.e. at the Planning Department, this would lead to significant improvements. Operations Planning and Control

Repositioning the CODP at the Planning department, would have the following consequences for PEB’s operations planning and control system (see Figure 3) 1. Master Project Schedule: Apart from deciding where to locate the new CODP point, setting up

a master schedule, following our framework, is one of the most important tasks. The master schedule is continuously fed by the different processes based upon the status of the jobs. The master project schedule should be compared with the MPS (Master Production Schedule). The main task of the MPS is to align manufacturing resources and material availability with customer orders; and look-ahead schedules are created for the jobs that should be processed in the coming periods. The look-ahead schedule has to take into account the existing variability of processes and has to build sufficient buffer times in the planning process using Critical Chain concepts (Hoel, 2000). In this manner each department is informed about an identical look-ahead schedule with the sequence of the jobs and their statuses (financial status, required raw materials, and required capacity)

2. Part Scheduling–Production Unit Model: The master project schedule is working as the aggregate goods flow control of the system. Based on the actual statuses and capacities, schedules are created at the master project schedule level. At the production unit levels, decisions regarding material control, material and work order release, capacity allocation, and other decisions have to be made. The jobs which have a fulfilled payment would be prioritized and part production planning is made according to the pull principle. The planning department is controlling the requirements at this stage with the master schedule.

3. Execute Schedule: The production schedule is executed and the shop will be controlled at the

production unit level. The work orders are released by the planning departments which controls the work order release, capacity allocation and material control (i.e. the goods flow control for production). The feedback of the shop is the status of orders being processed.

4. Measurement: In the new system variability should be continuously tracked down, to prevent repetitive errors. Measurements in MT output per department should be abolished since this parameter insufficiently reflects actual performance. Meeting actual customer requirements or backlogs (or finished goods level) are more appropriate performance measures to be used. Actually, we suggest a proper selection of the following set of indicators:

• Client satisfaction – product/service • Predictability Cost: Design / Production per order (project) • Predictability Time: Design / Production per order (project) • Profitability per order (project) • Productivity per process • Inventory (backlog) per process

The adoption of supply chain management measurement methods which are well established in sectors like automotive is considered as vital here, as is the presence of contingency measures to minimize delays.

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As applied to the Case study Applying our findings resulted from the research framework to PEB and earlier research (Ballard, 2000), we can create the new planning and control framework for PEB. Figure 7 shows the details of the new planning and control framework by including the process map and the links made from each step to the planning and control system. The previously discussed points are highlighted in the figure by tags. The focus is placed on the critical process steps within the chain.

Figure 7: New planning and control Framework 3

Summarizing, the “as-is” demand fulfilment chain characteristics of the supply chain when compared with “to-be” is adapted from more a more Push and MTS based fulfilment system to a Pull and MTO system. A simulation study, which was conducted and which is described below, demonstrates the validity of our analysis. Model Verification and Validation: A Simulation Study

The proposed supply chain planning and control concept has been implemented within an ERP system. However, before implementing our ideas for improvement, a simulation model was developed to verify and validate our proposed way of working i.e. framework. The simulation model appeared to be rather rough. However, it provided additional insight into the changes of PEB’s system behaviour. The model did include all sources of variability, except raw material shortage, which was considered to be much easier to tackle. All data used for the simulation purpose were statistically analyzed (see the last three columns of Table 1) by using histograms, Box and Whisker plots, and standardized Kurtosis and Skewness tests. To validate the other data, three concepts were used (McNeill, 1989), i.e. reliability, validity and representativeness. 3 Related to each step, the process number indicated in Figure 2 is also shown for referral purpose.

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Reliability appeared to be satisfactorily as our study approach is based on a variety of proven research methodologies within the Supply Chain research field. These methodologies can be re-applied by others in the same environment and would definitely lead to the same result. The validity is also considered to be high, since data was gathered from actual schedules or from meeting memos wherein the actual decisions were made regarding the day-to-day activities. Data regarding the lead times were extracted from the current ERP system within the company (see Table 1) and were validated using analysis of variance with the collected data (t-test and F-test). Concerning the representativeness one could argue that only one company was studied. Hence, we are limited in generalizing the results of our findings. Our simulations show that, based upon our propositions, PEB's total supply chain performance (P1 value, defined earlier) can be increased from meeting 76% of customer requirements to 88%. Furthermore, our simulation runs showed that PPC could reach 67.4%, when also other improvements to the current working method are implemented. The results of our research provide a first stepping-stone for further improving the construction industry supply chain. With the new proposed framework significant benefits can be achieved. The process variability will be more controlled since every process will be controlled at one level; the master schedule level. The new CODP will reduce the variability before the planning stage since engineering will work according to the same schedule as the Planning department. In addition, using one overall master schedule and continuous updating will result in a far better transparency of PEB’s supply chain. Since the master schedule is keeping track of every constraint, it will be able to proactively adjust the schedule based on the critical path, instead of reacting per process. As a result a more aligned demand/fulfilment chain from beginning to end will be the result. Finally, by adjusting Material Requirements Planning (MRP) methods, improved performance can be achieved throughout the different processes. In summary, our suggested planning and control framework offers many benefits, as is summarized in Table 3. Table 3: Summary benefits of new system design.

Dimension As-Is To-Be Manufacturing Strategy MTS look MTO Planning Process Push planning process Pull/Push, Constraint based planning

process Engineering and Design Push Financial based (DFCS) Push Process Variability Uncontrolled Controlled Work Effectiveness Reactive Proactive Productivity Conversion view Flow/value chain view Material Requirements Planning Single policy and without safety

stock. Policy based on 3D ABC classifications and including safety stock

Meeting Customer requirement 0.76 0.88 PPC Average (based on earliest schedule considered)

61.20% 67.38%

Discussion

Based on the work of Seuring (2008), it can be argued that this case study dealt only with one company in the construction industry. However, given its size and activities, we feel it is a representative one. The case study does not address only one stage of chain, rather is has dealt with three distinct stages, i.e. engineering and design, manufacturing, and structure construction. As indicated, our data was collected through interviews and the company’s ERP system and has

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been validated thoroughly. Furthermore, rigorous methods were adopted when developing solutions to the problems within PEB’s demand fulfilment chain. In summary, the paper contributes to literature by studying a fast growing, main supplier within the construction industry, while existing papers mostly investigate construction processes at the site level. This paper demonstrates that suppliers like PEB face identical problems as large construction firms on site. However, their complexities are even larger as they have to supply different sites. Given the scope of our study, various modern SCM principles and techniques have not been described in detail (e.g. partnering, information system, vendor managed inventory, collaborative planning). When construction suppliers have put the basic supply chain structures and mechanisms in place, as described, we are confident that they will be able to capture the future benefits of these techniques as well. Future research should be conducted to re-address the variables which we have analyzed in our model. Our approach is based on proven SCM model concepts, and the important factors within the environment of our case study. Further research could address whether more variables are required. In addition, our model is focused on the mid-term planning level, in which we detail the impact of planning practices on a construction firm’s operational processes. Since our research was limited to a single case study, our framework should be tested in other, similar companies to test its validity. Finally, our suggested framework requires intensive information availability, implying that a proper ERP system is in place. Further research, should be conducted to assess that information technology requirements can support in applying our framework successfully. Conclusions Based upon a thorough case study we proposed a new demand fulfilment framework in PEB’s supply chain. Our framework is based upon general supply chain management principles. However, it was enriched with critical chain project management principles and classical production planning techniques. The combination of these techniques can produce, as we have shown, valuable improvements. Focus should be placed on managing the whole chain, i.e. managing internal as well as external interdependencies. Dependency on external factors cannot be neglected. The uniqueness of each customer order makes the management of these external factors significantly important. In doing so, positioning of the CODP for different markets segment (Standard or Unique PEB structures) becomes a crucial strategic and tactical planning step. For our case the CODP should be placed at the planning department level and push/pull principles should be applied to manage downstream and upstream supply chain activities. These should also be used for controlling investments in raw materials. In order to successfully implement the new planning and control framework several conditions should be met. The master planner should get the authority to determine the sequence of the jobs. In order to be able to do so reliable status updates need to be given to this person on time. Other organizational changes required are related to changes in the measurement system. Here, it is important to stop using MT output per department as a key indicator, since it was found to work out detrimental to PEB's planning activities. The reason for this is that MT insufficiently reflects the complexity of a job. Planning should be primarily concerned with timings and flow of the jobs through multiple departments rather than with optimizing the workflow per department. Besides these changes, other organizational prerequisites are required for successfully implementing the proposed planning and control framework. Some of these were derived from construction management literature (Ballard, 2000). Those that have been found to be significant for the PEB case study were:

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1. Measuring and managing variability in the system continuously. The variability should not be disregarded and should be tracked down and managed continuously throughout the system. We propose to measure flexibility performance by considering the manufacturing performance and its ability to respond to demand variation.

2. Dynamic relocation of CDOP. Due to the dynamic construction market in the Middle East region and appearance of more competitors for PEB, the product portfolio and market focus of PEB can change gradually over time. This change could lead to repositioning the CODP. On the other hand, changing CODP requires significant investments (in terms of software systems, training, or organizational changes), and therefore we recommend to continuously monitor market segments (type of buildings required) and customer requirements so that when the needs are different, or the process variability is reduced, CODP repositioning can be re-evaluated.

3. Managing buffer times in the supply chain system. Due to the high variability within the supply chain, priorities and schedules are continuously changing. Re-planning should be professionally managed. To be able to do so, a time buffer management system should be maintained. In this manner, the jobs’ priorities are changed when certain jobs do not have all prerequisites in place.

4. Increasing transparency and flexibility. The new system should create a transparent supply chain to be able to cope with the high variability of the different resources. People upstream and downstream in the supply chain must know the job order status. In addition the system must enable to adjust their planning schedules and allow quick decision making.

When construction firms adopt these suggested practices, they will be able to improve their supply chain efficiency significantly. However, at the same time they also will be able to improve their customer service performance dramatically. Conceptually, to be able to do so they need to merge the insights gained from supply chain management, project management and production planning in parallel. Which explains why managing operations in construction industry is such a challenging job!

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References

Ala-Risku T. and Kärkkäinena M. (2006), “Material delivery problems in construction projects: A possible solution’, International Journal of Production Economics, Vol. 104, No.1, pp. 19-29.

Akintoye A., McIntosh G., and Fitzgerald E. (2000), “A survey of supply chain collaboration and management in the UK construction industry”, European Journal of Purchasing and Supply Management, Vol. 6, pp. 159-168

Artigues C., Demassey S., and Néron E., (2008), “Resource-Constrained Project Scheduling Models, Algorithms, Extensions and Applications”, ISTE/Wiley.

Ashayeri J. and Selen W. (2005),” An application of a unified capacity planning system”, International Journal of Operations and Production Management, Vol. 25, No. 9, pp. 917 – 937.

Ballard, G., (2000),” The Last Planner System of production control”, A thesis submitted to the Faculty of Engineering of The University of Birmingham for the degree of Doctor of Philosophy. School of Civil Engineering, Faculty of Engineering, The University of Birmingham.

Brewer G. J., Gajendran T., and Chen S.E. (2005), “Construction project supply chains and their use of ICT”, working paper w78-2005-a5-3-brewer, available at: http://itc.scix.net/cgi-bin/works/Show?w78-2005-a5-3-brewer (accessed at November 6, 2007).

Cutting-Decelle, A.F., Das, B.P., Young, R.I., Case, K., Rahimifard, S., Anumba, C.J. and Bouchlaghem, N.M. (2007), ''A Review of Approaches to Supply Chain Communications: From Manufacturing to Construction'', International Journal of IT in Construction, Vol. 12, pp. 73-102.

Douglas G., Harper, D.G. and Bernold L.E. (2005), “Success of Supplier Alliances for Capital Projects”, Journal of Construction Engineering and Management, Vol. 131, No. 9, pp. 979-985.

Flores, B.E. and Whybark, D.C. (1986), “Multiple Criteria ABC Analysis”, International Journal of Operations and Production Management, 6(3), pp. 191-195.

Gann, D.M., and Salter, A. (2000), Innovation in project-based, service-enhanced firms: the construction of complex products and systems, Research Policy, Vol. 29, No. 7-8, pp. 955-72.

Goldratt E.M. (1997),” Critical chain”. The North River Press: Great Barrington.

Green S.D., Fernie S. and Weller S. (2005), “Making sense of supply chain management: a comparative study of aerospace and construction”, Construction Management and Economics, Vol. 23, No. 6, pp. 579 – 593

Hastak, M. and Syal, M. (2004). "Building Process Optimization with Supply Chain Management in the Manufactured Housing Industry", Proceedings of the NSF-PATH Housing Research Agenda Workshop, NSF and U.S. Department of HUD, Washington DC, available at: www.pathnet.org/sp.asp?id=12201 (accessed at October 10, 2007).

Hoek, R. I. (2001), “ The Rediscovery of Postponement a literature review and directions for Research”, Journal of Operations Management, Vol. 19, pp. 161-184

Hoel K., (2000), Quantifying Buffers for Project Schedules, Production and Inventory Management Journal, Second Quarter, Vol. 40, pp. 43-47.

Hopp, W. J. and Spearman, M. L. (1996). “Factory Physics: Foundations of Manufacturing Management”, Irwin/McGraw-Hill, Boston, Massachusetts.

Iskanius P and Haapasalo H (2004),” Cornerstones of Project Oriented Business in Steel Product Industry”. In Hosni YA, Smith R and Khalil T (eds): Proceedings of 13th International Conference on Management of Technology - IAMOT-2004, International Association for

20

Management of Technology, Washington, USA, 3-7.4, available at: www.iamot.org/conference/index.php/ocs/4/paper/view/621/125 (accessed at October 10, 2007).

Jiang A., O'Brien W. and Issa R.R. (2003), “Construction Supply Chain Performance Management”, in proceedings of 4th Joint International Symposium on Information Technology in Civil Engineering, Ian Flood - Editor, November 15–16, 2003, Nashville, Tennessee, USA.

Kornelius, L. and Wamelink, J. (1998), “The virtual corporation: Learning from construction” Supply Chain Management: An International Journal, 3(4), pp. 193-202.

Koskela, L. (1999), “Management of Production in Construction: A Theoretical View”. Proceedings of the 7th Annual Conference of the International Group for Lean Construction, University of California, Berkeley, CA., pp. 241-252.

Koskela, L. and Huovila, P. (1997) “Foundations of concurrent engineering,” Paper presented at the 1st International Conference on Concurrent Engineering in Construction, July 3-4, 1997, London.

Kumar, V. and Viswanadham, N.A. (2007),” CBR Decision Support System Framework for Construction Supply Chain Risk Management”, in IEEE International Conference on Automation Science and Engineering CASE2007, Vol. 22, No. 25, pp. 980 – 985.

Love P.E.D., Irani Z. and Edwards D.J. (2004), “A seamless supply chain management model for construction”, Supply Chain Management: An International Journal, Vol. 9, No. 1, pp. 43-56.

McNeill, P. (1989), “Research Methods”, 2nd edition. Routledge, London

Naim M., and Barlow J. (2003), “An innovative supply chain strategy for customized housing”, Construction Management and Economics, Vol. 21, No. 6, pp. 593 – 602.

O’Brien W. (1999),” Construction Supply-Chain Management: A Vision for Advanced Coordination, Costing, and Control”, working paper, available at: www.ce.berkeley.edu/~tommelein/CEMworkshop/OBrien.pdf (accessed at October 10, 2007).

O’Brien W., London K., and Vrijhoef R. (2002),” Construction Supply Chain Modelling: a research review and interdisciplinary research agenda”, Proceedings IGLC-10, Aug. 2002, Gramado, Brazil, available at: www.cpgec.ufrgs.br/norie/iglc10/papers/62-O'BrienEtAl.pdf (accessed at October 10, 2007).

Oakland John S., and Marosszeky Marton (2006), Total quality in the construction supply chain, 1st edition, Butterworth Heinemann, Oxford, UK.

Perši N. (2007),” Business Process Reengineering of Complex Production Processes Using Simulation Modelling”, IIS 2007 Conference, 12– 14 September 2007, Hungary, available at: www.foi.hr/CMS_home/znan_strucni_rad/konferencije/IIS/2007/papers/T07_01.pdf (accessed at October 10, 2007).

Rudberg, M. and Wikner, J. (2004), “Mass Customization in Terms of the Customer Order Decoupling Point”, Production Planning and Control, 15(4), 445-458.

Sandhu M. and Helo P. (2006), “Supply process development for multi-project management”, International Journal of Management and Enterprise Development, Vol. 3, No. 4. pp. 376-396.

Seuring (2008)," Assessing the rigor of case study research in supply chain management, " Supply Chain Management: An International Journal, 13(2), pp. 128-137.

Sobotka A. and Czarnigowska A. (2005),” Analysis of supply chain models for planning construction project logistics”, Journal of Civil Engineering and Management, Vol. 6, No. 1, pp. 73-82.

21

Steyn H., (2000), “An Investigation into the Fundamentals of Critical Chain Project Scheduling”, International Journal of Project Management, Vol. 19, pp. 363-369.

Tommelein, I.D., Akel, N.G., and Boyers, J.C. (2003)," Capital Projects Supply Chain Management: SC Tactics of a Supplier Organization", Proc. Construction Research Congress, Honolulu, Hawaii, 19-21 March, ASCE, available at: www.ce.berkeley.edu/~tommelein/tommelein_pub.html (accessed at October 10, 2007).

Tserng P.H., Yin S.Y.L. and Li S. (2006),“ Developing a Resource Supply Chain Planning System for Construction Projects”, Journal of Construction Engineering and Management, Vol. 132, No. 4, pp. 393-407.

Tucker S.N., Mohamed S., Johnston D.R., McFallan S.L., and Hampson K.D. (2001), “Building and construction industries supply chain project (domestic)”, Report for Department of Industry, Science and Resources, available at: www.industry.gov.au/assets/documents/itrinternet/BC-SCMReport.pdf (accessed at October 10, 2007)

Turk, Ž., Bloomfiled, D., Amor, R., and Cerovšek, T. (2001), “Information services to enable European construction enterprises: The I-SEEC project: , E-work and E-commerce Conference, Venice, Italy, September 2001. ISBN 1 58603 205 4, IOS PRESS. pp. 937-943.

Vaidyanathan K. and Howell G. (2007a), “Construction supply chain maturity model - conceptual framework, maturity model”, IGLC 2007, available at: www.iglc.net/conferences/2007 (accessed at October 10, 2007).

Vaidyanathan K., Howell G. (2007b),” Construction supply chain maturity model - conceptual framework”, Proceedings IGLC 15, Aug. 2007, Michigan, USA, available at: www.iglc.net/conferences/2007/folder.2007-06-29.2095743756 (accessed at 10 October 2007).

Vrijhoef, R. (1998),” Co-makership in Construction: Towards Construction Supply Chain Management”, Thesis of Graduate Studies Delft University of Technology/VTT Building Technology, Espoo.

Vrijhoef, R. and Koskela, L. (1999). “Roles of supply chain management in construction” Proc. 7th Annual Conf. of the Int. Group for Lean Constr., Berkeley, 26-27 July 1999. pp. 133-146.

Vrijhoef, R., Cuperus, Y., and Voordijk, H. (2002),” Exploring the connection between open building and lean construction: defining a postponement strategy for supply chain management”, In Proceedings 10th IGLC Conference, edited by Carlos Formoso. UFRGS, Porto Alegr, Brazil.

Vrijhoef, R., Koskela, L., (2000),” The four roles of supply chain management in construction”, European Journal of Purchasing and Supply Management, Vol. 6, pp. 169–178.

Walsh, K.D., Hershauer, J.C., Tommelein, I.D., and Walsh, T.A. (2004), "Strategic Positioning of Inventory to Match Demand in a Capital Projects Supply Chain", Journal of Construction. Engineering and Management, Vol. 130, No. 6, pp. 818-826.

Walsh, K.D., Hershauer, J.C., Walsh, T.A., Tommelein, I.D., and Sawhney, A. (2002), "Lead Time Reduction via Pre-Positioning of Inventory in an Industrial Construction Supply Chain." Proc. Winter Simulation Conference (WSC2002), December 8-11, San Diego, CA, pp. 1737-1744.

Weele van A.J. (2003),”Purchasing and Supply Chain Management – Analysis, Planning and Practice”, 3rd edition, Thomson Learning, Padstow, Cornwall.

Whelton, M., Ballard, G., and Tommelein, I.D. (2002), "A Knowledge Management Framework for Project Definition", ITcon, Special Issue ICT for Knowledge Management in Construction, Vol. 7, pp. 197-212.

22

Wikner, J and Rudberg, M. (2005-a), “Integrating Production and Engineering Perspectives on the Customer Order Decoupling Point“, International Journal of Operations and Production Management, 25(7), pp. 623-641.

Wikner, J. and Rudberg, M. (2005-b), “Introducing a Customer Order Decoupling Point in Logistics Decision-Making”, International Journal of Logistics: Research and Applications, 8(3), pp. 211-224.

Xue X., Wang Y., Shen Q., and Yu Y. (2007),“ Coordination mechanisms for construction supply chain management in the Internet environment”, International Journal of Project Management, Vol. 25, pp. 150–157.

Yang I.T., and Chang C.Y., (2005), “Stochastic resource-constrained scheduling for repetitive construction projects with uncertain supply of resources and funding”, International Journal of Project Management, Volume 23, Issue 7, pp. 546-553.

Yeo K. T. and Ning J. H. (2002), “Integrating supply chain and critical chain concepts in engineer-procure-construct (EPC) projects”, International Journal of Project Management, Volume 20, Issue 4, pp. 253-262