Life Cycle Cost Estimation Research Articles

Estimation of life-cycle costs of buildings: regression vs artificial neural network

Purpose– The purpose of this paper is to compare the performance of regression and artificial-neural-networks (ANNs) methods to estimate the running cost of building projects towards improved accuracy.Design/methodology/approach– A data set of 20 building projects is used to test the performance of these two (ANNs/regression) models in estimating running cost. The concept of cost-significant-items is identified as important in assisting estimation. In addition, a stepwise technique is used to eliminate insignificant factors in regression modelling. A connection weight method is applied to determine the importance of cost factors in the performance of ANNs.Findings– The results illustrate that the value of the coefficient of determination=99.75 per cent for ANNs model(s), with a value of 98.1 per cent utilising multiple regression (MR) model(s); second, the mean percentage error (MPE) for ANNs at a testing stage is 0.179, which is less than that of the MPE gained through MR modelling of 1.28; and third, the average accuracy is 99 per cent for ANNs model(s) and 97 per cent for MR model(s). On the basis of these results, it is concluded that an ANNs model is superior to a MR model when predicting running cost of building projects.Research limitations/implications– A means for continuous improvement for the performance of the models accuracy has been established; this may be further enhanced by future extended sample.Originality/value– This work extends the knowledge base of life-cycle estimation where ANNs method has been found to reduce preparation time consumed and increasing accuracy improvement of the cost estimation.

Resilience analytics with disruption of preferences and lifecycle cost analysis for energy microgrids

Innovative technologies are presenting opportunities to improve resilience of energy plans for industrial and military installations. The investment rationale is complicated by uncertain future conditions across the system lifecycle, including technology, climate, economy, and others. This paper introduces resilience analytics with scenario-based preferences as follows. Risk is addressed here as the degree of disruption of priorities for investments in engineering systems. The particular concern of this paper is disruption from shifts in public values, and to evaluate the resilience of investment plans to such shifts. It recognizes resilience models as compilations of instantaneous framings of initiatives, objectives, stakeholder preferences, and uncertainties. Problem frames can be considered in series, where inputs to frames are the outputs of previous frames. Or frames can be considered in parallel, featuring joint inputs while addressing differing questions. This paper presents a case study of resilience analytics focusing on two quantitative frames. In the first frame, scenario-based preferences are used to identify combinations of factors disruptive to energy innovation at installations. In the second frame, estimation of lifecycle costs is performed with respect to factors that were identified as influential in the previous frame.

A tool for evaluation of lifecycle cost of water production for small-scale community projects

The aim of this study is to develop an analytical tool to estimate lifecycle cost for water service provision for small-scale community water projects. The primary objective is to provide an analytical estimation tool to governments, funding agencies and communities to ensure sustainability of water projects. The secondary objective is to use the tool as an industry benchmarking aid to empower governments, funding agencies and technology developers to support technologies that would further lower the cost of water production. The tool firstly considers capital expenditure required for a given water service system, focusing on equipment manufacturing costs in detail. Thereafter, it considers the operational expenditure associated with ongoing functioning of the water treatment plant. The developed tool is validated using five simulation scenarios. Results shows that the tool can be used to evaluate the performance of a water service system even if the water services systems are operated using varying strategies. The developed tool also enables effective decision making by testing alternatives and addressing the water service system lifecycle aspects and, thus, making the cost of water production manageable. This paper also introduces the web version of the tool, which is available to communities, governments, technology developers and funding agencies to use.

Simulation-based costing for early phase life cycle cost analysis: Example application to an environmental remediation project

Simulation-based costing (SBC) has been slow to be adopted by the traditional cost estimating community. This can be attributed to many factors, including complexity, how to gather data and develop probabilistic inputs, cost of SBC software, and a lack of understanding of the benefits of developing cost versus risk profiles. This article presents an overview of how SBC can be effectively utilized for early phase life cycle cost (LCC) estimation. A formal process for conducting LCC incorporating SBC is presented not only to provide a structured approach but to also convey to stakeholders how such a study is conducted. This article also presents a case study where total ownership cost versus risk profiles were developed using this proposed process in order to support budgetary and planning considerations for a large environmental remediation project. This research argues that SBC is needed during the concept exploration phase because this is when budgets are often fixed and expectations set.

Estimating Life Cycle Cost of Improved Field Irrigation Canal

The globe is facing an increase in water demand associated with an increase in the world population especially in developing countries. The increasing population urges an additional agricultural land and irrigation water. Traditional system of irrigation water supplier is open canals which allow a high percentage of water dissipation and evaporation. This paper presents a new approach to evaluate design alternatives of Improved Field Irrigation Canals (IFIC) using Life Cycle Cost (LCC) methods. LCC is a methodology for calculating the total cost of a system from inception to disposal taking into account the time value of money. The main objective of this paper is using LCC to evaluate irrigation improvement canals to save water and increase agricultural production. Four methods such: i) Net Present Value (NPV); ii) Benefit/Cost ratio (BCR); iii) Internal Rate of Return (IRR), and iv) Pay Back Period (PBP) are used to compare between three IFIC design alternatives. These alternatives are i) pipeline with one pump at canal head, ii) pipeline with one pump at the head and one pump at the middle, and iii) lined open canal and compared to the reference case; i.e. open canal. Results show that the best economic alternative for IFIC is pipeline with one pump at the intake of the canal.

ESTIMATION OF LONG-TERM INVESTMENT PROJECTS WITH ENERGY-EFFICIENT SOLUTIONS BASED ON LIFE CYCLE COSTS INDICATOR

The starting stage of the tender procedures in Russia with the participation of foreign suppliers dictates the feasibility of the developments for economical methods directed to comparison of technical solutions on the construction field. The article describes the example of practical Life Cycle Cost (LCC) evaluations under respect of Present Value (PV) determination. These create a possibility for investor to estimate long-term projects (indicated as 25 years) as commercially profitable, taking into account inflation rate, interest rate, real discount rate (indicated as 5 %). For economic analysis air-blower station of WWTP was selected as a significant energy consumer. Technical variants for the comparison of blower types are: 1 - multistage without control, 2 - multistage with VFD control, 3 - single stage double vane control. The result of LCC estimation shows the last variant as most attractive or cost-effective for investments with economy of 17,2 % (variant 1) and 21,0 % (variant 2) under adopted duty conditions and evaluations of capital costs (Cic + Cin) with annual expenditure related (Ce+Co+Cm). The adopted duty conditions include daily and seasonal fluctuations of air flow. This was the reason for the adopted energy consumption as, kW∙h: 2158 (variant 1),1743...2201 (variant 2), 1058...1951 (variant 3). The article refers to Europump guide tables in order to simplify sophisticated factors search (Cp /Cn, df), which can be useful for economical analyses in Russia. Example of evaluations connected with energy-efficient solutions is given, but this reference involves the use of materials for the cases with resource savings, such as all types of fuel. In conclusion follows the assent to use LCC indicator jointly with the method of determining discounted cash flows, that will satisfy the investor’s need for interest source due to technical and economical comparisons.

Product life-cycle cost estimation: a focus on the multi-generation manufacturing-based product

Product development (PD) workstream identifies and implements updates into the design of a product in order to keep up with the market demands. PD requires redesigning the product because an optimized strategy for a single generation may not be the best option in the multi-generation scenario. For this purpose, a mathematical model to estimate the product life-cycle cost for a multi-generation manufacturing-based product is proposed. The cost estimation model has three cost constituents: development cost, service cost, and associated risks cost. The article focuses on market risk and technical risk under risks, an element that most previous researchers have missed in their models. Operation risk related to uncertainty during project management has also been considered in the formulation. The model serves as a strategic decision-making tool and provides the guidelines for making project management efficient. This tool is very handy to those design engineers who have a little idea of cost–risk analysis when they design a product. It assists design teams by accurately forecasting and strategically planning a project and by making decisions which are compatible with future generations at a relatively cheaper cost. An empirical case study of a manufacturing-based product (gas turbine) has been discussed to illustrate and justify the use of proposed cost estimation model. The case study has three candidate concepts in the contention, and the best option needs to be selected. After a stringent analysis, concept-3 is found to be the most cost-effective option for most of the instances.

Probabilistic Life Cycle Cost Model for Repairable System

Traditionally, Life cycle cost (LCC) has been predicted in a deterministic approach, however; this method is not capable to consider the uncertainties in the input variables. In this paper, a probabilistic approach using Adaptive network-based fuzzy inference system (ANFIS) is proposed to estimate the LCC of repairable systems. The developed model could handle the uncertainties of input variables in the estimation of LCC. The numerical analysis shows that the acquisition and downtime cost could have a high effect towards the LCC compared to repair cost. The developed model could also provide more precise quantitative information for decision making process.

Sensitivity analysis for water supply input parameters of the CLARA simplified planning tool using three complementary methods

Research Article| February 24 2015 Sensitivity analysis for water supply input parameters of the CLARA simplified planning tool using three complementary methods Atekelt Abebe Ketema; Atekelt Abebe Ketema 1Institute of Sanitary Engineering and Water Pollution Control, University of Natural Resources and Life Sciences, Vienna (BOKU), Muthgasse 18, A-1190 Vienna, Austria Search for other works by this author on: This Site PubMed Google Scholar Guenter Langergraber Guenter Langergraber 1Institute of Sanitary Engineering and Water Pollution Control, University of Natural Resources and Life Sciences, Vienna (BOKU), Muthgasse 18, A-1190 Vienna, Austria E-mail: guenter.langergraber@boku.ac.at Search for other works by this author on: This Site PubMed Google Scholar Journal of Water Supply: Research and Technology-Aqua (2015) 64 (4): 391–403. https://doi.org/10.2166/aqua.2015.126 Article history Received: September 11 2014 Accepted: January 22 2015 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Cite Icon Cite Permissions Search Site Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThis Journal Search Advanced Search Citation Atekelt Abebe Ketema, Guenter Langergraber; Sensitivity analysis for water supply input parameters of the CLARA simplified planning tool using three complementary methods. Journal of Water Supply: Research and Technology-Aqua 1 June 2015; 64 (4): 391–403. doi: https://doi.org/10.2166/aqua.2015.126 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Three sensitivity analysis methods based on derivative, screening and regression are applied to the CLARA simplified planning tool (CLARA-SPT) estimating life cycle cost (LCC) of water supply systems. Derivative-based and standard regression coefficient methods are used to address parameter prioritization and Morris screen method for parameter fixing. The study investigated sensitivity of 26 parameters through three feasible water supply alternatives. The results revealed the importance of all global parameters: period of consideration, net interest rate and expected annual growth rate, for the LCC of all alternatives. The analysis identified ten technological parameters as non-influential, which can be fixed to a certain value. In contrast, two internally fixed parameters (i.e., chlorine dosage and alum dosage) are determined to be important; hence, these parameters need to be available for planners for reasonable cost estimation. Except for period of consideration, all parameters have low standard deviation (σ) value that indicates linear correlation of alternatives' LCC with input parameters and/or insignificant interaction among parameters. This study is valuable for further development of the CLARA-SPT in order to simplify it and to provide guidance for the tool user on the importance of specific input parameters. CLARA simplified planning tool, important parameter, life cycle cost, non-influential parameter, water supply alternatives © IWA Publishing 2015 Supplementary data SUPPORTING MATERIAL- pdf file You do not currently have access to this content.

Life-Cycle Cost–Based Decision Framework for Failed Portland Cement Concrete Pavement Materials in Indiana

The purpose of this study is to create a decision framework based on life-cycle cost (LCC) for failed portland cement concrete pavement (PCCP) materials in Indiana. The Indiana Department of Transportation (DOT) has a standard practice in testing and accepting the construction of PCCP. The challenge, though, is to make informed decisions concerning PCCP sections of failed materials and whether they should be removed and replaced or be accepted with a heavy penalty. This paper presents a decision framework for failed materials based on the long-term performance of PCCP and its LCC. The framework incorporates the PAVESPEC LCC module, a tool package developed as part of the performance-related specifications research efforts. The comparison of as-designed LCC and as-constructed LCC reveals the financial impact of failed PCCP materials. Probability and user confidence were incorporated to address the risk of accepting failed materials because of inferior pavement performance and shortened service life. Many simulations of various failed material scenarios were executed to develop, calibrate, and validate the decision framework. It was found that the interaction between acceptable quality characteristics (AQCs), that is, flexural strength, air content, thickness, and smoothness, had a significant impact on the LCC estimates. This framework was able to capture the composite impact of multiple AQCs deviating from their design target and provides a monetary base for the Indiana DOT to make informed decisions concerning failed PCCP materials.

NEKI ASPEKTI TEHNIČKIH MODELA U SISTEMU UPRAVLjANjA MOSTOVIMA

Bridge Management System (BMS) represents a rational and systematic approach to organizing and conducting of all activities related to bridge maintenance. Main goal of BMS is helping the bridge owner to make an optimal decision with respect to bridge maintenance budget, whether it is dedicated to one bridge or to group of bridges, by securing that the decision is made on the basis of Life-Cycle Cost (LCC) estimates. The structure of BMS is based on condition rating and Bridge Database (BD), Deterioration model (DM), Cost Model for evaluation of costs and Optimization Model for choosing the most rational maintenance strategy. Relationship between bridge condition rating and DM with maintenance costs within BMS is very important. Predictions regarding future intensity and rate of bridge deterioration depends on multitude of factors and it is a consequence of several simultaneous actions and deterioration processes (DP) which need to be included into DMs. DMs are mostly based on modeling of physical and chemical actions and processes or they are based on statistical analysis of large number of data regarding the condition of existing bridges, or on artificial intelligence models, etc. Stochastic models based on Markov processes are applied within more advanced contemporary BMS. Due to social and economic circumstances and lack of financial resources over the last two decades in Republic of Serbia bridge maintenance was neglected and creation of BD was discontinued. The paper deliberates some aspects of technical models within BMS, with DMs being pointed out, development of BD within bridge maintenance in Republic of Serbia and it gives an overview of sophisticated BMS and current advances in this field.

IDENTIFICATION OF THE KEY FACTORS FOR ACCURATE LIFE-CYCLE COST ESTIMATION FOR CONSTRUCTION

A major limitation of Life-Cycle Cost (LCC) estimation/prediction modelling is the current typical reliance only on those factors that can be readily quantified and come easily to hand. While estimation of the cost of the most common labor, material and plant resources receive consideration because of their high visibility factor, there are several non-cost factors (low visibility factors) affecting the estimate that are often overlooked and, it is argued here, require equal consideration in estimation processes that seek optimum accuracy. Unfortunately, such (low-visibility) factors are neglected or ignored by current prediction models. Identification of these non-cost factors (low visibility factors) affects LCC estimate accuracy and can improve estimation process confidence. This paper critically reviews secondary research on identification of these important non-cost factors and subsequently determines their influence on the accuracy level(s) of construction cost estimation.

Development of a Product Life-Cycle Cost Estimation Model to Support Engineering Decision-Making in a Multi-Generational Product Development Environment

The research under product development domain identifies and implements new concepts in design, planning, manufacturing, testing, and service sectors to keep up with the market demands. Many product developments are multi-generational in nature and may require redesigning the product at each generation because an optimized strategy for a single generation may not be the best option in the multi-generation scenarios. With this regard, this article proposes a novel product life-cycle cost estimation model to support engineering decision-making in a multi-generational product development environment. This cost estimation model develops a mathematical formulation which has three major cost constituents: development cost, service cost, and associated risks cost. The risks cost further includes three components coming from technical risk, market risk, and operation risk. The developed mathematical formulation measures the on-going multi-generational product development’s status, addresses its basic needs such a...

Research on the Highway Engineering LCC Estimation Modular Platform

The highway engineering is an important area for investment in infrastructure construction in China, in the stage of engineering design, to solve the difficult problem of life cycle cost estimates, the paper builds the highway engineering life-cycle cost estimation modular conceptual model, and develops the highway engineering LCC estimation modular platform under the model. It provides a practical way for the highway life cycle cost measuring, and presents a new idea for life cycle cost estimation model.

2.3.1 A MBSE probabilistic framework for preliminary lifecycle costing of mechanical products

AbstractThe challenging economic context and competitive pressure forces industrial companies to attain the highest profitability of a program, with lifecycle cost (LCC) as one of the key parameters. Thus, industrial companies are constantly developing more efficient methods to estimate LCC as early as possible in the design process. This paper presents a new Model Based Systems Engineering (MBSE) probabilistic framework for lifecycle cost estimation during preliminary design. Divided in two modules computing respectively manufacturing and maintenance costs, the framework is based on a suite of statistical regression‐based models whose results are aggregated in order to provide the best probabilistic estimate of lifecycle cost. The framework has been tested on components from civil jet engines but can be applied to a large variety of mechanical products. The early results are satisfactory with predictive accuracy of lifecycle costs of new components representing a significant improvement over state‐of‐the‐art methods.

Estimation of tractor life cycle cost

Methodological issues of tractor life cycle cost estimation are considered. Recommended calculation methods of the basic components of total costs for life cycle or for arbitrary period of use are given. An example of the developed method using for calculation of a tractor life cycle cost is given.

Energy recovery consideration in brackish water desalination

In brackish water RO desalination, the low feed water TDS and relatively low brine flow make the use of energy recovery devices ambiguous. The decision to implement energy recovery device must always be based on the Life Cycle Cost estimation of the plant. Design considerations concerning the energy recovery device selection and field experience in Lahat brackish water desalination plant (40,000m3/day) are presented in this article.Two types of energy recovery device are generally considered in the brackish water RO desalination, turbocharger and isobaric energy recovery devices. Taking into consideration the simplicity of the turbocharger, it was selected for the 1st phase of the Lahat brackish water desalination plant with the design recovery range of 80%–88%. The turbocharger was designed for max recovery and external bypass line was added to operate the plant at low recoveries. For such wide recovery range the turbocharger entire efficiency range of 30%–40% was achieved.Due to the limitation of the turbocharger to operate efficiently at the broad recovery range and Life Cycle Cost benefits of isobaric energy recovery device, the isobaric energy recovery device was selected for the 2nd phase of the Lahat brackish water desalination plant.

Integrating Reliability Analysis in Life Cycle Cost Estimation of Heat Exchanger and Pump

This paper presents a mathematical model to estimate the life cycle cost (LCC) of heat exchanger and pump. Maintenance cost, down time cost and acquisition costs are calculated. The main uncertainty in calculating these costs are prediction of number of failure and cumulative down time. Number of failure is determined using failure and repair time density function. According to the characteristic that the cumulative failure probability observed, a Weibull distribution model is used. The scale and shape parameters of the Weibull are extracted from the published data. The results of the study show that 71.3% loss in the reliability of heat exchanger and 34.2% reliability loss in pump could lead to 66.2 % increment of the total cost. The reliability of the system decreases because of number of failures will increase each year, and this failure leads to unavailability of the system.Therefore in order to achieve higher system effectiveness and reduce the total LCC, the reliability of the systems need to be increased through proper maintenance policies and strategies. The results of the study could assist the managers to make decision with high degree of accuracy.

A suggested framework for product life cycle cost analysis at product design stage

This paper provides a framework for life cycle cost analysis of products at the design stage based on reliability and maintainability parameters. When dealing with reliability field data, proper selection of models for time-to-failure data is essential as it affects the expected number of failures. The conventional time-to-failure analysis techniques rely on the major assumption of independent and identically distributed time between failures which is, in fact, not appropriate for all systems. This can lead to erroneous model selection for time-to-failure of a system leading to erroneous estimates of life cycle costs. To overcome this, a framework directed towards proper selection of time-to-failure model and a procedure for life cycle cost analysis is presented. The application of the proposed methodology is illustrated with two case studies by comparing the costs predicted by the proposed model with the costs that are actually experienced. It is found that the model correctly predicts each product’s life cycle cost as actually experienced by these products.

Exploiting Architectural Communities in Early Life Cycle Cost Estimation

System architectures evolve over time. Accordingly, the dynamic properties of architectures reflect how systems respond to change, and this response ultimately impacts cost. In prior work we make an explicit connection between the architectural diagrams of Model-Based Systems Engineering (MBSE), parametric cost estimation, and network science. Specifically, by treating the DoD Architecture Framework (DoDAF) Systems View 3 (SV3) as an adjacency matrix, we assess how the addition of a new subsystem to an immature architecture might grow the existing network. With the subsequent application of parametric cost modeling, we translate anticipated growth into expected cost, thereby quantifying the impact of change. This paper refines that approach. In particular, by using the Girvan-Newman algorithm, the SV3 is initially divided into groups of subsystems such that the number of interfaces is dense within and sparse between groups. Based on this division into “architectural communities” and the prevalence of bridging ties, interfaces generated by the addition of a new subsystem can be faithfully integrated into the existing architecture, adding validity to our growth mechanism. This procedure is illustrated in detail with an example that highlights the importance of this refinement, and it is incorporated within a Monte Carlo simulation that allows the distribution of future costs to be estimated and assessed.