Significant Factors Affecting the Life Cycle Cost Elements of a Building

Purpose This paper aims to identify the main non-cost factors affecting accurate estimation of life cycle cost (LCC) in building projects. Design/methodology/approach Ten factors affecting LCC in building project cost estimates are identified through literature and interviews. A questionnaire survey is conducted to rank these factors in order of priority and provide the views of cost practitioners about the significance of these factors in the accurate estimation of LCC. The data from 138 construction building projects completed in UK were collected and analysed via multiple regression to discover the relationship between capital and LCCs and between non-cost factors and cost estimation at each stage of the life cycle (capital, operation, maintenance and LCC). Findings The results of analysis of existing LCC data of completing project and survey data from cost professionals are mostly consistent with many literature views and provide a reasonable description of the non-cost factors affecting the accuracy of estimates. Originality/value The value of this study is in the method used, which involves analysis of existing life data and survey data from cost professionals. The results provide a plausible description of the non-cost factors affecting the accuracy of estimates.

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The Application of Blockchain-Based Life Cycle Assessment on an Industrial Supply Chain

10.20944/preprints202110.0441.v1 ◽

2021 ◽

Author(s):

Xuda Lin ◽

Xing Li ◽

Sameer Kulkarni ◽

Fu Zhao

Keyword(s):

Life Cycle Assessment ◽

Supply Chain ◽

Life Cycle ◽

Inventory Data ◽

Specific Data ◽

Factors Affecting ◽

Block Chain ◽

New Framework ◽

Significant Factors

Life Cycle Assessment (LCA) is a widely recognized tool used to evaluate environmental impacts of a product or process, based on the environmental inventory database and bills of material. Data quality is one of the most significant factors affecting the analysis results. However, currently most datasets in inventory databases are generic i.e., they may represent material and energy flow of a process at market average, instead of a specific process used by a manufacturer. As a result, stockholders are unable to track their supply chain to find out the actual environmental impact from each supplier and to compare the environmental performance of alternative options. In this paper, we developed a new framework i.e., blockchain based LCA (BC-LCA), where block-chain technology is adapted to secure and transmit inventory data from upstream suppliers to downstream manufacturers. With BC-LCA, more specific data can be acquired along the supply chain in a real-time manner. Moreover, the availability, accuracy, privacy, and automatic update of inventory data can be improved. A case study is provided based on an industrial supply chain, to demonstrate the utilization of BC-LCA.

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APPLICATION OF COST SIGNIFICANT ITEMS TOWARDS IMPROVING ESTIMATION FOR LIFE CYCLE COSTING OF BUILDING PROJECTS

Proceedings of International Structural Engineering and Construction ◽

10.14455/isec.res.2015.227 ◽

2015 ◽

Vol 2 (1) ◽

Author(s):

Ayedh Alqahtani ◽

Andrew Whyte

Keyword(s):

Life Cycle ◽

Life Cycle Cost ◽

Construction Projects ◽

Significant Cost ◽

Building Projects ◽

Factors Affecting ◽

Complicated Process ◽

Collection Data ◽

Management Effort ◽

Cost Factors

Construction projects have numerous variable factors affecting the value of life cycle-cost (LCC) and there is interaction between these factors, leading to complicated process. Therefore the current LCC models suffer from the absence of a standardized and a simple methodology of both the collection data and estimation LCC. Identification of the significant cost factors affecting the output of LCC is important step before embarking upon the collection of progress information. Furthermore, components of construction differ in their cost and time-importance, and thus management effort must be equivalently distributed. The concept of cost significant items (CSIs) is the best method to simplify estimation methodology as well as the collection data of construction projects. In general, The CSIs concept aims to determine the small number of items which represent a constant percentage of the LCC of construction projects. Therefore, this paper aims to present the explanation of each stage of LCC, the current classifications of asset components, the CSIs concept and previous practice of the significant cost items on the construction sector.

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The Application of Blockchain-Based Life Cycle Assessment on an Industrial Supply Chain

Sustainability ◽

10.3390/su132313332 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13332

Author(s):

Xuda Lin ◽

Xing Li ◽

Sameer Kulkarni ◽

Fu Zhao

Keyword(s):

Life Cycle Assessment ◽

Supply Chain ◽

Life Cycle ◽

Inventory Data ◽

Specific Data ◽

Factors Affecting ◽

Blockchain Technology ◽

New Framework ◽

Significant Factors

Life cycle assessment (LCA) is a widely recognized tool used to evaluate the environmental impacts of a product or process, based on the environmental inventory database and bills of material. Data quality is one of the most significant factors affecting the analysis results. However, currently, most datasets in inventory databases are generic, i.e., they may represent the material and energy flow of a process at a market average, instead of a specific process used by a manufacturer. As a result, stockholders are unable to track their supply chain to find out the actual environmental impact from each supplier and to compare the environmental performance of alternative options. In this paper, we developed a new framework, i.e., blockchain-based LCA (BC-LCA), where blockchain technology is adapted to secure and transmit inventory data from upstream suppliers to downstream manufacturers. With BC-LCA, more specific data can be acquired along the supply chain in a real-time manner. Moreover, the availability, accuracy, privacy, and automatic update of inventory data can be improved. A case study is provided based on an industrial supply chain to demonstrate the utilization of BC-LCA.

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A Method of Determining Rail Grinding Parameters Based On Life-Cycle Cost

The Open Mechanical Engineering Journal ◽

10.2174/1874155x01408010544 ◽

2014 ◽

Vol 8 (1) ◽

pp. 544-550 ◽

Cited By ~ 1

Author(s):

Wang Jianxi ◽

Chen Siyi ◽

Gui Jirong

Keyword(s):

Life Cycle ◽

Service Life ◽

Life Cycle Cost ◽

Economic Cost ◽

Present Value ◽

Factors Affecting ◽

Optimal Analysis ◽

Rail Grinding ◽

Grinding Parameters ◽

Rail Service

The factors affecting the economy efficiency of rail grinding and their interrelation are researched. Based on the management theory of life-cycle cost, the model of analyzing rail grinding parameters is established, the calculation method is determined, and minimizing the rail life-cycle cost is regarded as optimization objective for the optimal analysis of grinding factor. The results prove that with certain parameters (grinding interval and mental removal), the total present value of rail cost tends to decrease firstly and then increase with the increase of rail service life. With the increase of the grinding interval, the total present value of rail cost also tends to decrease firstly and then increase, and there is an extreme point in the variation tendency. In the economic cost of rail service life, rail replacement and waste of railway taking-up cost are two of the biggest parts. Therefore, reasonable rail maintenance strategy plays a significant role in reducing life-cycle cost.

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

Proceedings of International Structural Engineering and Construction ◽

10.14455/isec.res.2014.73 ◽

2014 ◽

Vol 1 (1) ◽

Author(s):

Ayedh Alqahtani ◽

Andrew Whyte

Keyword(s):

Life Cycle ◽

Cost Estimation ◽

Life Cycle Cost ◽

Prediction Models ◽

Key Factors ◽

Plant Resources ◽

Factors Affecting ◽

Low Visibility ◽

The Cost ◽

Cost Factors

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.

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