An Application of a Generalized Life Cycle Cost Model to a Typical Pump From Industry

2009 ◽  
Author(s):  
L. Y. Waghmode ◽  
A. D. Sahasrabudhe
Keyword(s):  
Life Cycle ◽  
Life Span ◽  
Life Cycle Cost ◽  
Cost Model ◽  
Life Time ◽  
Maintenance Cost ◽  
Repairable System ◽  
Repairable Systems ◽  
Generalized Model ◽  
Mean Time

The objective of this paper is to develop a methodology for effective implementation of life cycle costing (LCC) in design and procurement of repairable and non-repairable products. For this purpose, a generalized model for LCC of repairable and non-repairable products has been proposed. The equations of cost components of the proposed generalized model have been formulated for repairable systems based on the reliability and maintainability aspects to enable the life-time cost conscious design of such systems. The repairable systems typically have a life span of 10 to 20 years and experience multiple failures over their life span. The life cycle cost of a repairable system is significantly influenced by its reliability and maintainability. The life time energy and/or maintenance cost often dominate LCC for most of the repairable systems. Under the condition of constant failure rate the repairable system reliability is characterized by mean time between failures (MTBF) and maintainability by mean time to repair (MTTR). A higher value of MTBF and lower value of MTTR results into lower life cycle cost and therefore a due consideration to these factors is essential while designing repairable systems. The generalized LCC model presented in this paper will assist the designers to compare the life cycle cost of their different design alternatives at product design phase wherein most of the life cycle costs are committed. The developed generalized LCC model is applied to a typical repairable system, a pump from industry and the results obtained are presented.

On the Expected Number of Failures and Maintenance Cost Prediction of Repairable Systems From Life Cycle Cost Modeling Perspective

2010 ◽  
Author(s):  
Laxman Yadu Waghmode ◽  
Anil Dattatraya Sahasrabudhe
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Life Time ◽  
Maintenance Cost ◽  
Repairable System ◽  
Repair Cost ◽  
Repairable Systems ◽  
Expected Number ◽  
Maintenance And Repair ◽  
Repair Costs

The objective of this paper is to provide some useful insights on how cost driving events are related to the characteristics of failure distributions and the product lifetime (design life) in case of repairable systems. Repairable systems are those that can be restored to their fully operational capabilities by any method, other than the replacement of the entire system. In case of repairable systems, the components can be repaired or adjusted rather than replaced, whenever a breakdown occurs and thus such systems experience multiple failures over their life span. For majority of repairable systems, the life time maintenance and repair costs dominate the life cycle cost. To predict the maintenance and repair cost, failure data, maintenance data and repair time data is needed which is not readily available at the system design stage. When a repairable system is put into service, how many times it will fail over its life span depends on its reliability. Similarly, how fast the system is restored to its working condition when it fails (maintainability), also affect the costs incurred. Thus, the expected number of failures, time lost in restoring the system after each failure and cost per failure are important from life time maintenance cost prediction viewpoint. The expected number of failures depends upon the time to failure distribution of the system components and the after repair state of the system. In this paper, a modeling methodology is suggested for prediction of life time maintenance and repair cost of repairable systems based on expected number of failures. The repairable system lifetime is modeled using a two parameter Weibull distribution. The expected number of failures are estimated for renewal process (as-good-as-new after repair state) and minimal repair process (as-bad-as-old after repair state). The expected maintenance and repair costs are also evaluated for six different failure distributions. The technique has been illustrated through a specific application, namely an industrial pump and the results are presented.

An Application of a Generalized Life Cycle Cost Model to BOXN Wagons of Indian Railways

2010 ◽  
Author(s):  
Laxman Yadu Waghmode ◽  
Anil Dattatraya Sahasrabudhe
Keyword(s):  
Life Cycle ◽  
Life Span ◽  
Life Cycle Cost ◽  
Life Cycle Costing ◽  
Design Stage ◽  
Railway Vehicle ◽  
Repairable System ◽  
Initial Product ◽  
Finished Steel ◽  
Railway Industry

The objective of this paper is to apply a methodology developed for effective implementation of life cycle costing (LCC) in design and procurement of repairable products/systems to railway wagons. From its origin in defense equipment in US in 1960s, the application of life cycle cost concept has now been extended to other areas of private and public sectors too. This is because the customers are now considering not only the initial product costs but also the cost implications associated with the entire life span of a product. This emerging trend in global markets is gradually forcing the product manufacturers to estimate and optimize the product LCC with reference to performance, safety, reliability (R), and maintainability (M). The life cycle cost of a repairable system is closely coupled to its reliability and maintainability and therefore a careful consideration to the R & M parameters in the product design stage is quite essential from the LCC viewpoint. Taking into consideration these aspects a generalized modeling methodology has been proposed to estimate the life cycle cost of repairable products based on R & M principles. Life cycle costing in railway industry has traditionally been focused on the prediction of investment of railway vehicle. But, today’s mass transit market has rapidly been changed and the suppliers are now forced to treat the LCC of entire railway system. Indian railways are the principle mode of transport for raw materials for steel plants, finished steel from steel plants, coal, oil, iron, cement, petroleum products, fertilizers and food grains in India. To serve this purpose BOXN wagons are used by Indian railways. The BOXN wagons typically have a life span of 35 years and being a repairable system experience multiple failures over their life span. In this paper, a generalized model for LCC of repairable products has been proposed and is applied to BOXN wagon of Indian railways and the results obtained are presented. The methodology presented herein is expected to provide some useful guidelines to the railway industry to predict and analyze the life cycle cost of railway vehicles.

scholarly journals Life-cycle cost of bridges – first steps to a holistic approach

2016 ◽  
Vol 11 (2) ◽  
pp. 169-178 ◽  
Author(s):  
Václav Beran ◽  
Daniel Macek ◽  
Dana Měšťanová
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Benefit Analysis ◽  
Cost Model ◽  
Life Time ◽  
Holistic Approach ◽  
Transport Infrastructure ◽  
Benefit Analysis ◽  
High Investment ◽  
Cost And Benefit Analysis

Bridges create transport infrastructure and are subjected to long term witness of economic design, reliability, durability, maintainability and external risk (natural and human hazards). Deficient design of bridges points to high investment costs, low quality, retrofits maintenance costs, mitigates quality damages. The primary reason of the problem is usually stated high investment costs. Resources for investment are limited over and over again. However, approach for evaluating and comparing the cost effectiveness in practical design does not dominate in present-days as arbitration of different strategies and warrant for avoiding critical economic or functional situations. This paper illustrates a method for estimating the retrofits for bridges design based on Life-Cycle Costs and Cost-Benefit Analysis. The approach integrates cost model, fragility of as-designed and retrofitted benefits for a range of externalities and associated potential changes in design and economical retrofit. The emphasis on life-time performance and benefits, as opposed to initial retrofit acquisition investment cost alone, paves the way to risk-wise investment and also helps to support upgrade actions for sustainable infrastructure. An application of the holistic approach Life-Cycle Cost and benefit analysis is conducted for two representative bridges of highway class. The available financing has a big influence on the chosen technical design.

A Spreadsheet Life Cycle Cost Model for System Modernization Studies

1994 ◽  
Vol 11 (1) ◽  
pp. 47-56
Author(s):  
Virginia C. Day ◽  
Zachary F. Lansdowne ◽  
Richard A Moynihan ◽  
John A. Vitkevich
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Model

Hazardous Material Life-Cycle Cost Model. System User's Guide. Version 1.2.

1994 ◽  
Author(s):  
Bonnie J. LaFleur ◽  
Jennifer A. Jaeger ◽  
Lawrence A. Hermansen
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Cost Model ◽  
Model System ◽  
Hazardous Material ◽  
Material Life

scholarly journals Life Cycle Cost of Electricity Production: A Comparative Study of Coal-Fired, Biomass, and Wind Power in China

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3463
Author(s):  
Xueliang Yuan ◽  
Leping Chen ◽  
Xuerou Sheng ◽  
Mengyue Liu ◽  
Yue Xu ◽  
...  
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Wind Power ◽  
Life Cycle Cost ◽  
Raw Material ◽  
Electricity Production ◽  
Maintenance Cost ◽  
External Cost ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity

Economic cost is decisive for the development of different power generation. Life cycle cost (LCC) is a useful tool in calculating the cost at all life stages of electricity generation. This study improves the levelized cost of electricity (LCOE) model as the LCC calculation methods from three aspects, including considering the quantification of external cost, expanding the compositions of internal cost, and discounting power generation. The improved LCOE model is applied to three representative kinds of power generation, namely, coal-fired, biomass, and wind power in China, in the base year 2015. The external cost is quantified based on the ReCiPe model and an economic value conversion factor system. Results show that the internal cost of coal-fired, biomass, and wind power are 0.049, 0.098, and 0.081 USD/kWh, separately. With the quantification of external cost, the LCCs of the three are 0.275, 0.249, and 0.081 USD/kWh, respectively. Sensitivity analysis is conducted on the discount rate and five cost factors, namely, the capital cost, raw material cost, operational and maintenance cost (O&M cost), other annual costs, and external costs. The results provide a quantitative reference for decision makings of electricity production and consumption.

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