Computerized Manpower Cost Estimation Risk Analysis
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Solution Overview
Problem
Accurate cost estimates for manpower in industrial construction and maintenance projects, particularly in complex systems like chemical, oil & gas, and agricultural processing, are challenging due to variable conditions and contingent risks, often relying on trial and error and historical records, leading to inefficiencies and inaccuracies.
Innovation Solution
A computerized system that analyzes project estimates by receiving current and historical data, applying quantitative adjustments, calculating risk values, and displaying final risk outputs to improve accuracy and mitigate risks, incorporating collaborative inputs from experienced personnel for risk determination and mitigation success probabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional trial and error methods with historical records are used for cost estimation, then the estimation process is simple to implement, but the accuracy and reliability of the estimates deteriorate
Solution Approach 1:
The system segments the cost estimation process into distinct modules: historical data collection, risk factor identification, quantitative adjustment application, and validation. Each module handles specific aspects of the estimation, transforming a monolithic trial-and-error approach into structured, manageable components that improve accuracy while maintaining implementability
Solution Approach 2:
The system performs preliminary actions by pre-collecting and organizing historical data, pre-identifying risk factors, and pre-establishing validation criteria before actual cost estimation. This preparatory work creates a robust framework that enhances estimation accuracy without increasing operational complexity during the estimation process itself
2Reliability
If comprehensive risk analysis with multiple variables is implemented, then the reliability of cost estimates improves, but the time and resources required for analysis increase
Solution Approach 1:
Historical data and risk factors are collected and organized in advance, creating a ready-to-use knowledge base. This preliminary preparation allows the system to perform comprehensive risk analysis without excessive time consumption during actual estimation, as the foundational work has already been completed
Solution Approach 2:
The system incorporates feedback mechanisms where estimation results and actual outcomes are continuously compared. This feedback loop refines risk factor weights and adjustments over time, improving reliability with each iteration while reducing the time needed for analysis as the system learns from past data
3Measurement precision
If historical risk factor data is used without adjustments, then the estimation process is straightforward, but the accuracy deteriorates due to anomalous historical risks and newly known risks
Solution Approach 1:
The system dynamically adjusts historical risk factors based on current project conditions, transforming static historical data into adaptive estimates. Quantitative adjustments are applied to account for anomalous historical risks and newly known risks, maintaining process simplicity through automated calculations while significantly improving estimate precision
Solution Approach 2:
The system changes key parameters of historical data by applying quantitative adjustments that modify risk factor weights, cost multipliers, and time estimates. These parameter transformations allow the system to maintain straightforward processing while adapting to current conditions, thereby improving precision without sacrificing ease of implementation
Data Source
AI summary
A computer apparatus and method for analyzing and improving industrial turnaround or construction project manpower estimates. The apparatus comprises one or more processors in operative communication with one or more data stores and with at least one tangible medium upon which is encoded machine-readable software, the software, upon its execution, being configured so that the system carries out a process for analyzing and adjusting manpower cost estimates, outputting actionable results for display to users, and archiving and aggregating project execution data for use in future project analyzes to improve analysis and estimation accuracy over time by feeding back into the system data indicative of the scale and sources of historical execution inefficiencies.