CHEMICAL ENGINEERING TRANSACTIONS
VOL. 62, 2017
A publication of
The Italian Association
of Chemical Engineering
Online at www.aidic.it/cet
Guest Editors: Fei Song, Haibo Wang, Fang He
Copyright © 2017, AIDIC Servizi S.r.l.
ISBN 978-88-95608- 60-0; ISSN 2283-9216
Study on the Life-Cycle Engineering Cost Management of
Large Chemical Projects
Yong Gu
Langfang Teachers University, Langfang 065000, China
gy_syc@sohu.com
This paper conducted a study on the life-cycle engineering cost management of large chemical projects, with
the purpose of standardizing the management process and reducing the costs at all stages. Specifically, the
LCC analysis method was adopted to analyze the life cycle cost of large-scale chemical engineering projects
through detailed introduction to the theory, cost structure and cost analysis steps, based on which the all-
factor LCC model of large-scale chemical projects was established. Finally, through the determination of
constraints, the optimization of the life-cycle engineering cost model for large-scale chemical projects was
realized. This research is helpful to strengthen the engineering cost management for large-scale chemical
projects at all stages, and is instructive for the investment decision in large-scale chemical engineering
projects.
1. Introduction
In the context of global economic growth slowing down and commodity prices continuing to fall, the downward
pressure on the domestic economy has been increasingly growing. And the petroleum and chemical industries
are facing more and more fierce competition worldwide (Demeulemeester, 2015; Zhong and Zhang, 2006). In
order to reduce the engineering cost and improve economic efficiency comprehensively, all major
petrochemical enterprises have paid more attention to the management of engineering costs, so as to reduce
the life-cycle engineering cots of large-scale chemical projects (Jiang, 2002).
The schedule, cost, quality and safety of large-scale chemical projects are the four major elements of project
management, among which cost management is directly related to the project costs (Gluch and Baumann,
2004). The engineering cost is the manifestation of the monetary cost in all stages of the project, which is
reflected in the decision-making phase, implementation phase, operations phase and closure phase of the
large-scale chemical projects (Guo and Zhang, 2015). Although the decision-making phase takes fewer costs
out of all engineering costs, it affects the total engineering costs by over 90% (Nikolay, 2016). Therefore, it is
necessary to improve the life-cycle cost management of large chemical projects life cycle, especially during
the feasibility and design phase (Kirk and Dell'Isola, 1995).
This paper first gave an overview of the LCC (Life Cycle Costing) theory, analyzed the composition of
engineering costs in each phase of the project, and then used the LCC method to analyze other factors that
affect the engineering costs of large-scale chemical projects based on the classic LCC model to established
an all-factor model for large chemical projects; Finally, the life-cycle engineering costs of large-scale chemical
projects optimization were optimized by setting constraints.
2. Analysis of life cycle costs of large chemical project
2.1 Overview of LCC analysis theory
LCC analysis is an effective tool for analyzing investment decisions in engineering projects that was proposed
in the cost management industry of Western countries in the 1980s (Swarr et al., 2011; Morris, 2010). LCC
contains two basic points, namely the total costs that are directly related to products and consumed in the life
cycle, and the correlation between LCC and the time value of funds. Also, the LCC analysis includes three
main contents (Liang, 2014). First, determine the elements of the life cycle costs, and minimize the cost of
DOI: 10.3303/CET1762245
Please cite this article as: Yong Gu, 2017, Study on the life-cycle engineering cost management of large chemical projects, Chemical
Engineering Transactions, 62, 1465-1470 DOI:10.3303/CET1762245
1465
each element (Cleary et al., 2015). Second, associate life-cycle costs and system efficiency. Third, research
the relationship between life-cycle costs and system efficiency (Emblemsvåg, 2003).
2.2 Breakdown of life cycle costs of large-scale chemical projects
The breakdown of the life cycle costs of a large-scale chemical project corresponds to the four phases of the
project, namely the decision-making phase (Zhang, 2005), the implementation phase, the operations phase
and the project closure phase (He and You, 2016).
(1) Decision-making phase and implementation phase
In the decision-making stage, the main construction contents and supporting facilities of the proposed
chemical project are analyzed, such as raw material supply, process-oriented pipelines, equipment selection,
environmental impact, and economic effect (Lenior and Verhoeven, 1990; Kohl and Wulke, 2004). As for the
implementation stage, costs can be divided into design costs and construction costs. The design covers the
total layout, process and technologies, and the overall design of various aspects, while the construction mainly
refers to the construction based on the design drawings of all aspects, including manpower, materials,
equipment loss, etc. (Peñamora et al., 1999; Bhimani, 1994). The cost compositions in the decision-making
phase and the implementation phase are shown in Figure 1:
Figure 1: The Cost Composition in the Project Decision Stage and Implementation Stage
(2) Operations phase and project closure phase
Operational costs mainly represent all costs incurred during the equipment operations in a chemical project,
including costs for production, and equipment renewals and maintenance (White and Fortune, 2002; Ruiz-
Martin and Poza, 2015). And the costs in the project closure phase mainly refer to the costs generated in the
refurbishment or demolition phase of major chemical equipment (Stevens, 1986; MehranSepehri, 2012). The
costs in the operations phase and the project closure phase can be seen in Figure 2:
Figure 2: The Cost Compositions in the Project Operating Stage and Closure Stage
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2.3 Steps to analyze life-cycle costs of large-scale chemical projects
According to the characteristics of large-scale chemical projects, life-cycle cost analysis can be divided into
seven steps as follows (Yu et al., 2006; Chen, 2003). Firstly, determine the research target and identify the
target requirements and performance parameters. Secondly, propose a number of feasible plans that meet the
performance requirements of the project. Thirdly, establish a life-cycle costs estimation model (Ogihara et al.,
2003; Hollmann and Querns, 2003). Fourthly, collection data and information to make different assumptions
about discount rates, inflation rates, economic lifetimes, etc. Fifthly, calculate the life-cycle costs of each plan.
Sixthly, choose the optimal plan. Seventhly, give decision-making recommendations (Zakeri and Syri, 2015).
Figure 3 displays the process of analysis of large-scale chemical projects’ life cycle costs.
Figure 3: Large-scale Chemical Project Life Cycle Cost Analysis Process
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3. Life cycle cost models of large-scale chemical projects
3.1 Basic LCC Model
The life cycle cost estimation methods for engineering projects have changed from the initial static estimation
model into a dynamic estimation model with consideration of the time value (Zapalac et al., 1994). Despite
different manifestations, models, in essence, all consider the project's initial construction fee, operating
expenses, end-of-use disposal costs, and the time value of money (Ferchichi et al., 2015). The classic LCC
estimation model is shown in Formula 1.
LCCpv=K0+M0+i=1T(Kt+Mt+Et)(1+r)t-VT1+rT (1)
In the formula, LCCpv is the total costs, and K0 and M0 refer to the investment cost and management cost of
the chemical project in 0 year respectively. Kt and Mt are the investment cost and management cost of the
project in the tth year respectively. Et means other costs in the he tth year, with VT as the residual value of the
chemical project and T as the life of the project.
In fact, due to the long investment cycle of large-scale chemical projects, both the internal and external
investment environment in the project implementation stage are changing. At the same time, due to the impact
of changes in raw materials, product demands, labor costs and investment environment on the costs of
chemical projects, the accuracy of this model remains to be improved.
3.2 All-factor LCC model of large-scale chemical projects
Considering the time value of funds, the author introduced the idea of real options to correct the project value
changes caused by the uncertainties such as the changes in the real value in the construction process. And
based on the project’s risk cost, quality risk cost, safety risk cost, and environmental risk cost, the all-factor
LCC model of large-scale chemical projects was obtained, as shown in Formula 2.
LCCpv=t=0T1-1i=1nPit(1+r)-t+t=T1T1+T2-1i=1nCit1+r-t+t=T1+T2T1+T2+T3-1i=1nRit1+r-t+t
=0T1+T2+T3-1i=1nQit1+r-t-i=1nVTi1+r-T1+T2+T3+ROs
(2)
In the formula, LCCpv denotes the total discounted value, and Pit, Cit, Rit, and Qitt represent the decision-
making and research costs, design and construction costs, operating cost, and the discounted value of factors
of the device i in the tth year respectively. VTi refers to the end-of-use disposal residue value of the device i.
T1, T2, and T3 respectively mean the decision-making and research time, design and construction time, and
operations time. R represents the discount rate, and ROs represents the real option value of the chemical
equipment. The above model involves the life cycle costs of chemical engineering projects at all stages, cost
of influencing factors, real option value of the project, and the time value of funds for the above expenses,
making it an open all-factor LCC model (Liu et al., 2012).
3.3 Life-cycle engineering costs optimization for large chemical projects
The optimization is to reduce the construction cost under the guidance of LCC theory by selecting the
decision-making variables and establishing the optimization objective function and constraints. And then the
global optimal costs is achieved by realizing local optimal costs at all stages of the life-cycle engineering costs
of chemical projects.
The main objectives of LCC optimization are multiple feasibility plans in the project decision-making phase.
The optimization covers the construction scale, product solutions, raw material and fuel power supply
solutions, process technology and equipment plans, utilities and supporting facilities solutions, environmental
protection solutions, and operating costs and benefits in the operating stage.
3.3.1 Constraints
LCC optimization needs to meet the basic requirements of various technologies. P (x) is a function of the
design scheme. YsX, YTX, YFX, YEVX, YENX, and YAX respectively represent the standard norms
constraint, skills performance constraint, functional constraint, environmental constraint, energy consumption
constraint, and aesthetic constraint, with all the constraints no more than P (x).
3.3.2 Optimized model
Bring the constraints into Formula (2) to obtain the optimized all-factor LCC model. As shown in Formula 3,
the model can give the lowest life cycle engineering costs plan, a satisfactory result.
LCCpv=i=0T1-1i=1npi=1pnkpiit(1+r)-t+t=T1T1+T2-1i=1n[ci-1cnYciit+ck-1clpckit×Lckit×1+
dckit+fit(h)(1+r)-t]+t=T1+T2T1+T2+T3-1i=1n[(rj=1rmmrjit+rk=1reerkit+rl=1rssrlit+rh=1rwwrhit)×
(1+r)-t]+t=0T1+T2+T3i=1nQit(1+r)-t-i=1nRie×if=1igEif-Wic-Wi×1+r-T1+T2+T3+ROs
(3)
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=f(p)+f(c)+f(r)+f(q)-f(v)+f(s)
In the formula, f(p) is the present value cost (PVC) function at the decision-making stage, with f(c) as the PVC
function at the project implementation stage, f(r) as the PVC function at the operating stage, f(q) as the PVC
function of factors influencing the project costs, f(v) as the present residual value function at the waste
disposal phase, and f(s) as the present value function of the real option of the project.
The mathematical optimized LCC model can be expressed as Formula (4):
minLCCpv=W[ f(p)+f(c)+f(r)+f(q)-f(v)+f(s)] (4)
Since it is extremely difficult to find the global optimal solution directly from the above formula, for specific
projects, only a few major factors can be considered to establish a simplified mathematical model to find the
local optimal solution to the costs.
4. Conclusion
In order to optimize the management of life-cycle engineering costs of large-scale chemical projects and
optimize the investment decisions in chemical projects, this paper conducted relevant studies by following the
LCC theory. The main innovations are as follows:
(1) The structure of life cycle costs of large-scale chemical projects has been identified, as well as cost
analysis steps.
(2) In line with the basic LCC model, an all-factor LCC model for large-scale chemical projects has been built
by taking the factors such as quality, safety and environment into consideration. Additionally, the model has
been optimized based on the constraints, leading to the optimized all-factor LCC model for the investment
decision-making in large-scale chemical engineering projects.
Reference
Bhimani A., 1994, Modern cost management: putting the organization before the technique, International
Journal of Production Economics, 36(1), 29-37.
Chen G. S., 2003, A study of the intra-organization co-ordination cost in an enterprise. Journal of Beijing
Institute of Technology.
Cleary J., Wolf D.P., Caspersen J.P., 2015, Comparing the life cycle costs of using harvest residue as
feedstock for small- and large-scale bioenergy systems (part ii), Energy, 86, 539-547, DOI:
10.1016/j.energy.2015.04.057
Demeulemeester E., 2015, Effective expediting to improve project due date and cost performance through
buffer management, International Journal of Production Research, 53(5), 1460-1471, DOI:
10.1080/00207543.2014.948972
Emblemsvåg J., 2003, Life-cycle costing: using activity-based costing and monte carlo methods to manage
future costs and risks, Naval Engineers Journal, 81(2), 42–50.
Ferchichi A., Boulila W., Farah I.R., 2015, Improvement of LCC Prediction Modeling Based on Correlated
Parameters and Model Structure Uncertainty Propagation, International Joint Conference on
Computational Intelligence, Springer International Publishing, 270-290, DOI: 10.1007/978-3-319-48506-
5_14
Gluch P., Baumann H., 2004, The life cycle costing (lcc) approach: a conceptual discussion of its usefulness
for environmental decision-making, Building & Environment, 39(5), 571-580, DOI:
10.1016/j.buildenv.2003.10.008
Guo D., Zhang C., 2015, Evaluation of cost management controlling system in petroleum enterprise, Open
Petroleum Engineering Journal, 8(1), 358-362.
He C., You F., 2016, Deciphering the true life cycle environmental impacts and costs of the mega-scale shale
gas-to-olefins projects in the United States, Energy & Environmental Science, 9(3), 820-840, DOI:
10.1039/c5ee02365c
Hollmann J. K., Querns W. R., 2003, The total cost management (tcm) framework 1. Introduction, Aace
International Transactions.
Jiang X.L., 2002, The role of project cost management in local economic and social development, Human
Molecular Genetics, 11(26), 3345-3350.
Kirk S.J., Dell'Isola A.J., 1995, Life cycle costing for design professionals, McGraw-Hill.
Kohl B., Wulke R. J., 2004, Supplementing accounting systems for project cost management, Aace
International Transactions, IT31.
1469
Lenior T.M.J., Verhoeven J.H.M., 1990, Implementation of human factors in the management of large-scale
industrial investment projects: a management point of view and ergonomics practice, Ergonomics, 33(5),
643-653, DOI: 10.1080/00140139008927175
Liang, 2014, The application of modem cost management in real estate enterprise. International Journal of
Technology Management, 97-99.
Liu H.S., Liu J., Wang H.G., Qi X., Sang X.Z., 2012, Analysis of lcc model of high-voltage transmission line.
Journal of Special Education & Rehabilitation, 13(3-4), 1-4, DOI: 10.1109/appeec.2012.6307742
Mehran S., 2012, A grid-based collaborative supply chain with multi-product multi-period productionâ
distribution. Enterprise Information Systems, 6(1), 115-137.
Morris A. J., 2010, Enterprise project/cost management systems implementation—lessons learned, Aace
International Transactions.
Nikolay I., 2016, A study on optimization of nonconformities management cost in the quality management
system (qms) of small-sized enterprise of the construction industry ☆. Procedia Engineering, 153, 228-
231.
Ogihara Y., Mochida K., Nemoto Y., Murai K., Yamazaki Y., Shini T., 2003, Correlated clustering and virtual
display of gene expression patterns in the wheat life cycle by large-scale statistical analyses of expressed
sequence tags, Plant Journal, 33(6), 1001, DOI: 10.1046/j.1365-313x.2003.01687.x
Peñamora F., Vadhavkar S., Perkins E., Weber T., 1999, Information technology planning framework for
large-scale projects, Journal of Computing in Civil Engineering, 13(4), 226-237.
Ruiz-Martin C., Poza D. J., 2015, Project configuration by means of network theory, International Journal of
Project Management, 33(8), 1755-1767.
Stevens W. M., 1986, Cost control: integrated cost⁄schedule performance. Journal of Management in
Engineering, 2(3), 157-164.
Swarr T.E., Hunkeler D., Klöpffer W., Pesonen H.L., Ciroth A., Brent A.C., 2011, Environmental life-cycle
costing: a code of practice, International Journal of Life Cycle Assessment, 16(5), 389-391.
White D., Fortune J., 2002, Current practice in project management - an empirical study. International Journal
of Project Management, 20(1), 1-11, DOI: 10.1016/s0263-7863(00)00029-6
Yu B. Q., Wang T. Y., Zhang J., Li G. Q., 2006, A new algorithm to refresh file aggregates in distributed
enterprises. Materials Science Forum, 532-533, 1001-1004.
Zakeri B., Syri S., 2015, Electrical energy storage systems: a comparative life cycle cost analysis, Renewable
& Sustainable Energy Reviews, 42(C), 569-596, DOI: 10.1016/j.rser.2014.10.011
Zapalac R., Kuemmler K., Malagon, T., 1994, Establishing management information systems for multiproject
programs. Journal of Management in Engineering, 10(1), 37-42.
Zhang Y. H., 2005, Key problems in implementing management of responsibility cost by construction
enterprise, Journal of Railway Engineering Society.
Zhong W. U., Zhang R. W., 2006, The new progress of cost management theory and its influence on
enterprise performance evaluation, Systems Engineering, 24(2), 15-18.
1470