Optimisation assessment model for selection of material and assembly for sustainable building projects

International Journal of Modern Research in Engineering & Management (IJMREM)
||Volume|| 1||Issue|| 3 ||Pages|| 16-31 ||March 2018|| ISSN: 2581-4540
www.ijmrem.com IJMREM Page 16
Optimisation assessment model for selection of material and
assembly for sustainable building projects
Liman Alhaji Saba *1,2
, Mohd Hamdan Ahmad 1
, Roshida Binti Abdul Majid1
and Taki Eddine Seghier1
1
Faculty of Built Environment, Universiti of Teknologi Malaysia johor Bahru, Malaysia.
2
School of Environmental Studies, Federal Polytechnic Bida, Nigeria.
----------------------------------------------------ABSTRACT------------------------------------------------------
Sustainable Selection of Material and Assembly (SMA) constitutes a importants strategy in building design and
construction. Current sustainable SMA methods fail to provide adequate solutions for finding the optimum
improvement strategies and choosing the best alternative in a decision environment. To assist the decision-making
process, this study suggests the Multi objective Optimization (MO) approach utilization. However, process
improvements cannot be based only on environmental considerations, other factors like socio-economic must be
also being considered in parallel. As well, the study indicates that MO coupled with Life Cycle Assessment (LCA)
provides a tool for balancing process environmental and economic performance. The value of this approach in
environmental process analysis rests in providing an optimal option for process improvements which may be
optimal and suitable for a particular situation. A decision-aid tool – optimum Life Cycle Assessment Performance
(OLCAP) – is recommended. OLCAP is tested and demonstrated by application to case studies of an existing
traditional construction method and contemporary construction method of low cost housing projects. The MO
value in process analysis lies in allowing for an alternative option for process betterments, therefore able the
selection of the Best Available Technique not Entailing Excessive Cost (BATEEC) and Best Practicable
Environmental Option (BPEO).
KEYWORDS: Selection of material and assembly; Life cycle assessment; multiobjective optimisation; process
analysis; environmental impact
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Date of Submission: Date, 19 February 2018 Date of Accepted: 25 March 2018
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I. INTRODUCTION
The construction, fit-out, operation and ultimate demolition of buildings is a huge factor of human impact on the
environment both directly (through material and energy consumption and the consequent pollution and waste) and
indirectly (through the pressures on often inefficient infrastructure). Building construction practitioners have
begun to pay attention to controlling and correcting the environmental damage due to their activities. With regard
to important influence of the building sector, the approach of sustainable building possesses a high potential to
make a worthful contribution to sustainability. The speed actions towards sustainable usage depends on decisions
taken various actors in the construction process: firms. owners, designers, managers, and so on. [1, 2]. An
significant decision is the sustainable Selection of Materials and Assemblies (SMA) to be utilized in building
construction projects. As careful selection of sustainable materials has been identified as the simplest way for
designers to start integrating the principles of sustainability in building construction projects [3]. The selection of
building materials is considered as a multi-criteria decision problem [4], which is based on believing experience
rather than utilizing numerical approach, as a result of lack of formal and measurement criteria availability [5]. It
is a design process area that takes place in the detail design stage where significant decisions are made with respect
to building assembly [6].
A lot of the evaluation methods have been faulted for overstressing the aspects of environment [7]. Some other
methods like BREEAM and other existing methods for assessing buildings that are restricted to resource
efficiency and environmental protection agenda possess small utility for assessing economic and social factors –
which are all important indicators involved to sustainability – as fought to environmental sustainability, since they
predominantly focused on environment that is one of the four (4) principles of sustainable building. Even against
this single principle, they are only able to render relative assessment as opposed to absolute [8]. Also, the
majorities of the assessment methods were designed for new construction, and focused on the design of the
constructed buildings. To be considered sustainable, the methods of assessment will have to be remodel under the
sustainability umbrella – economic, environmental, technical and social [9, 10].

Optimisation assessment model for selection of material...
Increasing the discussion scope outside environmental responsibility as well as adopting the wider sustainability
agenda are more and more necessary requirements. In this challenges recognition, in 2011, a new standard BS
8905 was launched that was directed at products manufacturers to aid in initiation and advance their efforts of
supply chain sustainability. This standard fail to meet or come short of aligning material selection practices with
goals of sustainability at the building design phase. This is a phase where material selection and assessment
normally take place. Among the literal effort to reduce the construction impact is by taken into consideration the
embodied energy and carbon mitigation, which exist mostly in the building walls and frame as well as the recurring
embodied energy and carbon components [11-13]. They also reported that in other to achieve significant
minimization in the embodied energy and carbon intensity, replacement of conventional building materials with
durable and low energy materials like locally resourced materials as well as innovative construction methods
adoption were recommended. Therefore there is a require need for developing a holistic and systematic sustainable
material selection process, of evaluating trade-offs between economic, environmental, technical and social criteria
[14, 15].
The material selection process features as basically having many problem that will involve varied considerations,
in many cases with complex trade-offs between them, which implied suitable solution might be found amongst
the multi-criteria decision analysis (MCDA) methods [16-18]. In this regards, more detailed systematic
interpretation of the Life Cycle Assessment (LCA) application to process selection and design is given [19]. This
exemplifies the usage of system analysis to environmental management problems. However, recent literature
suggests that LCA is gaining wider acceptance in many industrial sectors, particularly in the process sectors.
While the utilization of LCA has traditionally been adjusted towards bettering the products environmental
performance, various studies demonstrated the potential of LCA as a tool for process selection, process design
and optimisation. Here, the focus is on the use of LCA for process optimisation. The aim is to demonstrate how
the type of analysis adapted from welfare economics and operations systematic investigation can be combined
with system analysis in the LCA context to provide a powerful decision-making tool for sustainable performance
of process sector. The potential of this method is exemplified by the incorporation of two (2) case studies of an
traditional construction method (TCM) and contemporary construction method (CCM) of low cost housing
construction projects. Based on this information and the present study lacks, this paper suggests an optimisation
method using mathematical programming technique to evaluate building materials and assemblies founded on
their sustainability, of which Optimum Life Cycle Assessment Performance (OLCAP) was recommended. The
procedures for integrating into the process optimisation framework of the environmental criteria alongside the
economic as well as technical criteria are reviewed and discussed. It is indicated that this approach can provide a
potentially powerful decision making tool for firms, managers, designers and process engineers.
II. LITERATURE REVIEW
To gain insights into how similar studies on optimisation assessment approach in Selection of Materials and
Assemblies (SMA) studies might have been conducted around the globe. A systematic search of key peer-
reviewed papers from renowned databases about SMA analysis was conducted. These searches yielded few results
with little relevance. The first overarching outcome was the general agreement among peer-reviewed literature
about the importance of optimisation method in assessment of building impacts on the environment [20]. The
second outcome was that despite acknowledgement of the need to consider building SMA impact analysis, few
quantitative studies have been conducted in this respect. These were discussed under the following sub-sections.
Life cycle assessment (LCA) : LCA is a quantitative environmental performance tool, essentially based around
mass and energy balances but applied to a complete economic system rather than a single process. While chemical
or process engineering is normally concerned with the operations within system boundary 1, LCA considers the
whole material and energy supply chains, so that the system of concern becomes everything within system
boundary 2. The material and energy flows that enter, exist in or leave the system include material and energy
resources and emissions to air, water and land, called environmental burdens and they arise from extraction and
refining of raw materials, transportation, production, use and waste disposal of a product or process. The potential
effects of the burdens on the environment, i.e. environmental impacts, normally include global warming potential
(GWP), acidification, ozone depletion (OD), eutrophication and so on. As a result, in 1990, the Society for
Environmental Toxicology and Chemistry (SETAC) initiated activities to define LCA and develop a general
methodology for conducting the LCA studies. Soon afterwards, the International Organisation for Standardisation
(ISO) started similar work on developing principles and guidelines on the LCA methodology [21]. The LCA
methodology is still under development. At present, the methodological framework comprises four phases,
namely: Goal and scope definition; Inventory analysis; Impact assessment; Interpretation. However, LCA is based
on the kind of thermodynamic and system analyses which are central to process engineering [22]. Thus for these
purposes, `the environment' is defined along with the system, by exclusion. The system of interest exists because

it produces goods and services, which are treated together as outputs. To generate these outputs, inputs of energy
and materials are required. In the LCA context, system boundaries are drawn from `cradle to grave' to include all
burdens and impacts in the life cycle of a product or a process, so that the inputs into the system become primary
resources. The objectives of LCA can be of particular importance to process designers and engineers, because it
can inform them on how to modify a system to decrease its environmental impacts. To assist in identification of
the optimal options for improved system operation from ‘cradle to grave’, LCA can be coupled with optimisation
techniques as discussed in the ensuing section.
System optimisation and Life cycle assessment :In order to predict and describe the composite industrial
systems behaviour, it is absolutely essemtial to utilize detailed mathematical modelling. In the same manner, the
optimum operating conditions identification that will ensure bettered process performance normally renders the
utilization of an optimisation technique absolute necessary. Historically, system optimisation in chemical and
process engineering usages has focused on maximising the economic performance, subject to the certain
constraints in the system. Over the years, environmental performance optimisation has started to be incorporated
into system optimisation, beside traditional economic criteria. These methods have primarily been focused on
several waste minimisation techniques [23]. An efforts to incorporate environmental considerations into the
design and optimisation processes make up the starting of the paradigm shift in the process sector which are
adjusted towards the process economic performance. Thus, it is possible for waste reduction methods to minimize
the emissions from the plant but to enhance the impacts in or to another place in the life cycle, so that overall
environmental impacts are enhanced, for example Bai [24]. Consequently, the need to incorporate Life Cycle
Thinking (LCT) into optimisation and process design procedures has been accepted by researchers [25-27]. For
exemple, that which establishes a link between the process environmental and economic performance from ‘cradle
to grave’ been formulated by [28-30]. This method is known as ‘Optimum Life Cycle Assessment Performance’
(OLCAP). The OLCAP process is exemplified on low cost housing construction projects case study of TCM
using stablise clay block and CCM using sand-cement block houses in the ensuing section.
III. APPLICATION OF OPTIMUM LCA PERFORMANCE – CASE
STUDIES’
The process chosen for the exemplification of OLCAP approach is an existing traditional construction method
(TCM) using stabilise clay block and contemporary construction method (CCM) using sand-cement block of low
income house (LIH) constructed in 2016 in Abuja of Nigeria. A two bedroom apartment house of 69.0m2
floor
area with the average headroom of 3.0m was used as the model for the case study. The structural system used was
a reinforced concrete columns, beams and roof beams. The external envelope material and the internal partition
material were not rendered on both faces with sand-cement mortar, with the following specifications as indicated
in Table 1. Figure 1 shows the graphical drawings of stabilise clay block house model.
Figure 1: The graphical drawings of TCM stablise clay block house
Figure 2 showed the construction activities prominent features (extraction, processing, manufacturing and
production/construction) for the model TCM stablise clay block house.

Figure 2: TCM construction activities prominent features
In addition, to the case study, further scenario (CCM using sand-cement block house) was a 3 bedrooms apartment
house of 92.0m2
floor area and with average headroom of also 3.0m was modeled to provide a comparison. Figure
3 shows the graphical drawings of CCM sand-cement block house model. The structural system used was a
reinforced concrete columns, beams and roof beams. The external envelope material and the internal partition
material were rendered on both faces with sand-cement mortar, with the following specifications as indicated in
Table 1.
Figure 3: The graphical drawings of CCM sand-cement block house
In addition, Figure 4 showed the construction activities prominent features (extraction, processing,
manufacturing and production/construction) for the model CCM sand-cement block house.

Figure 4: CCM construction activities prominent features
Table 1: List of building materials and assemblies
Building Stage Component Material AMC CMC
1,0 Substructure
Strip foundation Concrete √ √
Wall in foundation 230 x 230 x 450 mm hollow sand-
cement blocks filled with light
concrete
√ √
Filling to level Laterite soil √ √
Hardcore Broken concrete/stone √ √
Ground floor slab Concrete √ √
2.0 Super structure
2.1 Walls and columns Columns Reinforced concrete √ √
Beams Reinforced concrete √ √
External walls 230 x230 x 450 mm hollow blocks x √
Partition walls 150 x 230 x 450 mm hollow blocks x √
External walls 230 x 150 x 300 mm solid blocks √ x
Internal walls 230 x 150 x 300 mm solid blocks √ x
2.2 Roof Structure and
covering
Wall plate 75 x 100mm hardwood √ √
Tie beam 50 x 150mm hardwood √ √
Rafters/struts 50 x 100mm hardwood √ √
Purlins 50 x 75mm hardwood √ √
Noggins 50 x 50 mm hardwood √ √
Fascia board 25 x 250mm hardwood √ √
Roof covering 0.55 mm long span aluminium
sheets
√ √
2.3 Finishes Ceiling PVC Tiles √ √
Internal walls Plastering and emulsion paint x √
External walls Plastering and emulsion paint x √
Floor finishes Vitrified ceramic tiles √ √
2.4 Doors/Windows/Fittings External doors Locally steel doors √ √
Internal doors Hardwood panel doors √ √
Windows Aluminium/glass casement √ √
Anti-burglary bars 20 x 20mm hollow steel pipe √ √
Key: √ = Applicable, x = Not applicable
The Methods of Assessment : In this section, the different EE and EC assessment methods are examined. The
aim is to establish which method(s) to use. In the literature, three methods of assessment are quite common: the
input-output analysis, the process analysis, and the hybrid analysis. Input-output LCA is a top-down method for
analyzing the environmental interventions of a product using a combination of national sector-by-sector economic

interdependent data which quantifies the dependencies between sectors, with sector level environmental effects
and resource use data [31]. In process LCA, known environmental inputs and outputs are systematically modelled
through the utilisation of a process flow diagram. The process LCA is often called a bottom-up approach. This is
because the subjects of analysis in process LCA are individual processing units and the flow rate and composition
of streams entering and exiting such units. The above two (2) life cycle methods of assessment have advantages
and disadvantages which have been extensively discussed [32-34]. In order to justify the choice of the methods
used in this study, a summary of the advantages and disadvantages of the preferred choice is examined. Input-
output analysis suffers from lack of representativeness being used due to over-aggregation of data. Also, national
sector-by-sector economic interdependent data or sectoral matrix is often too old and out of date in developed
countries and worse in developing countries. Process-based LCA allows for a detailed analysis of a specific
process at a point in time and space. Nonetheless, it is often criticized for its subjectivity in the definition of the
processes that should be considered and the data sources to be used, which can be complex if the building has so
many different types of materials.
Mathematical models : The main reason for using emission or impact factors is to facilitate computation of
emissions. By using emission factors, tedious tasks that would have involved chemical equations are avoided.
This is because emission factors are expressed as quantity of EE or EC per functional unit. For example, according
to Bath ICE, the emission factor of virgin aluminium is 11.46kgCO2/kg. The functional unit is the “kg” in the
denominator as it denotes quantity of virgin aluminium in 1kg. Therefore, to compute the emission from a given
quantity of virgin aluminium, a simple multiplication of the total quantity and the emission factor is conducted. If
there are several construction materials considered, then the products of the emission from different materials are
added. This is modelled mathematically as in equations (1) and (2) [13]. Further details on the research methods
are explained subsequently using equations (1) to (8) [35].
𝐸𝐸 𝑘 = ∑(1 + 𝑊𝑘) × 𝑄 𝑘 × 𝐼𝑘
𝑛
𝑘=1
(1)
𝐸𝐶 𝐾 = ∑(1 + 𝑊𝑘) × 𝑄 𝑘 × 𝐼𝑘 (2)
𝑛
𝑘=1
Where,
EEk and ECk are EE and embodied CO2 of material type k with units MJ and kgCO2 respectively;
Wk is the waste factor (dimensionless) of material type k;
Qk is the total functional quantity of material;
Ik is the EE factor or embodied CO2 factor with units’ MJ/functional unit and kgCO2/functional unit of
material respectively.
However, carbon emission for direct fuel combustion was calculated using the formula:
CEF = A x EC (3)
Where,
CEF = carbon emission from direct fuel consumption,
A = activity data (litres of fuel),
EC = emission coefficient (kgCO2/litre of fuel).
However, given the labour-intensive construction methods prevalent in the study area, manual energy
was estimated using the manual energy coefficient for the tropical region as recommended by [36, 37].
Total Embodied Energy:
EE = EEM + EET + EEC (4)
Where,
EE= total embodied energy,
EEM = embodied energy of material (cradle-to-gate),
EET = embodied energy of transportation, and
EEC = embodied energy of construction.
Material Embodied Energy (Cradle-to-Gate)
EEM = QM [EECF] (5)

Where,
EEM = cradle-to-gate embodied energy of material,
QM = quantity of material (kg), and
EECF = embodied energy coefficient of material (MJ/kg) according to ICE database and available local
inventory data.
Transportation Energy
EET = QF [LHV] (6)
Where,
EET = embodied energy of material transportation,
QF = quantity of fuel consumed (litres), and
LHV = lower heating value of fuel.
The study assumed that all building materials were locally produced. Hence local transportation of materials was
accounted for. Road haulage is the main mode of material transportation in the study area and the fuel type was
found to be predominantly diesel. The quantity of diesel was estimated using 35litres per 100kilometers for heavy
duty trucks and 20litres per 100kilometers for light duty trucks [38].
Site Construction Energy
This is divided into two parts namely: energy used by site equipment and site installations as well as manual
energy. All fabrications were assumed to be carried out on the construction site. Energy and fuel use data were
obtained from the records of the contractor that built the reference building. Where electricity is used for site
construction activities, the primary energy content of grid electricity was estimated using the formula:
E = 3.6[GE] PEF (7)
Where,
E = primary energy content of electricity use,
GE = grid electricity use in kWh,
PEF = primary energy factor of grid electricity, and
3.6 = conversion factor from kWh to MJ.
The PEF for electricity in the study area was estimated to be 2.83 [39]. Also, if direct fuel combustion is
used in the site construction, the primary energy content of direct fuel combustion is estimated using equation (6).
Manual Energy
ME = 0.75LT (8)
Where,
ME = manual energy,
0.75MJ/hour = human energy coefficient,
L = number of labour workers, and
T = number of hours of work.
Equation (7) above was derived from earlier work by [40] on agricultural productivity and used in a
recent work by [41] on energy assessment of cement production in Nigeria. Because of lack of information about
waste data in Nigeria, the waste factor was considered to be zero.
Aggregation of Data
Aggregation is a straight forward task. First, the emissions from a category are added independently. In
other words, emissions from all the different construction materials, equipment, and personnel transport types
used are independently computed. Then, the emissions from the three different categories are summed up to obtain
a total. These steps were implemented in assessing EE and EC of the two case studies considered.
Application of optimum LCA performance framework to the problem : The Optimum Life Cycle Assessment
Performance (OLCAP) methodological framework consists of four (4) steps:
1. LCA completion study;
2. Optimisation problem formulation;
3. Multiobjective optimisation (MO); and
4. Selection of the best compromise solution.

However, there is an important gaps between the theory and practice of sustainability and Sustainable
Development (SD) at the project level [42]. The foundations for SD are already encapsulated in the definition
given in the seminal Brundtland report [43]. This most quoted definition states that it is, “development that meets
the needs of present generation without compromising the ability of future generations to meet their own needs”.
However, [42] stated that the all-inclusive definition sounds abstract, and requires hierarchical transformation to
operational decision-making variables. There is now wide recognition of the requirement for quantitative
transformations, counterpart incorporated holistic approaches in evaluating the sustainability of building material
and assembly, as a part of wider SD agenda. Researchers working on the evolving discipline of Sustainability
Science presently acknowledge that the implementation success at the project levels depends on various
contributors. These include:
1. the criteria development that transform macro-level policies and national sustainability goals to project level
decision-making variables;
2. the decision models development, computational frameworks, and assessment methods for building material
and assembly sustainability assessment; and
3. the development and incorporated decision support tools implementation to facilitate decision making by
various stakeholders.
Such a crisp value index would facilitate dissimilar material and assembly alternatives comparison along diverse
sustainability envelope dimensions: economy, environment, resource efficiency, performance, waste
minimization, and socio benefit. A mathematical model is therefore an essential requirement of the optimisation
problem. Such a model is needed for sustainability quantification in decision-making. The detail description of
the steps contained in the model formulation is described below and the OLCAP approach represented by diagram
as indicated in Figure 5 [30].
Step 1.
LCA
Step 2.
Optimisation Model
Step 3.
Multiobjective
Optimisation (MO)
Step 4.
Optimisation
Method
Improved Process
Performance of
“Upstream”
Manual Computation
Process-based LCA
(PBLCA)
BIM generator
Mathematical
Programming
Linear Programming
(LP)
REVIT
Decision- makers
Socio-economic, technical,
legislative and other
constraints
Burdens Impacts
Environmental criteriaEconomic criteria
Optimum solutions
Best compromise solution
Figure 5: Optimum LCA performance (OLCAP) methodological framework
Step1: LCA Completion study – It involves conducting a system LCA study, in an accordance to [44]
methodology, as showed in Figure 8. An appropriate software of LCA, for example PEMS [19], TEAM [45] or
BIM [13], can be utilized to conduct energy and material balances, as well as to quantify the impacts it has

throughout the life cycle. Because of lack of database and tools, a process-based LCA analysis technique was
adopted for this purpose.
Step 2: Optimisation problem formulation - Because of LCA nature, with distinct environmental impacts to be
taken into consideration, the problems of optimisation is multiobjective. Thus, the problems of conventional
single-optimisation involving economic objective function are translated into problems of multiobjective, to
consider the environmental objectives. The problem of Multi-Objective (MO) in LCA context can be in this form:
Min f(x, y) = [f1 f2 ……… fp] (1)
s. t.
h(x, y) = 0
g(x, y) ≤ 0
x ∈ X 𝜌 Rn
y ∈ Y 𝜌 Zq
(2)
Where,
f is a vector of economic and environmental objective functions;
h(x, y) = 0 and g(x, y) ≤ 0 are equality and inequality constraints; and
x and y are the vectors of continuous and integer (discrete) variables.
For example, the equivalence physical constrained may be defined by energy and material balances; this may
depict the material availabilities, capacities, heat requirements and so on. A n vector continuous variables is the
energy flows and material, compositions, pressures, units sizes and so on, while a q vector integer variables is
option materials or system’s processing paths. If the Z integer is null set and the physical constrained as well as
impacts are linear, then Equations (1) and (2) is the problem of Linear Programming (LP); while if the integer
variables is not null set and nonlinear terms present in the impacts and physical-constrain, Equations (1) and (2)
will be problem of Mixed-Integer Nonlinear Programming (MINLP). The problems of Mixed Integer Linear
Programming (MILP) incorporate only linear and integer variables.
Typically, an economic objective involves a cost or profit function, which is defined by:
F = CT
y + f(x) (3)
Where,
c is a cost or profit coefficients vector for integer variables and
f(x) is a linear or nonlinear function depicted by continuous variables.
In this context, the environmental objectives is the burdens Bj or impacts Ek:
𝑀𝑖𝑛 𝐵𝑗 = ∑ 𝑏𝑗,𝑛 𝑥 𝑛
𝑁
𝑛=1
(4)
𝐸 𝑘 = ∑ 𝑒 𝑘,𝑗 𝐵𝑗 (5)
𝐽
𝑗=1
Where,
𝑏𝑗,𝑛 is emission coefficients associated with continuous variables 𝑥 𝑛 xn.
In equation (5), 𝑒 𝑘,𝑗 is the relative contribution of burden Bj to impact Ek, as defined by the ‘problem
oriented’ technique to impact assessment [46].
In this approach, for example, GWP factors, 𝑒 𝑘,𝑗 , for dissimilar greenhouse gases (GHGs) are showed relative to
the global warming potential (GWP) of carbon dioxide (CO2), which is thus determined to be unity. In the event
of utilization of different impact assessment technique, subsequently equation (5) is given a new definition
accordingly. But, presently, it was noted that the LCA technique assumes that environmental impacts as well as
burdens functions are linear, that is, are directly proportional to the functional output unit(s) and no synergetic or
antagonistic effects. BIM tool – REVIT was adopted for this purpose.
Step 3: Multiobjective optimisation - The system is then optimised at the same time on environmental and
economic impacts to discover the several aspects or multidimensional noninferior or Pareto surface that maps

optimal solutions. The choice of environmental objectives for optimisation is contingent upon the Scope and Goal
of the study. Therefore, optimisation can be at the impact assessment or inventory levels, in which the
environmental objectives are defined as burdens or impacts [28, 30]. One possible approach to optimisation in the
context of LCA would be to combine environmental and economic objectives into one function so that the problem
may be minimize to one objective optimisation. The significance is on the choices from the noninferior solutions,
rather than preferences before analysing all the trade-offs among objectives. The trade-offs amongst the
noninferior solutions indicate the gained and lost by selecting the option. The decision makers who know and
comprehend the options and trade-offs are potential to understand other parties’ interests and make a compromise.
Furthermore, by trade-off incommensurable objectives such as economic requirements and environmental
impacts, this technique avoids the well-known problems that may be encountered, e.g., in cost – benefit analysis
[47], that is minimizing individual preferences to the value of market or trying to express the environmental quality
in financial terms. Cost-benefit analysis (CBA) is maximum net gain idea: this minimizes the combine social
welfare to the net economic benefit monetary unit. In the recent past, CBA has been used in environmental
decision-making. The widely used technique is known as ‘contingent valuation’ (CV). Its difficulties and
limitations have been recognised. The latter [48, 49] have pointed out that CBA has serious difficulties in dealing
with intergenerational equity and sustainability problems as well as in valuing the natural environment.
Summarily, CBA and related economic techniques to decision-making faced three (3) problems: the individual
preferences measurement, the comparison of these preferences, and their combination into a social preference
function. But these cannot provide information for decision-making on a ‘local’ level: for example, they cannot
advise engineers on how to modify a process to better its environmental performance. Multiobjective optimisation
(MO), on the other hand, does exactly this: it can optimize the system operation with environmental, economic
technical and other aspects taken into consideration. If used in the context of LCA can be able to optimize the
product or process whole life cycle and so provide a more effective approach to environmental management of a
system. Linear programming (LP) was adopted for this purpose.
Step 4: Selection of the best compromise solution - To choose the best compromise solution from optimum
alternatives, preferences articulation is essential. One of the possible ways to choose the ‘best’ solution is to
consider a graphical representation of the noninferior and then choose the best compromise solution on the basis
of the trade-offs. However, this technique is limited to two (2) or three (3) objective functions at most; more than
this, graphical representation becomes complex. If all objectives are considered importance, than the best
compromise solution might be that which equalises the percentage by which all objectives differ from their
optimum values. However, should any of the objectives be considered more important than the others, then other
methods that allow preferences ordering and quantification is known as multicriteria decision-making (MCDM)
techniques, can be used to identify the best compromise solution. MCDM techniques provide a structured
approach to a decision making process. Extensive reviews of MCDM techniques can be found in [50] and [51].
User friendly software with various MCDM methods to aid the decision making process are also available [24].
They enable systematic analysis and modelling of preferences with the aim of providing help and guidance to
decision-makers in identifying their most desired solution. The major advantages of these techniques like BIM
tool - REVIT is transparent, non-ambiguous and easy to use by non-experts. It is important to note that the
attributes and the preferences are always identified on a case by case basis within a bounded decision space, and
that they only apply in that particular decision-making context. This avoids the criticism often voiced, in both
LCA and CBA, of trying to use general weights or costs to indicate the importance of distinct criteria in different
decision-making situations. Optimisation method was adopted using mathematical programming (MP).
In sum, the first step in this procedure involves carrying out an LCA study of the process, by following the [44]
methodology. As indicated in Figure 8 [30], BIM software can be used to carry out material and energy balances
and to quantify the burdens and impacts along the life cycle. The material and energy balances for the process
itself (boundary 1 in Figure 7) can also be carried out within existing design operation software and these data can
then be fed into the BIM software. The data for the other parts of the system (boundary 2 in Fig. 1) can be sourced
from a database which is normally an integral part of the BIM software. A more detailed exposition of the LCA
methodology is given elsewhere [44] and is not discussed further here.
Instead, the focus of this paper is on steps 2 – 4 of the OLCAP procedure. The environmental burdens and impacts
quantified in step 1 represent an input into the optimisation model, which is formulated in step 2. In addition to
environmental criteria, the model includes economic, technical, legislative and other constraints within which the
system must operate. In step 3, the system is optimised on environmental and socio–economic objectives of
interest to the decision-makers, to yield a number of optimum solutions. A suitable optimisation technique and
software must be used to generate and solve the optimisation problem. A more detailed account of these two steps
of OLCAP is given in step 2 and 3. Finally, step 4 enables the decision-makers to choose the best compromise

alternative from a range of optimum solutions. Thus, BIM tool – REVIT can be used to facilitate the decision-
making process. This is discussed in step 4.
IV. THE TECHNIQUE ADOPTED FOR VALIDATING THE SMA MODEL
According to [52], “the suitable technique for validating a model mainly depend on the real world distinct element
and characteristic in a problem being analysed as well as the type of model utilized”. Nevertheless, the various
techniques consideration suggests degenerate tests as the only suitable techniques for validating the developed
SMA model, mainly because no real-system database available. Also, the aim of this study to validate the model
for sector-wide usage also makes this approach more suitable than the others. The objective of degenerated tests
validation was to see if it degenerates as expected by modeling such situations in the model using suitable values
selection of the input and internal parameters. Therefore, BIM tool - REVIT was adopted for the validation. The
ensuing sections describe the detailed procedure of the validation exercise and the findings.
Results validation using BIM tool – REVIT : Based on the Embodied Energy (EE) and Embodied Carbon (EC)
computation, the challenges encountered in performing the same for the whole building systems cannot be
underestimated. This is manual computation fundamental weakness, where everyday computational tasks are
repeated for each building material identified. Moreover, the manual process is allergic to errors and the
probabilities of naming the errors are lose weight. The come out of BIM can be utilized to increase the process-
based approach acuracy in the EE and EC computation. Also, BIM act to fulfill an option to validate the obtained
manual computational results. The previous studies such as [53], many BIM software exist and are presently being
used to model buildings. Example of such is Revit, which is regarded with great favour in the BIM software
market. A main merit of Revit is that its building models can be converted into practical or readily communicated
formats without much difficulty that can be processed by other software [54]. However, comma-separated value
(CSV) is a comparatively simple file format supported by Microsoft Excel and Revit. Excel can the information
in CSV format. Producing or making up building model data in CSV can be interpret by MS Excel or Revit. The
MS Excel computational power provide a particular quality of great choice in modelling equations 1 and 2, which
are utilized in EE and EC calculation. In addition, MS Excel can be utilized to show calculation results in an
accordance to standard formats like the Cahier des Prescriptions Techniques in France and the New Rules of
Measurements (NRM) in the United Kingdom (UK), which are These are principles or conditions of output
presentation and construction quantity measurements. This was adopted for this study. Since it is usually used in
developing countries like Cameroon as well as in developed countries like Singapore. Based on the 2D drawings
and Architects specification stabilise clay block house and sand-cement block house were modelled in Revit. The
3D equivalents are presented in Figure 6 and 7.
Figure 6: 3D TCM of stabilise clay house Revit model

Figure 7: 3D CMC of sand-cement block house Revit model
Furthermore, the schedules as well as quantities are generated from these models by utilizing the “Modify
Schedules/Quantities” function under the “View” tab in Revit 2014. The output is converted to CSV format using
the “Export” function in Revit 2014. The CSV format is stored in any preferred location on the computer and read
with “MS Excel”. Equations 1 and 2 are modeled in Excel and calculation are conducted in this environment. First
results obtained differ slightly from those obtained by utilizing manual calculations. The manual process is
reaffirmed to name and also correct the errors. In addition, BIM model is reaffirmed to name the missing
components. These exercises were performed several times until common results were obtained, and this results
are presented in Tables 2 and 3.
Table 2: Cradle-to-gate performance (TCM of stablise clay block house)
Building component EE emissions
MJ/kg
Percentage
(%)
EC emissions
(kgCO2)
Percentage
(%)
Site installation No data
Substructure 70,154.17 54.0 10,001.89 64.0
Walls and frames 10,255.38 8.0 810.35 5.0
Roof structure and covering 32,298.00 24.0 1,804.56 11.5
Finishes 1,217.14 0.4 76.89 0.5
Doors/windows/fixture/fittings 16,010.23 12.1 1,127.86 7.0
Plumbing installations 610.96 0.5 980.37 4.0
Electrical installations 1,257.19 1.0 1,615.51 8.0
Waste No data
Total 129,953.82 100.0 15,689.70 100.0
Table 3: Cradle-to-gate performance (CCM of sand-cement block house)
Building component EE emissions
MJ/kg
Percentage
(%)
EC emissions
(kgCO2)
Percentage
(%)
Site installation No data
Substructure 97,114.99 33.2 13,861.97 33.3
Walls and frames 129,434.25 44.0 19,991.51 48.0
Roof structure and covering 43,052.68 14.2 2,408.00 5.8
Finishes 2,290.04 0.8 145,41 0.6
Doors/windows/fixture/fittings 20,434.85 7.0 1,422.31 3.4
Plumbing installations 980.37 0.3 1,222.00 2.9
Electrical installations 1615.51 0.5 2,514.37 6.0
Waste No data
Total 294,194.96 100.0 41,565.57 100.0
V. DISCUSSION
After clearly identifying the performance of various materials and component elements assemblies, decision-
makers are more knowledgeable in selecting weights that reflect their personal reliability on each analysis.

This research discovered that a house built using sand-cement block house, produced a building with a
294,194.96MJ of EE and 41,565.57kgCO2 EC emission, with 126% EE and 165% embodied carbon more when
compared with stabilise clay block masonry wall for a residential building. However, the minimization in the
usage of materials with comparatively high EC, in this case sand blocks, with materials with lower EC, in this
case clay, in the wall component was the fundamental reasons or logic behind factor in the difference found. A
distinctive for the Nigeria, clay was not only utilized as the principal structural material but also not needing
mortar wall finishes, rather than the more traditional mortar for wall plastering finishes (as found in the TCM of
stablise clay block house). The mortar displacement for wall plastering finishes gave rise to a carbon saving of
27%. The further factor leading to the low EC of the study case is the efficiency of volume production that is
related with stabilise clay block. In spite of ratio of the output to the input in the manufacturing of the TCM of
stabilise clay block, onsite waste production in this case study was still an important factor in the overall EC, 5%
of the total. However the clay manufacturing does not add to the overall waste associated CO2 produced; barely
about 6% of transport associated EC. In addition, this proposes decreases in EC can be made by increasing the
quantities of off-site manufacturing and minimization of on-site waste. Because no waste data collected, for both
process, was not of sufficient quality to make a robust EE and EC emissions quantification. Thus further study is
required so as to quantify the resource efficiency claims from stabilise clay block house processes in comparison
with that from onsite construction.
In spite of the high clay ratio throughout the structure half of the materials associated embodied carbon was
discovered to be related with the foundation, substructure as well as floor slab construction. Hence the comparative
importance of these sub structural elements minimizes with the materials CO2 intensive gain in other elements.
This proposes that these sub structural components and materials utilized would be appropriate objectives for
minimizing the EC further in such stabilize clay house. The sub structural elements were consisted of having the
properties of cement rich materials and blocks. The cement in concrete and mortars can possess a high energy
input during production as well as relatively high EC, in addition to the already CO2 release during the chemical
changes of manufacture. The embodied carbon quantity that is related with cement manufacturing depends on the
primary materials as well as the source of energy utilized in its output. The emissions that are linked with the
production of cement can be minimized by the fossil fuels uniform movement with both waste materials and
renewable energy as the source of energy. Therefore, any sensible or fair EE minimization should aim the
application of steel, cement-based products as well as cement. The policy direction in this regard should be
towards replacement of energy-intensive materials with low energy materials.
A number of research works on alternative building materials in Nigeria exist, but there is need for proper
documentation and a set of rules, principles or laws, especially written ones (or codification) to help and make
easier the informed use. In this regard, study on the utilization of more alternative envelope material to sand-
cement blocks (like recycle and reuse) and the utilization of cement replacement (for example lime, fly ash) is
crucial to sustainable materials selection in achieving sustainable development. In addition, since the continue
application of cement play significant function in building construction in the study area, uninterrupted change
for the better or progress in the production process is suggested. The materials replacement is not the only
alternative for sustainable building construction. Efficient as well as effective construction processes also help or
make use of sustainability in building construction. Minimizing the environmental loads from stabilise clay block
to a more advance stage which could be achieved in two (2) ways [55]. Firstly, by minimize the cement usage by
replacing with lower embodied carbon alternatives such as ground granulated blast furnace slag, fly ash and other
pozzolanic materials or lime based materials as mentioned in foregoing paragraph. Secondly, which is not
associated with this study case is by utilizing the design strategies so as to minimize the cement volumes needed,
for example, removing the oversite concrete ‘raft’, utilizing isolated point foundations instead of strip foundations
or utilizing steel helical screw piles. Although a relatively high embodied energy product steel helical screw piles
are both reusable and recyclable. Therefore, both the two strategies would minimize the application of carbon
intensive materials where no additional benefit to the application is possible in lightweight construction.
Nevertheless, in the study case, distinctive of majority clay construction, the most of its practicable mass is
separated or detached within the building structure or under other material finishes and, accordingly, not available
for the practicable thermal storage that could compensate for or counterbalance the environmental loads of its
extraction and production.
The full lifecycle, be made up of occupation, maintenance and demolition as well as disposal requires to be
considered. EC consideration requires to be incorporated at the earliest stage of design. If environmental loads are
to be reduced reasonably even though reducing further benefits there requires being general well-informed thought
in design of building.

The above scenario for building construction materials emphasizes the significant function built environment
practitioners participated in building construction materials selection or specification as well as in the process of
construction. Frequently, selection of alternative building construction materials has been hindered by the
deficiency of adequate technical information concerning the materials which makes built environment
practitioners bind to conventional building construction materials with widely known technical information. This
entails that cooperative attempts should be made to identify, codify as well as integrate into option or alternative,
low energy material and building codes that are dependent on context applicable to the area of study. In this regard,
the applicable government agencies together with the built environment stakeholders as well as professionals
should make cooperative attempts to address the challenge. With the performance scores of each assembly type,
the present study is not aiming at normalizing and ranking the different combinations. This study attempts to
incorporate the whole building system, in order to begin setting benchmarks for the industry. This would transform
the way the sector performs environmental assessment on building SMA and perhaps enhance research in more
simplified tools and methods to conduct LCA. It is interesting to note that there is no support on the effect of EE
and CO2. When observed, it can be found that sand-cement block house is responsible for a difference about
1256MJ/m2
of EE and 217.37kgCO2/m2
of EC.
V. CONCLUSION
MO process can be combined with LCA successfully as an aid in building construction process environmental
management. The results exposes that the process can be simultaneously optimised on an environmental objective
functions to identify the best compromise solution for bettering the performance of a process. The results indicate
that the process environmental performance can be improved by up to 26% EE and 65% EC emissions in
comparison with the existing contemporary construction method process. Since process improvements cannot be
carried out on the basis of environmental LCA only, it is also shown in this study that the compromise between
environmental and economic performance can be found on the TCM obtained by process optimisation. The merit
of MO in environmental process management in the context of LCA lies in offering alternative options for process
improvements that enables the choice of the BATNEEC and BPEO. Furthermore, multiobjective process
optimisation can successfully be combined with LCA as an aid in environmental management of a building
construction process. The process is simultaneously optimized on a number of environmental objective functions
to identify the best compromise solution for bettering the performance of the process. MO utilized in this approach
provides a more effective approach to environmental management process by offering alternative optimal
solutions and enabling decision-makers to identify and choose the BIM tool - REVIT. The process-based approach
was manual and because of susceptibility of such an approach to errors, BIM software was used to validate the
computational results. It is important to note that this is an emerging field and knowledge in this field is gradually
being explored. Hence, emissions from whole process construction were assessed but emissions from site
installation and was waste are not included, due to lack of data. The results obtained were converted to per unit
m2
so as to ease the comparison. Furthermore, when compared to other studies, the calculational results were in
the same range, although significantly lower than values obtained in the developed countries. The comparison
revealed sand-cement block house consumed more embodied energy and carbon than stablise clay house. The
approach suggested in this research can allow for assessment of the other civil infrastructures. The authors are
convinced that this research can assist building stakeholders in making critical decisions during the selection of
sustainable material and assembly alternatives.
Novelty : The mathematical methodology could also be extended with the other optimisationn techniques in
solving material and assembly selection problems. Finally, the evaluation model and results can provide a valuable
reference for building professionals seeking to enhance the sustainability of construction projects.
ACKNOWLEDGEMENT
The authors would like to thank the Universiti Teknologi Malaysia and Federal Polytechnic Bida, Nigeria
for their facilities, conducive-environment and support for the study as well as the project manager of MS
Cornerstone Engineering Construction and Company Limited in Nigeria who contributed to this study.
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