W9_AI_Contingency Estimation of O&M Cost Offshore Regasification Project

  1. Problem Definition

Offshore Regasification Project has been one of the most priority project. Therefore, calculation of O&M Cost of Offshore Regasification Project must be developed.

The objective of this calculation is to determine cost overrun probability during O&M period. Therefore, it is necessary to prepare cost contingency for the project to anticipate the additional cost.

  1. Identify the Possible Alternative

There are 4 methods to estimate cost (also time) contingency, as follow:

  • Expert Judgment
  • Predetermined Guidelines
  • Simulation Analysis
    • Range Estimation
    • Expected Value
  • Parametric Modeling

For this case, Author uses Simulation Analysis with Range Estimation method.

Range estimating is a risk analysis technology that combines Monte Carlo sampling, a focus on the few critical items, and heuristics (rules of thumb) to rank critical risks and opportunities. This approach is used to establish the range of the total project estimate and to define how contingency should be allocated among the critical items.

  1. Development of The Outcome for Alternative

The following steps will be used to determine cost contingency using range estimating:

  • Determines of ranges for each cost items.
  • Determines the probability that each item can be completed within the estimate.
  • Running Monte Carlo simulation for the cost range.
  • Determines of critical items based on result of Monte Carlo simulation.
  • Determine of contingency with reference to critical items only.

Following are base estimates for each cost items:

Table 1. Base Estimate of O&M Cost Offshore Regasification Facilities

Estimator has developed table (1) above, to determine range of each cost item. Good estimate shall be calculated equal probability of overrun and underrun (50% probability), hence the assumption being that some project will overrun while others will underrun, and in the end they will balance out.

But estimator shall be added some risk-aversed attitude, in this calculation P80 will be used. It means that probability of 80% that the project will not overrun.

Table 2. Range and Desire Probability of Each Component

After determining range and desire probability of component cost, further step is to conduct Monte Carlo simulation with 1000 iterations. The result as follow:

Table 3. Monte Carlo Simulation Result

  1. Selection Criteria

Estimator using Bottom Line Critical Variance to categorize critical item of each cost component, table show below:

Table 4. Bottom Line Critical Variances

  1. Analysis & Comparison of Alternative

Using Bottom Line Critical Variance table above, critical item result as follows:

Table 5. Critical Items

  1. Selection of the Preferred Alternative

After categorize critical component, then the next step is determining cost contingency, as shown in following table:

Table 6. Cost Contingency

Hence the total cost contingency will be used for this project is $ 126.000 (only for critical item).

 

  1. Performance Monitoring and The Post Evaluation of Result

During the implementation of Offshore Regasification Project, it is necessary to monitor O&M cost to prevent cost overrun exceed cost contingency.

References:

  1. AACE International Recommended Practice No. 41R-08
    Retrieved from https://www.yumpu.com/en/document/view/50838191/41r-08-risk-analysis-and-contingency-determination-using-range-
  2. AACE International Recommended Practice No. 44R-08
    Retrieved from http://nebula.wsimg.com/ab1871cc797714d7bf4dc2bfc4f5c243?AccessKeyId=593FFA6B20F5002887D7&disposition=0&alloworigin=1
  3. Milza, R. (2016). W10_RM_Contingency Estimation in Gas Station Project.

Retrieved from https://goldenaace2015.wordpress.com/2016/03/08/w10_rm_contingency-estimation-in-gas-station-project/

  1. Asro. Y. W. (2014). W20_YAW_Contingency Estimation in Storage Tank Project.

Retrieved from  https://kristalaace2014.wordpress.com/2014/07/07/w20_yaw_contingency-estimation-in-storage-tank-project/

 

W8.1_AI_Tuckman Survey on Process Engineer Team

  1. Problem Definition

Process Engineer Team has been actively working together for the past 4 years. The challenge of this team is the increasing and complexity of gas infrastructure projects that will be faced. We now want to determine the leadership skills and styles which the group may benefit from as it enters this next phase of the project. Then for this week Tuckman Survey will be applied.

  1. Identify the Possible Alternative

In 1965, Tuckman published his Forming Storming Norming Performing model and completed with the fifth stage, Adjourning in 1970s. This model explains that as the team develops maturity and ability, relationships establish, and the leader changes leadership style from Directing (Telling), Coaching, Participative, and Delegating up to Directing (Concluding).

Fig. 1 Tuckman’s Team Development Model

Illustration graph of Tuckman Model Group Development Stages is shown in the next figure:

Fig 2. Tuckman Group Development Stages Model

  1. Development of The Outcome for Alternative

To determine current Process Engineer Team stage, each individual in team fill the excel format of Tuckman Survey Scoring Template.

Table.1 – Individual responses from the Tuckman Survey Scoring Template.

  1. Selection Criteria

Based on the above individual’s response, PERT analysis was performed to identify team behavior at P90 because these team already join over long time (4 years)

Table 2. P90 Delphi Technique Result

  1. Analysis & Comparison of Alternative

Based on Table 2, we can conclude team is in Performing stage (indicated by the rank). During this stage, team members often experience:

  • Constructive self-change;
  • Deep sense of belonging;
  • Understanding of each other’s strengths and weaknesses;
  • Self-organization of work;

Hints for team leaders:

  • Delegate all work that sensibly can;
  • Focus on developing team members;

Style of leadership this stage is “DELEGATING” mode where some leadership is shared by the team.

  1. Selection of the Preferred Alternative

Process Engineer team can achieve more than each team member individually. Being part of a high-performance team can be extremely rewarding, but it requires time and commitment to get to that stage. The team leader job is to help this team reach and sustain high-performance and leader has to adapt behavior and leadership style to the different challenges presented at each stage. The team leader responsibility is to be aware of the challenges the team will face and support the team to get aim together.

  1. Performance Monitoring and The Post Evaluation of Result

Team assessment should conduct periodically in six months ahead to capture team phase changing and select appropriate style of leadership, this evaluation can help the team to improve coordination and productivity.

 

References:

  1. Tuckman, B. (1965). Tuckman’s Team Developmental Model. Retrieved from http://www.focusadventure.com/team-building/gallery/tuckmans-team-developmental-model/
  2. Michell, Tony (2017). W2_ABM_Folow Up Tuckman|EMERALD AACE 2017. Retrieved from http://emeraldaace2017.com/2017/08/08/w2_abm_follow-up-tuckman-survey-on-spj-offshore-construction-team/
  3. Irene, A. (2017). W2_AI_Tuckman Analysis|EMERALD AACE 2017.

Retrieved from https://emeraldaace2017.com/2017/08/01/w1_ai_tuckman-analysis-assigment/

 

W8_AI_Tuckman Survey for Process Engineering

  1. Problem Definition

Process Engineer Team has been actively working together for the past 4 years. The challenge of this team is the increasing and complexity of gas infrastructure projects that will be faced. We now want to determine the leadership skills and styles which the group may benefit from as it enters this next phase of the project. Then for this week Tuckman Survey will be applied.

  1. Identify the Possible Alternative

In 1965, Tuckman published his Forming Storming Norming Performing model and completed with the fifth stage, Adjourning in 1970s. This model explains that as the team develops maturity and ability, relationships establish, and the leader changes leadership style from Directing (Telling), Coaching, Participative, and Delegating up to Directing (Concluding).

Figure 1. Tuckman’s Team Development Model

Illustration graph of Tuckman Model Group Development Stages is shown in the next figure:

Fig 2. Tuckman Group Development Stages Model

  1. Development of The Outcome for Alternative

To determine current Process Engineer Team stage, each individual in team fill the excel format of Tuckman Survey Scoring Template.

Table.1 – Individual responses

  1. Selection Criteria

Based on the above individual’s response, PERT analysis was performed to identify team behavior at P90 because these team already join over long time (4 years)

Table 2. P90 Delphi Technique Result

  1. Analysis & Comparison of Alternative

Based on Table 2 above, we can conclude the team is in Performing stage (indicated by the rank). During this stage, team members often experience:

  • Constructive self-change;
  • Deep sense of belonging;
  • Understanding of each other’s strengths and weaknesses;
  • Self-organization of work;

Hints for team leaders:

  • Delegate all work that sensibly can;
  • Focus on developing team members;

Style of leadership this stage is “DELEGATING” mode where some leadership is shared by the team.

  1. Selection of the Preferred Alternative

Process Engineer team can achieve more than each team member individually. Being part of a high-performance team can be extremely rewarding, but it requires time and commitment to get to that stage. The team leader job is to help this team reach and sustain high-performance and leader has to adapt behavior and leadership style to the different challenges presented at each stage. The team leader responsibility is to be aware of the challenges the team will face and support the team to get aim together.

  1. Performance Monitoring and The Post Evaluation of Result

Team assessment should conduct periodically in six months ahead to capture team phase changing and select appropriate style of leadership, this evaluation can help the team to improve coordination and productivity.

 

References:

  1. Tuckman, B. (1965). Tuckman’s Team Developmental Model. Retrieved from http://www.focusadventure.com/team-building/gallery/tuckmans-team-developmental-model/
  2. Michell, Tony (2017). W2_ABM_Folow Up Tuckman|EMERALD AACE 2017. Retrieved from http://emeraldaace2017.com/2017/08/08/w2_abm_follow-up-tuckman-survey-on-spj-offshore-construction-team/
 

W7.1_AI_Developing Operation & Maintenance Model for Offshore Regasification Facility Project

 

  1. Problem Definition

Besides capital expenditure, one of the cost components which is needed in financial economic model is operation and maintenance cost. Still discuss about offshore regasification facility project, this week I will develop operation and maintenance model for the project, and this WBS would be applied for O&M activities provide by owner so it will be covered the asset of onshore receiving facilities and pipeline. As for the initial stages in building O&M model is determine cost structure. In making the cost structure of a project, the first thing to do is by determining work breakdown structure (WBS). In this week, I will choose WBS standardization between omni class and norsok to be applied.

Figure 1. Business Scheme

  1. Identify the Possible Alternative

There are two commonly used WBS standardization among others:

  1. OmniClass
  2. Norsok

Both of this standard would be compared and the optimum WBS standard would be chosen.

 

  1. Development of The Outcome for Alternative

Table 1. OmniClass Table

The table above is 15 hierarchical that is designed to provide a standardized basis for classifying information. Each of it represents a different phase of project information and every entity can be combined one and another, to build more complex structure.

Moine has developed a 3D WBS model. All of three dimension project can be integrated which visualized as figure below:

Figure 2. 3D WBS Model

 

Norsok Standard describe a system for cost coding and weight estimates and as-built or experience data. The following is coding system classification of Norsok standard:

Figure 3. Norsok Standard

 

  1. Selection Criteria

Cost structure which can be applied from OmniClass standard to O&M model of Offshore Regasification Facility Project consists of:

Table 2. WBS Matrix

The table above shows matrix from omniclass table to being an input for develop 3D WBS structure.  The 3D WBS is based on three main dimensions consist of Zone Breakdown Structure (ZBS), Product Breakdown Structure (PBS) and Activity Breakdown Structure (ABS).

While the applicable cost coding of Norsok Standard to O&M model of Offshore Regasification Facility Project consists of:

Figure 4. Operational Principles Norsok Standard

Using Norsok standard some parameter must be identified at the first place:

  1. Operating Concept
  • Operation objectives
  • Operating environment
  1. Operating Philosophy
  • Criticality
  • Complexity
  • Choice of technology
  • Training and sparing
  • Manning and personnel competence
  1. Production function requirements
  • Production operations (general, start-up, shut-down, isolation for maintenance, well testing, well intervention)
  1. Maintenance function requirements
  • Maintenance strategy
  • Maintenance engineering (design, organization, programs)
  1. Inspection strategy

 

  1. Analysis & Comparison of Alternative

Both standards can be applied in operation & maintenance model of offshore regasification project. But one of the most optimum methods must be chosen to be applied in this project. Considering that the methods used is top-down and from owner perspective, as well as on business scheme operation & maintenance facilities will be contracted to a third party (ship management) using the Long Term Service Agreement, so to coverage of O&M model consists of head quarter for office activity, along onshore receiving facilities and pipeline.

Considering it is then the most optimum standard used is OmniClass standard.

The developed WBS will be follow this criteria:

  • WBS Phase related to the asset
  • WBS Area related to the asset
  • WBS Service related to the asset
  • WBS Organization Role related to the asset
  • WBS Element related to the asset

Table 3. WBS Value Score

Table 4. WBS Weighted Score

  1. Selection of the Preferred Alternative

Based on above description, it shows that the combination of Omniclass table with 3D WBS is better than the single standard. As we can gain deliverables that can be view from many perspectives. Then OmniClass 3D WBS is considered to be applied for Offshore Regasification Facility Project. The rating of OmniClass 3D WBS as follow:

Table 5. OmniClass Table Rating

Rating no 1 up to no 6 will be develop as an input for 3D WBS of Offshore Regasification Facility Project.

 

  1. Performance Monitoring and The Post Evaluation of Result

This 3D WBS is very suitable with condition of current business scheme, so it will have a positive impact on the company for developing it. But also the company need to consider another standard like Norsok as a validation against third parties, or when the business scheme changes, such as the company responsible as a facility operator & maintenance.

Reference:

  1. Planning Planet (2017). Creating Work Breakdown Structure.

Retrieved from http://www.planningplanet.com/guild/gpccar/creating-work-breakdown-structure

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 3 – Cost-Estimation Techniques, pp. 96-98.
  2. Hendarto, T. (2017). W6.1_TH_ Standardized WBS Structures for Gas Station Project-Part 3

Retrieved from https://emeraldaace2017.com/2017/09/22/w6-1_th_-standardized-wbs-structures-for-gas-station-project-part-3/

  1. Norsok Standard. Retrieved from

http://www.standard.no/en/webshop/norsok/?gclid=CjwKCAjwuvjNBRBPEiwApYq0znFC82NEh-OnYem5gU6RHcLNKM-Gx94QdFJQCp_ljPWR14CyBKHaoRoC2r8QAvD_BwE#.Wb5XtdElHIU

  1. OmniClass Standard. Retrieved from

http://www.omniclass.org/

 

W7_AI_Developing Operation & Maintenance Model for Offshore Regasification Facility Project

  1. Problem Definition

Besides capital expenditure, one of the cost components which is needed in financial economic model is operation and maintenance cost. Still discuss about offshore regasification facility project, this week I will develop operation and maintenance model for the project. As for the initial stages in building O&M model is determine cost structure. In making the cost structure of a project, the first thing to do is by determining work breakdown structure (WBS). In this week, I will choose WBS standardization between omni class and norsok to be applied.

 

  1. Identify the Possible Alternative

There are two commonly used WBS standardization among others:

  1. OmniClass
  2. Norsok

Both of this standard would be compared and the optimum WBS standard would be choosen.

 

  1. Development of The Outcome for Alternative

Table 1. OmniClass Table

The table above is 15 hierarchical that is designed to provide a standardized basis for classifying information. Each of it represents a different phase of project information and every entity can be combined one and another, to build more complex structure.

Moine has developed a 3D WBS model. All of three dimension project can be integrated which visualized as figure below:

Figure 1. 3D WBS Model

 

Norsok Standard describe a system for cost coding and weight estimates and as-built or experience data. The following is coding system classification of Norsok standard:

Figure 2. Norsok Standard

 

  1. Selection Criteria

Cost structure which can be applied from OmniClass standard to O&M model of Offshore Regasification Facility Project consists of:

  1. Level 1 Table 31 – Phases
  2. Level 2 Table 32 – Service
  3. Level 3 consists of several components:
  • Table 34 – Organizational Roles
  • Table 21 – elements

Figure 3. Table 31 – Phase

Figure 4. Table 32 – Service

Figure 5. Table 34 – Organizational Roles

Figure 6. Table 21 – elements

 

While the applicable cost coding of Norsok Standard to O&M model of Offshore Regasification Facility Project consists of:

Figure 7. Operational Principles Norsok Standard

Using Norsok standard some parameter must be identified at the first place:

  1. Operating Concept
  • Operation objectives
  • Operating environment
  1. Operating Philosophy
  • Criticality
  • Complexity
  • Choice of technology
  • Training and sparing
  • Manning and personnel competence
  1. Production function requirements
  • Production operations (general, start-up, shut-down, isolation for maintenance, well testing, well intervention)
  1. Maintenance function requirements
  • Maintenance strategy
  • Maintenance engineering (design, organization, programs)
  1. Inspection strategy

 

  1. Analysis & Comparison of Alternative

Both standards can be applied in operation & maintenance model of offshore regasification project. But one of the most optimum methods must be chosen to be applied in this project. Considering that the methods used is top-down and from owner perspective, as well as on business scheme operation & maintenance facilities will be contracted to a third party (ship management) using the Long Term Service Agreement, so the coverage of O&M model consists of head quarter O&M, along onshore receiving facilities and pipeline on site.

Considering it is then the most optimum standard used is OmniClass standard.

 

  1. Selection of the Preferred Alternative

Based on above description, it shows that the combination of Omniclass table with 3D WBS is better than the single standard. As we can gain deliverables that can be view from many perspectives. Then OmniClass 3D WBS is considered to be applied for Offshore Regasification Facility Project.

 

  1. Performance Monitoring and The Post Evaluation of Result

This 3D WBS is very suitable with condition of current business scheme, so it will have a positive impact on the company for developing it. But also the company need to consider another standard like Norsok as a validation against third parties, or when the business scheme changes, such as the company responsible as a facility operator & maintenance.

Reference:

  1. Planning Planet (2017). Creating Work Breakdown Structure.

Retrieved from http://www.planningplanet.com/guild/gpccar/creating-work-breakdown-structure

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 3 – Cost-Estimation Techniques, pp. 96-98.
  2. Nunar, A. H. (2014). 1_SJP_Forecasts Part 3.

Retrieved from https://soroakoaace2014.wordpress.com/2014/10/01/w4_anh_exploring-omniclass-and-3d-wbs-for-waste-water-treatment-plant-project/

  1. Norsok Standard. Retrieved from

http://www.standard.no/en/webshop/norsok/?gclid=CjwKCAjwuvjNBRBPEiwApYq0znFC82NEh-OnYem5gU6RHcLNKM-Gx94QdFJQCp_ljPWR14CyBKHaoRoC2r8QAvD_BwE#.Wb5XtdElHIU

  1. OmniClass Standard. Retrieved from

http://www.omniclass.org/

 

W6_AI_Price Forecasts for Offshore Regasification Facility Project

  1. Problem Definition

After last week blog discussed about cost estimate calculation for offshore regasification facility project using historical data, and then this week according to Dr. Paul Giammalvo suggestion, price forecast method will be used to predict project cost within the next 5 years.

Still using the same indicative price last week, this week the indicative price for offshore regasification facility project with capacity 100 MMSCFD will be forecasting using MS Excel “Best Fit” Regression Analysis Curve.

This calculation can be using as an input value in financial economic model. With this method, we can calculate cash flow prediction project value within a certain period in the future.

  1. Identify the Possible Alternative

Using last week indicative price, then capex value for offshore regasification facility project, as follow:

Table 1. Indicative Price

From the table above, then to analyze price forecasts for next 5 years will use:

  1. MS Excel “Best Fit” Linear Regression Analysis Curve
  2. MS Excel “Best Fit” Polynomial Regression Analysis Curve
  3. MS Excel “Best Fit” Logarithmic Regression Analysis Curve

 

  1. Development of The Outcome for Alternative

These are the following an initial data plotting in determining price forecast:

Picture 1. Input Data

Using these input data (indicative price 2015-2017) and MS Excel “Best Fit” Linear Regression Analysis Curve, then trendline and trending them out to 5 years provide in picture (2) below. While the trendline use R2 = 0.9948.

Picture 2. Linear Trendline

Then still using data input in 2015-2017, now MS Excel “Best Fit” Polynomial Regression Analysis Curve with R2 = 1 will be used in the second analysis. The result of the polynominal regression analysis can be seen in the picture (3) below.

Picture 3. Polynominal Trendline

The latest, on the third data input in 2015-2017 analysis will use MS Excel “Best Fit” Logarithmic Regression Analysis Curve with R2 = 0.9941. The result of the logarithmic regression analysis can be seen in the picture (4) below.

Picture 4. Logarithmic Trendline

With the purpose to make it simple to see the results of the analysis, then bellow will be displayed plotting all three trendline in one chart.

Picture 5. All Trendline (Linear, Polynominal, Logarithmic)

 

  1. Selection Criteria

Further, value of all treadline for the fifth year, which is 2021, will be used, ranked and analyzed using PERT calculation. As for the smallest value represents “best case”, middle value represents “most likely” and the highest value represents “worst case”.

 

  1. Analysis & Comparison of Alternative

The following is data to be used for PERT calculation

Table 2. Trendline Forecasts of Offshore Regasification Facility Project

From the table above, we can see

a. Best case (optimistic) = $ 114.2

b. Most Likely case = $ 123.5

c. Worst case (pessimistic) = $ 124.2

Using PERT calculation, then the Mean, Sd, and variance:

Step 1 – PERT weighted Mean

= ((Optimistic)+(4 x Most Likely)+(pessimistic))/6

= $ ((114.2) + (4 x 123.5) + (124.2))/6

= $ 732.4/6

= $ 122.1

Step 2 – Standard Deviation

= (Largest Value – Smallest Value)/6

= $ (124.2 – 114.2)/6

= $ 10/6

= $ 1.67

Step 3 – Variance

= Sigma/Standard Deviation^2

= $ 1.67^2

= $ 2.8

The following picture (6) below shows normal distribution curve:

Picture 6. Normal Distribution Curve

From the step 3, there is small variance means that the risk was small, so there is no need high contingency to cover the risk. Hence, P(75) will be considered to being calculate for the indicative price .

Picture7. P(75) Distribution Curve

The following above is P(75) cost estimate offshore regasification facility project in 2021 with value $ 123.36.

 

  1. Selection of the Preferred Alternative

This blog displays one of method in determining price forecast, on next week blog another price forecast method will be applied. So in the last price forecast series, the best and optimum forecast method will be chosen to be applied in part of financial economic model for offshore regasification facility project.

 

  1. Performance Monitoring and The Post Evaluation of Result

Forecasting method very dependent on the amount of data used, so it will be better and optimal if forecasting calculations using updated and valid data. Therefore project character are dynamic and unique, preferably input data for price forecast is updated periodically as a continual process of checking, reviewing and monitoring.

Reference:

  1. Planning Planet (2017). Creating The Owners Cost Estimate (Top Down).

Retrieved from http://www.planningplanet.com/guild/gpccar/creating-the-owners-cost-estimate

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 3 – Cost-Estimation Techniques, pp. 113-121.
  2. (2017). W11.1_SJP_Forecasts Part 3.

Retrieved from https://js-pag-cert-2017.com/w11-1_sjp_forecasts-part-3/

  1. (2009). Excel Dynamic Chart #11: Dynamic Area Chart with IF Functioin – Normal Distribution Chart Statistics

Retrieved from https://www.youtube.com/watch?v=Fp1JV-ZVDZw

 

 

 

 

 

 

 

 

W5_AI_Power Sizing Model and Index Value for Offshore Regasification Facility Project Cost Estimating

 

  1. Problem Definition

The gas supply scheme has been choose using decision making models (previous weeks) is Offshore Regasification Facility. Gas demand from customer is 100 MMSCFD, so the facility shall be designed 100 MMSCFD at minimum capacity. Company has indicative price from 3 (three) different contractor (all good performance contractor). Since the company will be using the price for calculate economic model (conceptual), then the optimum average price for 100 MMSCFD gas facility must be develop, in this stage power sizing-model would be applied.

 

  1. Identify the Possible Alternative

There are indicative historical price from 3 (three) different companies, as follow:

Table 1. Indicative Price

Table above shows the indicative price from PT.A, PT.B, and PT. C with various capacities. Furthermore to get the requirement capacity 100 MMSCFD, correlation exponent will be obtained by power sizing-model.

 

  1. Development of The Outcome for Alternative

Picture 1 below shows the formula of power sizing-model using correlation between price and capacity.

Picture 1. Power Sizing Model Formula

Based on data and formulation above, here is the analysis and calculation for correlation exponent result:

Table 2. Correlation Exponent

Using correlation exponent (m), sizing model analysis for 100 MMSCFD for each contractor could be calculated as follow:

Table 3. Estimate Cost 100 MMSCFD

  1. Selection Criteria

The optimum average price for 100 MMSCFD offshore gas facility will be defining using power sizing model.

 

  1. Analysis & Comparison of Alternative

Picture 2. Estimate Cost 100 MMSCFD

The calculation above show still using 2012 database and to get reflection new cost 2017 the data shall be adjusted by index value.

Picture 3. Index Value Formula

Table 4. Index Value Result

  1. Selection of the Preferred Alternative

The table (4) above shows the indicative price of offshore regasification facility, with the lowest price is 130.99 MMU$ from PT. A compare to PT. B (145.84 MMU$) and PT.C (183.55 MMU$). Based on analysis above, PT. A  indicative price will be chosen.

 

  1. Performance Monitoring and The Post Evaluation of Result

Power Sizing Model and Index Value above is a good formula to estimate the indicative price for conceptual economic calculation. It can be using of any kind project, such as oil & gas, automotive, power plant, etc.

Reference:

  1. Planning Planet (2017). Creating The Owners Cost Estimate (Top Down).

Retrieved from http://www.planningplanet.com/guild/gpccar/creating-the-owners-cost-estimate

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 3 – Cost-Estimation Techniques, pp. 99-110.
  2. Aziz, A. A. (2015). W12_AAA_Sizing Model and Economic of Scale (Gas Processing Facilities)

Retrieved from https://garudaaace2015.wordpress.com/2015/05/30/w12_aaa_sizing-model-and-economies-of-scale-gas-processing-facilities/

  1. Diary, C.A (2017). Cost Inflation Index – Capital Gain.

Retrieved from https://cadiary.org/cost-inflation-index-capital-gain/

 

W4_AI_Selecting The Best Gas Supply Scheme for X Project Using Compensatory Models

  1. Problem Definition

Since the last week the gas supply scheme already define by using non-compensatory model, then for this week compensatory models will be used to select the best gas supply scheme. By using and compare both of multi attribute decision making models, the best model can be chosen. The compensatory models divided into 2 (two) approach which is non-dimensional scaling and the additive weighting technique.

 

  1. Identify the Possible Alternative

3 (three) alternative gas supply facility to fulfill gas needed of x area, as follow:

  1. Offshore regasification facility
  2. Gas pipeline
  3. Landbase regasification facility

Table 1. Alternative Value

  1. Development of The Outcome for Alternative

Compensatory model using weighted score with the range 0 to 1 with the purpose is identifying dimensionless value for each attribute.

  1. Non-dimensional Scaling

Table 2. Dimensionless Scoring model

The table above, show the scoring 1 means the highest/optimum value of attribute (preference decision), meanwhile the scoring 0 means the minimum value (avoided decision). Quantitative comparison for each alternative describe in table 2 above, after that the total score is required to represent the rank of alternative.

Table 3. Dimensionless Relative Weighting

Using non-dimensional scaling, the highest rank is offshore regasification facility with total score 6.11 (1.5 times better than pipeline)

2. The Additive Weighting Technique

Table 4. Additive Weighting Score

Table 4 (above) describe the highest rank is offshore regasification facility with total score 0.91 (1.7 times better than pipeline).

 

  1. Selection Criteria

The highest alternative rank of gas supply scheme was defined using both of compensatory models.

 

  1. Analysis & Comparison of Alternative

Both of compensatory models have the same result with offshore regasification facility as the highest rank, it shown on:

Table 5. Compensatory Model

The difference between these two techniques is the weighting factors, the additive weighting using weighting factor because each attribute might be have different level of importance. Therefore, the recommendation chosen by additive weighting model, has been concern the alternate values and the attribute importance also.

 

  1. Selection of the Preferred Alternative

The compensatory model using quantitative data to being calculate, meanwhile the non-compensatory (last week) model using qualitative judgment to being analyze. Since the quantitative approach give more clear comprehension, so the preferred model to present to director is compensatory model.

Both models, compensatory and non-compensatory model show that Offshore Regasification facility was the best alternative to choose.

 

  1. Performance Monitoring and The Post Evaluation of Result

The alternative value could be change based on the project characteristic (every project is unique), so it is importance to really understand about the alternative to be compared.

Reference:

  1. Planning Planet (2017). Multi Attribute Decision Making.

Retrieved from http://www.planningplanet.com/guild/gpccar/managing-change-the-owners-perspective

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 14 – Decision Making Considering Multiattributes, pp. 603-608.
  2. Ardi (2017). W3_A_Using Multiattribute Decision Making with Compensatory and Non-Compensatory Model for Supply of Electricity Tanjung Uban

Retrieved from http://emeraldaace2017.com/2017/08/15/w3_a_using-multiattribute-decision-making-with-compensatory-and-non-compensatory-model-for-supply-of-electricity-tanjung-uban/

 

W3_AI_Selecting The Best Gas Supply Scheme for X Project Using Non-Dimensional Scaling Technique

  1. Problem Definition

My Company in initiation stage to fulfill gas needs of x area. There are 3 (three) alternative gas supply scheme, which can be analyzed to meet the company objective. Board of Director has been develop 7 (seven) mandatory parameter to select the best gas supply scheme. Hence a method is needed to accommodate all mandatory parameter, Multi-Attribute Decision Making method would be applied.

 

  1. Identify the Possible Alternative

3 (three) alternative gas supply facility to fulfill gas needed of x area, as follow:

  1. Offshore regasification facility
  2. Gas pipeline
  3. Landbase regasification facility

Because of the selected facility must be accommodating all the parameter that have been determined by Board of Director, then non-compensatory approach shall be chosen to select the best alternative in view of the full dimensionality.

 

  1. Development of The Outcome for Alternative

Non-compensatory approach consists of 4 different techniques:

  1. Dominance
  2. Satisficing
  3. Disjunctive Reasoning
  4. Lexicography

This technique is use to select the best alternative by comparing an attribute –by-attribute.

Table 1. Parameter Objective

Using non-compensatory approach, all of 3 (three) alternative gas supply will be ranked to get the most optimal alternative.

 

  1. Selection Criteria
  • Dominance

Table 2. Alternative Dominance

From table (2) above, Offshore Regasification Facility dominates for all categories, with the only contenders would be Pipeline A. While, Landbase Regasification Facility cannot compete in all an attributes with offshore Regasification and pipeline A.

  • Satisficing

Table 3. Alternative Satisficing

The minimum and maximum acceptable value for alternative has been described in table (3) above. Maximum acceptable value was adjusted by the company target, with baseline MARR 10% and project on-stream Q2 2019.

This step to weed out any outliers, and also serves to look at only the alternative are marginally acceptable, eliminating the ability to look extremes which may prove to be acceptable trade off.

  • Disjunctive Reasoning

Table 4. Attribute Disjunctive

The attribute ranking base on importance scale are Social Risk > Permit Duration > Capex > Location > Delay Potential > Project Duration > Optimize Existing Asset.

This step is serves to determine attribute ranked in order of importance, by means of compare between each possible attribute combination.

  • Lexicography

Table 5. Alternative Lexicography

Using the ordinal ranking of attribute, in terms of social risk (1st rank) the best alternative is Offshore Regasification Facility, with another alternative which is even close would be Pipeline A and follow by Landbase Regasification Facility as the last alternative rank.

 

  1. Analysis & Comparison of Alternative

Base on the attribute, comparison for all alternatives would be defined, as follow:

Table 6. Alternative Comparison

  1. Selection of the Preferred Alternative

The best alternative was described in the analysis above, offshore regasification facility would be the best supply gas scheme to be proposed to Board of Director.

This alternative has considered all parameter objective required by BoD, while the only one cons should be mitigated by the planning team.

 

  1. Performance Monitoring and The Post Evaluation of Result

The cons condition shall be monitor and manage on the planning and execute stage to reduce the risk. Planning and project team must be identifying the activity which will give impact to offshore regasification facility construction.

Reference:

  1. Planning Planet (2017). Multi Attribute Decision Making.

Retrieved from http://www.planningplanet.com/guild/gpccar/managing-change-the-owners-perspective

  1. Sullivan, G. W. (2014). Engineering Economy 16th Chapter 14 – Decision Making Considering Multiattributes, pp. 603-608.
  2. Dhanu, H. U. (2017). 1_UDS_Choosing a New Fuel Terminal Location in Dumai Using Additive Weighting Technique in Multi-Attribute Decision Making.

Retrieved from http://emeraldaace2017.com/2017/08/09/w2-1_uds_choosing-a-new-fuel-terminal-location-in-dumai-using-additive-weighting-technique-in-multi-attribute-decision-making/

 

 

W2.1_AI_Workloading Histogram

  1. Problem Definition

Formed in face to face classroom (24-28 July 2017), Emerald AACE 2017 team will face the distance learning mode since then. In this phase, the daily work and a lot of tasks must be executed at the same time. To achieve optimal productivity and minimize stress, the workload must be distributed effectively. However some tools must be performed to monitor forecast and balance the distribution of workload, it was manloading chart, resource histogram, and s-curve.

 

  1. Identify the Possible Alternative

To monitor and manage the workload we can use manpower loading chart, resource histogram, and s-curve.

The proposed of these tools is to define forecast workload base on activity, resources, duration and target date. Therefore before the project being late, it will help the Project Manager to maintain team members load.

 

  1. Development of The Outcome for Alternative

The activity and plan for each member will be defined in man power loading chart, as follow:

Table 1. Emerald AACE 2017 Manpower loading chart

While the resource histogram showing required resource quantity in a week, as follow:

Picture 1. Emerald AACE 2017 Resource Histogram

Since the schedule was set, the s-curve showed cumulative man hours spend, as follow:

Picture 2. Emerald AACE 2017 S-curve

 

  1. Selection Criteria

Refer to Table.1 above (Manpower loading chart), it showing each member required 8 hours per week (P50) to finish all the tasks. Using the manpower loading chart, will give the information about each member peak and low time consumed.

Table 2. Emerald AACE 2017 Manpower loading chart (balance)

The resource loaded must be provide in the histogram showing required resource quantities and time consumed each week, then when compared to peak resource availability gives us a clear indication how much resource flexibility we have.

Picture 3. Emerald AACE 2017 Resource Histogram (balance)

While the s-curve will be using for monitoring the progress of the project to be tracked.

Picture 4. Emerald AACE 2017 S-curve

 

  1. Analysis & Comparison of Alternative

Since the advantage was mentioned above, so the disadvantage of those tools was:

  • Manpower loading chart : no clear information of resource flexibility
  • Resource histogram : no clear information of activity
  • S-curve : no clear information of peak and low period

 

  1. Selection of the Preferred Alternative

The objective was balance the workload distribution, so the important information that should be shown was peak and low period.

With this information, we can balance the resource from peak period to low period.

The best tools for Project Manager to manage and balance the team member was resource histogram.

 

  1. Performance Monitoring and The Post Evaluation of Result

Resource histogram shall be monitor in weekly basis, it will help Project Manager to maintain and monitor team member loading. In parallel, implementing these tools will help team member to manage the workload effectively, increase the productivity and raise the team opportunities to achieve goal together.

Reference:

  1. Planning Planet (2017). Allocating Resources.

Retrieved from http://www.planningplanet.com/guild/gpccar/allocating-resources

  1. Planning Planet (2017). Introduction To Managing Planning & Scheduling.

Retrieved from http://www.planningplanet.com/guild/gpccar/introduction-to-managing-planning-and-scheduling

  1. Planning Planet (2017). Assigning Resources To All Activities.

Retrieved from http://www.planningplanet.com/guild/gpccar/assigning-resources-to-all-activities

  1. Fahmi, A. (2013). W2_AFS_Workloading Histogram.

Retrieved from https://simatupangaace2014.wordpress.com/2013/09/12/w2_afs_-workloading-histogram/#more-423

  1. Likhite, Rashmi. (2015). Resource Load Chart.

Retrieved from https://celoxis.atlassian.net/wiki/display/DOC11/Resource+Load+Chart