W22_RM_Equipment Factored Cost Estimates

1. Problem Recognition

The increasing demand of LPG Product in a new province in Borneo Island has made the management planned to build a New LPG Storage Facilities in the province. Since the investment decisions should be made in a short time, Management asked the estimator to estimate  the investment cost of this facilities based on the limited time and data available. Management stated that the estimation will be used to conduct a feasibility study.

2. Identify the Feasible Alternative

Based on the following matrix [1], the estimator should create a class 4 estimate to meet the management requirement that the estimation purpose is to study or feasibility.

Table 1. Cost Estimate Classification Matrix

In order to prepare a class 4 estimates, the Author then prepare the estimation requirement check list as follow [2]:

Table 2. Estimate Input Checklist for Class 4 Estimate

 

3. Development of the Outcome for Alternative

After selecting the estimation class, the Author then select an estimation method to produce the estimates. Based on the table 1 above, the methodology suggested to produce a class 4 estimates is : Equipment Factored or Parametric Models.

In this case, the Author will use Happel’s Method [3]. Happel estimated purchase cost for all pieces of equipment (material), labor needed for installation using factors for each class of equipment, extra material and labor for piping, insulation etc. from ratios relative to sum of material and added installed cost of special equipment, overhead, engineering fees,and contingency.

The Happel’s Method can be described as follow:

Table 3. Happel’s Method: Table 1

Table 4: Happel’s Method : Table 2

Table 5: Happel’s Method: Table 3

 

4. Selection of Criteria

The estimation result should meet the management desired expected accuracy at the end of the project actual cost generated.

5. Analysis and Comparison of the Alternative

The Author has collected the estimate data input required (material data) in the calculation by using Happels Method as follow:

Table 6. Input Data for Happel’s Method

The estimation result calculated by using Happel’s Mehod as follow:

Table 7. Estimation Result

 

6. Selection of the Preferred Alternative

Based on the estimation result in Table 7, the Author then proposed a class 4 estimate with expected accuracy -30% to 50%  to the Management with the total investment cost is $ 5.636.407. The total investment cost include all of the construction cost plus overhead, engineering fees, and contingency.

7. Performance Monitoring and Post-Evaluation Results

The class 4 estimates purpose is only for the study or feasibility. If the management approve the FID (Final Investment Decision),  the Estimators then should complete the required project scope so that the level 2 or 3 estimate can be produced for bidding process.

References:

1. Christensen, P.et.al.(2011). AACE International Recommended Practice No. 18R-97 Cost Estimate Classification System – As Applied in Engineering, Procurement, and Construction for The Process Industry. United States of America: AACE International.
2. Ibid 1
3. Prasad, Rashmi. et.al. (2011). AACE International Recommended Practice No. 59R-10 Development of Factored Cost Estimates- As Applied in Engineering, Procurement, and Construction for The Process Industry. United States of America: AACE International.
4. Amos, S. J. (2012). Skills & Knowledge of Cost Engineering: A Continuing Project of the AACE International Education Board (5th ed.). Section 2, Chapter 9. Morgantown, WV: AACE International.

W21_RM_Benchmark of Cost Estimate Process

1. Problem Recognition

In this blog posting, the Author will conduct a benchmark analysis related to the cost estimating process in Indonesia national oil & gas company compared to another standard. In this case, the Author uses GAO Cost Estimates and Assessment Guide as a comparison standard.

2. Identify the Feasible Alternative

This benchmark will produce a recommendation to the Management related to the estimating process in the company with the following possible recommendation:

1. There is no need to improve: The existing process is meet the GAO Cost Estimates and Assessment Guide.
2. Need to improve and can be applied: The existing process should be improved to meet the requirement of GAO Cost Estimates and Assessment Guide, and implementation of GAO Guide can be applied easily.
3. Need to improve and can not be applied easily: The existing process should be improved to meet the requirement of GAO Cost Estimates and Assessment Guide, and implementation of GAO Guide can not be applied easily.

 

3. Development of the Outcome for Alternative

GAO Cost Estimates and Assessment Guide produce a best practice called The Cost Estimating Process. These best practices represent an overall process of established, repeatable methods that result in high-quality cost estimates that are comprehensive and accurate and that can be easily and clearly traced, replicated, and updated.

 

Figure 1. GAO Estimating Process [1]

There are four sub process based on these best practices:

1. Initiation and Research
2. Assesment
3. Analysis
4. Presentation

 

4. Selection of Criteria

The missing steps from the existing process in estimating compared to GAO Guide will get noticed and purposed to improve.

5. Analysis and Comparison of the Alternative

The following table shows the missing steps of existing process compared to GAO Guide in estimating:

Table 1. GAO Steps Checklist on Existing Process

The table above shows that the company should  improve the following important steps in cost estimation process:

• The company should conduct a sensitivity analysis in the estimation process.
• The company should conduct a risk and uncertainty analysis.
• The company should conduct postmortem and lesson learned for each estimation result.

 

6. Selection of the Preferred Alternative

To help figuring out the implementation of GAO Guide in the company, the Author uses Force Field Analysis as follow [2]:

Figure 2. Force Field Analysis

The final decisions in this benchmark is propose a suggestion to management to implement the missing process compared to the GAO Guide, even though it is not easy process.

7. Performance Monitoring and Post-Evaluation Results

To obtain an optimum result of implementing the GAO estimating guide, the company should spent more resources (budget and man hours) to conduct a comprehensive training. Top management should support the implementation because it will interfere with the existing process in the company.

 

References:

1. United States Government Accountability Office, GAO. (2009). GAO Cost Estimating and Assessment Guide GAO-09-3SP. Washington DC, United States: Richey, K., Echard, J., Cha, C., Borecki, G., Chaplain, C., Hung, R., Kelly, J., Kingsbury, N., Phillips, C., Pickett, P., Powner, D., Rhodes, K., Vodraska, A.
2. Wells, Stephen. (2006), Force Field Analysis Mini-Tutorial Quality Management, Retrieved from http://www.freequality.org/documents/knowledge/Mini-Tutorial.pdf, web 12 March 2013
3. Permana, Arif. (2013). W16_APE_Comparison Cost Estimate Process. Retrieved from: https://simatupangaace2014.wordpress.com/2013/11/12/w16_ape_comparison-cost-estimate-process/

W20_RM_Estimate Preparation Effort For a Bid

1. Problem Recognition

In a bid process, generally, after bidder’s conference the contractors will submit the proposals to the owner in a specific time agreed by both parties. In this blog posting, the Author will conduct the analysis related to time and cost needed to prepare the appropriate estimation by the contractors in a bid process for the process industries.

The results of time to prepare an estimation during a bidding, then will be compared to the existing company regulation stated that “bidder should submit their bidding proposal 3 to 7 working days in a normal project”.

The Author will use the following project value classification used in Oil & Gas company:

Table 1. Project Value Classification

2. Identify the Feasible Alternative

The following matrix provide the cost estimate classification for the Process Industries [1]:

Table 2. Cost Estimate Classification System for Process Industries

3. Development of the Outcome for Alternative

Based on the above matrix, cost estimates can be described as follow [2]:

• Class 5 estimates are generally prepared base on very limited information.
• Class 4 estimates are typically used for project screening, determination of feasibility, concept evaluation, and preliminary budget approval.
• Class 3 estimates are used as the project budget until replaced by more detailed estimates.
• Class 2 estimates are often used as the “bid” estimate to establish contract value for contractors.
• Class 1 estimates are typically prepared to form a current control estimate to be used as the final control baseline.

 

4. Selection of Criteria

In bidding process, the contractor will use Class 2 estimate in their proposal. Based on the Class 2 estimates, the preparation effort ranges from 0,02% to 0,1% of project cost.

5. Analysis and Comparison of the Alternative

To get the preparation effort (cost and time) for the project, the Author then using some external data such as Rate for cost estimator and Assumption of working hours a day. In this case, Rate for the cost estimator is US $ 29,03 / hour and 8 hours of work  per day. [3]

The following table describe the preparation effort based on the project value classification in the company:

Table 3. Bid Estimation Preparation Effort

• (* Days) = 85% productivity rate for the cost estimator
  

 

6. Selection of the Preferred Alternative

From table 3, the preparation effort to prepare the project estimate for instance a 5 million USD project  is range from 5 days to 22 days and 6 to 26 days for 85% productivity.

Based on the company regulations, contractor should submit their bidding proposal 3 to 7 working days in a normal project. In this case study, the Author assumed that the 5 million USD as normal project since most of the company’s project range in this value.

Table 4. Estimation Preparation Effort: Company vs AACE RP

Based on the comparison, the company should revised their bidding rule so that the bidder have more time to prepare their estimation. The longer time to produce an estimation, the higher quality of the estimates is and minimize the possible change order during the project execution.

By using the range from 5 days to 22 days, it will accommodate the  variation of project size, project complexity, estimator skills and knowledge, and on the availability of appropriate estimating cost data and tools.

7. Performance Monitoring and Post-Evaluation Results

The implementation of this analysis, especially for the contractor is that the contractor should monitor their actual spent during estimating preparation not exceed the budget range and time allowance set by the owner during bidding process.

References:

1. Amos, S. J. (2012). Skills & Knowledge of Cost Engineering: A Continuing Project of the AACE International Education Board (5th ed.). Section 2, Chapter 9. Morgantown, WV: AACE International.
2. Wibowo, Gideon. (2014). W8_GW_ Costs to Prepare a Bid for a Contractor. Retrieved from:  https://kristalaace2014.wordpress.com/2014/04/16/w8_gw_-costs-to-prepare-a-bid-for-a-contractor/
3. Occupational Employment Handbook. (2016, May). Retrieved from: Bureau of Labor Statistics: http://www.bls.gov/ooh/business-and-financial/cost-estimators.htm

W19_RM_Defender or Challenger

1. Problem Recognition

One of our Fuel Terminal is still using analog filling system, which has been used since 20 years ago. The management plan to replace the old technology with the newer digital based technology, so that the maintenance cost can be reduced.

2. Identify the Feasible Alternative

There are two possible alternatives:

1. Remain using the old analog filling system, since this technology can be used at least for the next 5 years (based on the expert assesment)
2. Replace it with the new digital based technology.

 

3. Development of the Outcome for Alternative

To conduct the economic analysis of the alternatives, the author use the MARR obtained from the previous blog posting, that is 17,44%. [1]

 

Table 1. Summary Information of Both Alternatives

After tax cash flow (ATCF) for both alternatives are shown in the following tables:

Table 2. ATCF for Existing System (Defender)

Table 3. ATCF of New Digital System (Challenger)

4. Selection of Criteria

The EUAC will be used as selection criteria, since the useful life for both alternatives is different.

5. Analysis and Comparison of the Alternative

From table 2 and 3, because EUAC defender is less than Challenger, so that the analog filling system should be kept at least for 5 years.

6. Selection of the Preferred Alternative

Since Management criteria is based on the financial analysis of the alternatives, the existing analog filling system with the lowest EUAC (equivalent uniform annual cost) is the preferred choice.

7. Performance Monitoring and Post-Evaluation Results

Since the defender selected as the preferred choice, the management should conduct a strict control and monitoring of the existing system performance so that the maintenance cost should not exceed the original assumption value.

References:

1. Milza, Rico. (2016). W4_RM_Project Economic Sensitivity Analysis. Retrieved from: https://goldenaace2015.wordpress.com/2016/01/05/w4_rm_project-economic-sensitivity-analysis/
2. Wain, Yosep Asro. (2014). W8.1_YAW_Defender or Challenger?. Retrieved from:https://kristalaace2014.wordpress.com/2014/04/16/w8-1_yaw_defender-or-challenger/
3. Sullivan, W.G., Wicks, E. M., Koelling, C. P. (2012). Engineering Economy , Chapter 9, page 379 to 418. Prentice Hall. Fifteenth Edition

W18_RM_Comparison of Depreciation Methods

1. Problem Recognition

A downstream oil & gas  company in the US plan to purchase a centrifugal pump for transferring white oil from storage tank to filling shed. The company purchase the pump for US$ 800.000. The asset will used for 16 years, and the SV at the end of the useful life is expected US$ 16.000.

In this blog posting, the Author wants to know the best depreciation method for the company that could reduce the company’s income taxes in the early years. Then, in the next blog posting, the Author will conduct an analysis related to the relationship of depreciation and income taxes.

2. Identify the Feasible Alternative

Based on the problem, the Author identify that there are five feasible alternatives [1]:

• Option 1: the Straight Line (SL) Method
• Option 2: Declining-Balance (DB) Method
• Option 3: DB with Switchover to SL Depreciation
• Option 4: Sum of the Year Digits (SYD) Method
• Option 5: Modified Accelerated Cost Recovery System (MARCS)

 

3. Development of the Outcome for Alternative

Option 1: SL Method

This method assumes that a constant amount is depreciated each year over the useful life of the asset.

dk = (800.000 – 16.000) / 16 Years,  for k = 1 to 16 ;

EOY = End of Year k

d k  = depreciation amount in year k

BV k = Book Value in Year k

Table 1. Straight Line Method

 

Option 2: DB Method using 200% DB Equations

DB Method assumes that the annual cost of depreciation is a fixed percentage of the BV at the beginning of the year.

Table 2. Declining Balance Method

 

Option 3: DB with Switch over to SL Depreciation

DB with Switch over to SL Depreciation assumes that the DB Method never reaches a BV of zero; it is permissible to switch from DB to the SL method so that an asset’s BV will be zero (or some other determined amount such as its SV at year k).

Table 3. DB with Switch Over to SL

 

Option 4: Sum of the Year Digits (SYD) Method

SYD methods assumes that assets are generally more productive when they are new and their productivity decreases as they become old.

Table 4. SYD Method

 

Option 5: Modified Accelerated Cost Recovery System (MARCS)

MACRS is unique to the United States Tax Code. Depreciation is based on original asset cost, asset class, asset recovery period, and asset placed in service. Asset classes are differentiated depending on asset type. Depreciation rates are set by percentages allowed under the U.S. Tax Code.

Based on the MARCS Class Lives and Recovery Periods from IRS Publication 946, Tables B-1 and B-2 2006, the equipment categorized in asset class 13.3 Petroleum refining, class life 16 years and GDS 10 years.

Table 5. MARCS Method

4. Selection of Criteria

Since the company is planning to expand its business, the company will choose the depreciation method that could reduce the company’s income taxes in the early years.

5. Analysis and Comparison of the Alternative

Table 6. Comparison of depreciation Amount each year

Table 6 shows that the MACRS Method results in a larger share of the depreciation being charged during the earlier years of the asset’s life than the Declining Balance Method and the Sum of Years Digit Method. The Straight Line Method is neither accelerated nor decelerated and draws a linear line.

6. Selection of the Preferred Alternative

Figure 1. BV Comparison for selected method of Depreciation

A company’s depreciation expense reduces the amount of taxable earnings used to calculate taxes and reduces the amount of taxes owed. The larger the depreciation expense, the lower the taxable income and the lower a company’s tax payments owed. [2]

The largest depreciation expense in early years generated from MARCS method, hence this method will generate the lower taxable income for the company in early years.

7. Performance Monitoring and Post-Evaluation Results

MACRS is unique to the United States Tax Code. The application of this method depends on the location of the company itself. If the company’s business located outside of the US, for example in Indonesia, the depreciation method will exclude the MARCS from the analysis and use the acceptable depreciation method based on the tax regulation in Indonesia.

References

1. Sullivan, W.G., Wicks, E. M., & Koelling, C. P. (2011). Engineering Economy, pp. 289 – 308
2. Investopedia. (2016). What is the tax impact of calculating depreciation?. Retrieved from: http://www.investopedia.com/ask/answers/031815/what-tax-impact-calculating-depreciation.asp
3. Nurani, E.D. (2016). W7.0_EDN_Comparison of Depreciation Methods. Retrieved from: https://goldenaace2015.wordpress.com/2016/02/26/w7-0_edn_comparison-of-depreciation-methods-2/

W11.1_IP_Crashing The Network Product Oil Tanker 3500 DWT

1. Problem Recognition, Definition and Evaluation

Base On Blog 10, Project Development Progress Product Oil Tanker DWT 3500 declined between Planing Vs Actual. Management wants to know what the optimum time to complete the project by compressing time and how much the total cost of the project.

Table 1. Ship Building Data Project

2. Development of the Feasible Alternatives

One strategy to accelerate the project schedule is crashing. However, crashing has impact on cost. Therefore the simulation of crashing of duration corresponding to increasing cost will be evaluated.

3. Development of the Outcomes for Each Alternative

Based on developing network the critical path is ACDGHI with original duration is 132 weeks.

4. Selection of a Criterion

The optimum time duration for the project will be selected.

5. Analysis and Comparison of The Alternatives

Shortening activities not on the critical path is wasted expense, therefore the author will do shortened to accomplish a reduction of the total project duration at critical path only.

Result of crashing mentioned at cpm below.

Prioritize critical path activities, with lowest cost duration reduction first:

The initial project duration is 132 week and the critical path is ACDGHI, so that the Author should reduce the lowest cost slope activity within the critical path.

The lowest cost duration reduction between activities ACDGHI is:

(A = 8.000 ; C = 85.714; D= 100.000; G=30.000; H=35.000 , I=35.000)

The minimum cost is crashing activity A with costs 8.000 per week. After crashing the activity A by 1 week to 5 week, there is no effect in the project critical path. Since the maximum crashing time for activity A is 5 week, then the Author should identify the other activity to crash.

(A = 8.000 ; C = 85.714; D= 100.000; G=30.000; H=35.000 , I=35.000)

The minimum cost is crashing activity G with costs 30.000 per week. After crashing the activity G by 1 week, there is no effect in the project critical path. Since the maximum crashing time for activity G is 1 week, then the Author should identify the other activity to crash.

(A = 8.000 ; C = 85.714; D= 100.000; G=30.000; H=35.000 , I=35.000)

The minimum cost is crashing activity H with costs 35.000 per week. After crashing the activity H by 1 week to 2 week, there is no effect in the project critical path. Since the maximum crashing time for activity H is 2 week, then the Author should identify the other activity to crash.

(A = 8.000 ; C = 85.714; D= 100.000; G=30.000; H=35.000 , I=35.000)

The minimum cost is crashing activity I with costs 35.000 per week. After crashing the activity I by 1 week to 2 week, there is no effect in the project critical path. Since the maximum crashing time for activity I is 2 week, then the Author should identify the other activity to crash.

(A = 8.000 ; C = 85.714; D= 100.000; G=30.000; H=35.000 , I=35.000)

The minimum cost is crashing activity C with costs 85.714 per week. After crashing the activity C by 1 week to 7 week, there is no effect in the project critical path. Since the maximum crashing time for activity C is 7 week, then the Author should identify the other activity to crash.

(A = 8.000 ; C = 85.714; D= 100.000; G=30.000; H=35.000 , I=35.000)

The minimum cost is crashing activity D with costs 100.000 per week. After crashing the activity D by 1 week to 3 week, there is no effect in the project critical path. Since the maximum crashing time for activity D is 3 week, then the Author should identify the other activity to crash.

After all activities on the critical path has reach its maximum time for crashing and the critical path is remain the same (fully crashed), then the crashing has reach the minimum possible duration of the project.

The iteration process for the crashing available in the following table:

In those the option of crashing and increasing cost depicted to graph show below:

6. Selection of Preferred Alternatives

 According to that result; crashing can show to management the trade of between speed up duration and cost increase, there are three points with same crash duration but with different cost, one point is minimum cost which is crashing just at critical path another is crashing in all activity. If main concern the management in optimum time, the author recommended to put the crashing at critical path with minimum cost.The optimum total project duration can be reduced to 20 weeks at a total cost of USD 13.180.000,-

7. Performance Monitoring & Post Evaluation of Result

Crashing can compress the Project duration till get minimum duration, however in some cases don’t’ only just increase cost but also can increase the critical path. Therefore, additional attention of critical path should one of the management to manage well.

8. Reference:

1. Humphreys, C, G (2014), Project Management Using Earned Value 3rdEdition, Chapter 11, Schedule Acceleration Techniques. Orange, CA: Humphreys & Assoc.
2. Darwito, Rikky (2015, August). W14_RD_ Project Crashing, Garuda AACE 2014. Retrieved from https://garudaaace2015.wordpress.com/2015/07/05/w14-rd_-project-crashing/
3. Hadi, Eyus (2015, August). W23_EY_Project Schedule Acceleration Using Network Crashing, Garuda AACE 2014. Retrieved from https://garudaaace2015.wordpress.com/2015/07/05/w14-rd_-project-crashing/
4. Milza, Rico. (2016). W16_RM_Project Crashing. Retrieved from: https://goldenaace2015.wordpress.com/2016/04/23/w15_rm_project-schedule-contingency-2/

 

 

 

 

W17_RM_Measuring Time Sensitivity: Critical Index

1.    Problem Definition

Previously, the Author has conducted schedule contingency for the Jetty Facilities Project [1].  Based on the results, schedule contingency for this project is 8 days which generated from the Monte Carlo simulation using Triangular Distribution for the critical path (A>B>H>J) duration.

In this blog posting, the Author will conduct a schedule sensitivity analysis for the project, which involved all activities on the project to asses the probability of each activity will remain lies on the critical path (also known as Critical Index).

2.    Identify the Feasible Alternative.

Based on the following network diagram, there are 9 (nine) possible path to become the critical path, as follow:

Figure 1. Project Network Diagram

Table 1. Project Path

3.   Development of the Outcome for Alternative.

The baseline schedule has a planned duration PD = 285 days and the critical path is equal to the activity sequence A>B>H>J. However, the baseline schedule is only an estimate of the real project duration and hence, the real project duration and the critical path might differ from the baseline schedule estimates.

Following is the three point duration estimates of the schedule, based on the historical data of PM Division:

Table 2. Three Point Estimates of Activity Duration

To conduct a simulation for the schedule, the Author will use these following software: Ms Project as the basis of the project schedule, @ Risk as the simulation engine, and Ms Excel as the platform for the @risk. Steps to do the simulation as follow:

Set up the baseline schedule in Ms Project

Figure 2. Baseline Schedule in Ms Project

Export the baseline project from Ms Project to Excel using @Risk

Figure 3. Project Schedule Using @Risk

Insert Three Point Estimate Model

Define the model parameter (Min Duration, Most Likely Duration, Max Duration) in @Risk based on the data on Table 2.

Run Simulation

In this case, the Author use 1.000 iterations for the model.

Generate the Results

Figure 4. Simulation Results

4.    Selection of Criteria.

The risk management system indicates that the points of risk are the greatest when [2]:

1. There is more risk on the converging path.
2. The CPM duration estimates are more aggressive
3. There is little flexibility or margin error because float has been used in the project.

 

5.    Analysis and Comparison of the Alternative.

Based on the simulation results in figure 4, following activities has 100% critical index: A, B, J. Meanwhile, activity H Critical Index is 92,1 and Activity J Critical Index is 7,9%.

Figure 5. Critical Index

The above result means that during 1.000 iterations of the schedule simulation, activity A, B, and J always in the critical path. Activity H 921 occurrences in the critical path, and Activity I 79 occurrences in the critical path.

Path convergence is a relationship in which a schedule activity has more than one predecessor. If an activity has more predecessor, the attention to that activity should be more intense because it may get delayed since it has so many dependencies.

Based on the above project schedule network in the figure 1, activity G and J have more predecessor than other activity. Based on the simulation, activity J always in the critical path. But, activity G never been in the critical path because activity G has more free float (30 days) than the activity worst case scenario from 30 days to 45 days (15 days delayed). Free Float is the amount of time that an activity can be delayed without delaying the early start date of any successor activity.

6.    Selection of the Preferred Alternative.

The project manager should pay more attentions to activity A, B, H, J, and I since those activities occur in the critical path during simulations. The actual project duration might be different from the historical data of previous project, so that the project manager also needs to pay more attentions to activity G and J because these activity has more predecessor than others, and have a higher probability for delay since it has so many dependencies.

7.    Performance Monitoring and the Post Evaluation of Result.

It is necessary to conduct strict schedule monitoring during implementation of the Project, especially for the highest risk path.

 

References:

1. Milza, Rico. (2016). W15_RM_Project Schedule Contingency (2). Retrieved from: https://goldenaace2015.wordpress.com/2016/04/23/w15_rm_project-schedule-contingency-2/
2. Humphreys, G.C. (2011). Project Management Using Earned Value, Chapter 11, Second Edition, Humphreys & Associates, Management Consultants.
3. Vanhoucke, Mario. (2011). Measuring time sensitivity in a project: The criticality index. Retrieved from: http://www.pmknowledgecenter.com/node/136

 

 

W16_RM_Project Crashing: Jetty Facilities

1.    Problem Definition

Downstream Oil & Gas Business Unit has a Fuel Terminal in East Indonesia. This fuel terminal is the one and only fuel terminal operating in the island. There are 2 (two) Jetties in this Fuel Terminal: Jetty A with 3.500 DWT capacity and Jetty B with 6.500 DWT capacity.

Recently, Jetty B with capacity of 6.500 DWT accidentally hit by one of the supply tanker and cause a permanent damaged, so that the fuel terminal now operating with a single jetty with capacity of 3.500 DWT. Because the management can not accept the fuel shortage for the island, they decided to run a contingency plan to operate a ship to ship cargo transfer with costs US $ 5.000 per day, while the new Jetty C with capacity 6.500 DWT being build with project duration 285 days.

By considering the lost opportunity cost of US $ 5.000 per day, the management wants to analyze the options for accelerating the Jetty C Project as soon as possible to operate, so that the Fuel Terminal operate normally without ship to ship operation.

2.    Identify the Feasible Alternative.

One strategy to accelerate the project schedule is crashing. However, crashing has an impact on cost. Therefore, the simulation of crashing of duration corresponding to increasing cost will be evaluated.

There are seven-step process to conduct a schedule crashing [1]:

1. Compute the network critical path
2. Establish the objective total duration
3. Identify the crash time/cost for each activity selected for compression
4. Prioritize critical path activities, with lowest cost duration reduction first
5. Invoke the lowest cost alternative by shortening that activity and comparing the revised project duration with the objective duration
6. Recheck the critical path(s)
7. Continue steps 5 and 6 until the objective is reached of a critical path becomes “fully crashed”

 

3.   Development of the Outcome for Alternative.

Network critical path

Based on the previous blog, the Author has conducted a network analysis for the project and the project duration as well as critical path as follow:

Figure 1. Project Network Diagram

Based on the network diagram above, the project planned to finish in 285 days and the critical path is A B H J

Objective total duration

The management wants the project finished as soon as possible to minimize the ship to ship operation with costs US$ 5.000 per day. The total cost for crashing the project should not exceed the total cost to operate the ship to ship within the total days saved.

Crash time/cost for each activity selected for compression

The company PM Division then negotiate with the contractor and has agreed with the following time/cost for crashing:

Table 1. Project Time/Cost for Crashing

Prioritize critical path activities, with lowest cost duration reduction first

The initial project duration is 285 days and the critical path is A B H J, so that the Author should reduce the lowest cost slope activity within the critical path.

The lowest cost duration reduction between activities A B H  J is:

(A = 1500 ; B = 5000; H= 1333; J=6.000 )

The minimum cost is crashing activity H with costs 1333 per day. After crashing the activity H by 1 day to 15 days, there is no effect in the project critical path. Since the maximum crashing time for activity H is 15 day, then the Author should identify the other activity to crash.

After crashing activity H by 15 days, the critical path changed and the critical path now is A B H J and A B I J, as follow:

Figure 2. Project Network (H Crashed 15 Days)

The lowest cost duration reduction between activities A B H  J and A B I J is:

(A = 1500 ; B = 5000; H= 1333; J=6.000;  I=Can not be crashed)

The minimum cost for possible activity to crash is Activity A with costs 1500 per day. After crashing the activity A by 1 day to 10 days, there is no effect in the project critical path. Since the maximum crashing time for activity A is 10 days, then the Author should identify the other activity to crash.

(A = 1500 ; B = 5000; H= 1333; J=6.000;  I=Can not be crashed)

The minimum cost for possible activity to crash is Activity B with costs 5000 per day. After crashing the activity B by 1 day to 20 days, there is no effect in the project critical path. Since the maximum crashing time for activity B is 20 days, then the Author should identify the other activity to crash.

(A = 1500 ; B = 5000; H= 1333; J=6.000;  I=Can not be crashed)

The minimum cost for possible activity to crash is Activity J with costs 6000 per day. After crashing the activity J by 1 day to 5 days, there is no effect in the project critical path. Since the maximum crashing time for activity J is 5 days, then the Author should identify the other activity to crash.

After all activities on the critical path has reach its maximum time for crashing and the critical path is remain the same (fully crashed), then the crashing has reach the minimum possible duration of the project.

The iteration process for the crashing available in the following table:

Table 2. Iteration Process for Crashing.

Figure 3. Project Cost vs Time

4.    Selection of Criteria.

The total cost for crashing the project should not exceed the total cost to operate the ship to ship within the total days saved.

5.    Analysis and Comparison of the Alternative.

Since the crashing criteria for the project is to achieve the minimum feasible project duration with the total cost for crashing should not exceed the cost to operate ship to ship, the Author has develop a simulation table as follow:

Table 3. Cost for Crashing vs Cost Saving

6.    Selection of the Preferred Alternative.

The minimum feasible project duration is 235 days with costs US$ 165.000 to crash and save US$ 250.000 from avoiding ship to ship operation. The decision is profitable for the company since it has a net cost saving of US$ 85.000.

7. Performance Monitoring & Post Evaluation of Result

Although the management has decided to crash the project by 50 days, it is possible to make a further reduction of the project duration in other ways. Some example include: if the scope were reduced or if more experienced resources could perform the activities faster and cheaper than the currently assigned resources or of activities can be performed in parallel (fast tracking)

References:

1. Humphreys, G.C. (2011). Project Management Using Earned Value, Chapter 11, page 245, Second Edition, Humphreys & Associates, Management Consultants.
2. Milza, Rico. (2016). W14_RM_Project Schedule Contingency. Retrieved from: https://goldenaace2015.wordpress.com/2016/04/21/w14_rm_project-schedule-contingency/
3. Milza, Rico. (2016). W15_RM_Project Schedule Contingency (2). Retrieved from: https://goldenaace2015.wordpress.com/2016/04/23/w15_rm_project-schedule-contingency-2/
4. GAO. (2015). Schedule Assessment Guide: Best Practices for Project Schedules. Retrieved form: http://www.gao.gov/assets/680/674404.pdf

 

W12_TK_Scheduling Risk Analysis MCC Building

1. Problem Definition

A copper mine and Product Company currently have an expansion project in Eastern Indonesia.  By end next month the project shall be commissioning. There is one little package MCC building was given to local sub-contractor as requirement from Government to involved local Company. The sub-contractor shall submit detail schedule to show how much times required and do risk analysis against that schedule to determine schedule contingency.

2. Development of Feasible Alternatives

The steps involved in assessing the risk of a schedule are as follows:

• Create a complete and quality-checked CPM network.
• Develop three duration estimates (optimistic, pessimistic, and most likely) for each activity.
• Identify a duration distribution method for all activities.
• Compute the path distribution.
• Evaluate the result (completion date certainty and high risk paths)
• Initiate status monitoring

In compute the path distribution, there are two tools will be used, namely PERT and Monte Carlo simulation. This W12 blog posting will use PERT analysis.

3. Development of the Outcomes for Alternative

Table-01 below showing the project base activity and Figure-01 showing its CPM Network:

Table-01 Project Based Activity

Figure-01 CPM Network – Precedence Diagram Method (PDM)

As shown in Figure-01, the Project duration is 39 days, with the critical path is activities ACEFGHLM. Beside critical path, there are two other paths, namely ACEJKM and ADHLM.

Table-02 below contains three duration estimates, where a, b and m are optimistic, pessimistic and most likely respectively.

Table-02 Three Duration Estimates

By using PERT analysis, it has been obtained expected time, variance and standard deviation for Critical Path CDFGHI as shown in Table-03.

Table-03 Result of PERT analysis for Critical PATH ACEFGHLM

4. Selection of the Acceptable Criteria

It is necessary to look the result of above PERT analysis.

5. Analysis and Comparison of the Alternatives

Table 4 contains comparison of schedule risk analysis using PERT for all paths.

Table-04 Comparison of Risk Schedule Analysis using PERT

6. Selection of the Preferred Alternative

By using management desired probability of P80, contingency for Schedule Risk using PERT analysis for all paths were obtained, as shown in Table-05 below.

Table-05 Schedule Contingency

We decide to use critical path ACEFGHLM contingency of 3 days as schedule as contingency of the Project.

7. Performance Monitoring and Post-Evaluation of Results

Since the schedule only short period of time, bar-chart schedule with three (3) week look ahead will very helpful. Daily target schedule have to set up and monitor, materials and tools shall be ready available at least 3week before activity to be done.

Reference:

1. Humphreys, G.C. (2011). Project Management Using Earned Value, Chapter 17, third  Edition, Humphreys & Associates, Management Consultants.

2. United States Government Accountability Office( May 2012) GAO Schedule assessment guide
3. Wain Y.A. (2014). W24_YAW_Schedule Risk Analysis Retrieved from https://kristalaace2014.wordpress.com/2014/08/01/w24_yaw_schedule-risk-analysis/

 

 

W12.0_MY_OMNIClass Standard 3D WBS On New Building and Electrical Installation for SS#71

 Problem definition

As my previous blog before, which is used NORZOL Standard Z-014 3D WBS in my project as my management was decided to make new building complete electrical equipment and installation for Sub Station #71 for replace existing Sub Station #71 which is the structure of existing substation #71 already repaired to make sure no other issues for 20 year ahead.

Now, I will try to use OMNIClass Standard 3D WBS can be applied to this project too?

Development of the Feasible Alternatives

The OmniClass Construction Classification System (known as OmniClass or OCCS) is a means of organizing and retrieving information specifically designed for the construction industry. OmniClass draws from other extant systems in use to form the basis of its Tables wherever possible — MasterFormat™ for work results, UniFormat™ for elements, and EPIC (Electronic Product Information Cooperation) for products.

OmniClass consists of 15 hierarchical tables, each of which represents a different facet of construction information. Each table can be used independently to classify a particular type of information, or entries on it can be combined with entries on other tables to classify more complex subjects.

3D WBS is a theory that tells us that WBS includes three main dimensions: Construction Entities by Form (Table 12), Element (Table 21), and Work Result (Table 22). The concept for OmniClass is derived from internationally-accepted standards that have been developed by the International Organization for Standardization (ISO) and the International Construction Information Society (ICIS) subcommittees and workgroups from the early-1990s to the present.

Development of the outcomes and Cash flow

There are three tree structures that compose the WBS from 3D WBS, namely:

1) Table 12 that Construction Entities by Form are significant, definable units of the built environment comprised of elements and interrelated spaces and characterized by form

2) Table 21 that Construction Entities by Form are significant, definable units of the built environment comprised of elements and interrelated spaces and characterized by form

3) Table 22 that Work Results are construction results achieved in the production stage or phase or by subsequent alteration, maintenance, or demolition processes and identified by one or more of the following: the particular skill or trade involved; the construction resources used; the part of the construction entity which results; the temporary work or other preparatory or completion of work which is the result.

 Selection of Criteria

Characteristics of the WBS:

1. WBS defines output
2. WBS is hierarchical
3. One WBS level’s output is an input to the next higher level.
   

   Analysis and Comparison of the alternatives

Then I will try to create 3D WBS with using OMNIClassStandard as reference.

Selection of preferred Alternative

3D WBS method can be based on OMNIClass is really detailed. OMNIClass can be applied to this new building and electrical for SS#71 and project. It gives a more detailed and suitable WBS for oil and gas projects and to avoid additional scope of work. And using OMNIClass could be give more detailed by using more table as OMNIClass was prepared 15 tables.

Performance Monitoring and Post Evaluation Result

OmniClass is designed to provide a standardized basis for classifying information created and used by the North American architectural, engineering and construction (AEC) industry, throughout the full facility life cycle from conception to demolition or reuse, and encompassing all of the different types of construction that make up the built environment. OmniClass is intended to be the means for organizing, sorting, and retrieving information and deriving relational computer applications.

References:

OMNICLASS A Strategy for Classifying The Built Information. (n.d.). Retrieved from http://www.omniclass.org/background.asp

Humpreys, G. C. (2011). Project Management Using Earned Value (2nd ed.). Pp 45 – 57. Humpreys & Associates, Inc.

Mayapati (2016). W11.0_MY_NORSOK Standard Z-014 3D WBS On New Building and Electrical Installation for SS#71. Retrieved from https://goldenaace2015.wordpress.com/2016/04/07/w11-0_my_norsok-standard-z-014-3d-wbs-on-new-building-and-electrical-installation-for-ss71/