An Evaluation Model for Selecting Part Candidates for Additive Manufacturing in the Transport Sector
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metals
Article
An Evaluation Model for Selecting Part Candidates for Additive
Manufacturing in the Transport Sector
Rumbidzai Muvunzi * , Khumbulani Mpofu and Ilesanmi Daniyan
Department of Industrial Engineering, Tshwane University of Technology, Pretoria 0183, South Africa;
mpofuk@tut.ac.za (K.M.); afolabiilesanmi@yahoo.com (I.D.)
* Correspondence: MuvunziR@tut.ac.za
Abstract: There is a need to develop guidelines for identifying situations where it is more beneficial
to apply Additive Manufacturing (AM) as opposed to conventional methods of manufacturing. Thus,
the aim of this paper is to propose a model for evaluating the sustainability of applying AM in
the manufacture of transport equipment parts. A literature review was conducted to identify the
parameters for selecting the part candidates. In the next stage, the criteria were ranked according
to the needs of the transport equipment manufacturing industry using the Analytical Hierarchy
Process (AHP) technique. The next stage featured the development of the decision matrix using
the weights and classified levels. To validate the proposed decision matrix, different case studies
from literature were used. The weights obtained from the case studies were in agreement with the
proposed evaluation model. This study will add to the understanding of how the AM industries
can effectively screen potential part candidates, thereby promoting the overall sustainability of the
AM process in terms of material conservation, geometric complexity and functionality. There is
still a dearth of information on the evaluation models capable of identifying the core functions of
the products and the applicable environment. The work presents a proposed framework for part
selection using the evaluation model.
Citation: Muvunzi, R.; Mpofu, K.;
Daniyan, I. An Evaluation Model for
Keywords: additive manufacturing; AHP; evaluation model; Industry 4.0; part candidates; sustainability
Selecting Part Candidates for
Additive Manufacturing in the
Transport Sector. Metals 2021, 11, 765.
https://doi.org/10.3390/met11050765
1. Introduction
Academic Editor: Miguel Cervera Due to pressure from international organisations, the current global trend is aligned
towards the adaptation of sustainable manufacturing technologies [1] (Additive Manu-
Received: 23 February 2021 facturing (AM) is an important element of Industry 4.0 with the potential to positively
Accepted: 12 April 2021 transform the transport equipment manufacturing Industry [2–4]. In South Africa, most
Published: 6 May 2021 transport equipment parts are imported from other countries [5] According to the Ob-
servatory for Economic Complexity (OEC), $3.07B worth of vehicle parts were imported
Publisher’s Note: MDPI stays neutral from other countries in 2019 [6]. As a flexible technology, AM can be used as an enabling
with regard to jurisdictional claims in technology for increasing local production of transport equipment parts This is possible
published maps and institutional affil- due to the benefits of this emerging technology. Firstly, AM can be used to produce parts
iations. directly from digital models, thus, resulting in shorter process chains [7]. Additionally, AM
offers design freedom, allowing the manufacture of parts with complex geometry without
the need for tooling [7]. Additionally, AM has shown the potential to reduce or eliminate
the costs of inventory, logistics and tooling [8]. As a result, a wide variety of parts can be
Copyright: © 2021 by the authors. produced [9]. For example, AM has been used in the medical industry to produce complex
Licensee MDPI, Basel, Switzerland. implants. Yadroitsev et al. [10] studied the application of the Ti6Al4V alloy for biomedical
This article is an open access article applications. Du plessis et al. [11] conducted a study on the mechanical properties of
distributed under the terms and lightweight lattice structures that can be applied in developing bone implants for the medi-
conditions of the Creative Commons cal industry. Unlike conventional manufacturing techniques, such as machining, casting
Attribution (CC BY) license (https://
and forming, AM creates the final shape by adding materials, thereby eliminating wastage
creativecommons.org/licenses/by/
of raw materials. A lot of studies were done to improve the quality of parts produced
4.0/).
Metals 2021, 11, 765. https://doi.org/10.3390/met11050765 https://www.mdpi.com/journal/metals
Metals 2021, 11, 765 2 of 18
with AM [12–14]. Furthermore, the implications of the global pandemic and need for local
manufacturing capability call for exploitation of available manufacturing technologies.
1.1. AM Opportunities in the Production of Transport Equipment Parts
As mentioned earlier, AM offers many advantages to the transport equipment manu-
facturing industry. The following section explains some of the opportunities in which AM
can exploited to increase local production of parts in the transport sector.
1.1.1. Production of Lightweight Parts
One of the most important goals of the transport industry is to reduce fuel con-
sumption while improving safety [4] This can be achieved through reducing the weight of
components. AM offers the opportunity to processes advanced lightweight materials which
are difficult to process using conventional methods such as machining [15]. Additionally,
the freedom of design offered by AM can be exploited to allow the production of parts with
complex designs that are able to meet functional requirements while using lesser materi-
als [16,17]. Most cases in the literature that involve the use of AM to produce lightweight
parts are mostly for the aerospace and automotive industry [18–21]. Shi et al. [22] addi-
tively manufactured a lightweight aerospace bracket which was designed using topology
optimisation. Kim et al. [21] used topology optimisation and structural analysis to develop
a lighter automotive knuckle part with improved stiffness and structural safety. Moreover,
Calleja-Ochoa et al. [23] developed a method for producing ultralight components with
improved functionality using the Laser Bed Powder Fusion Process (LPBF). In this study,
the part produced using the developed approach exhibited high structural properties in
terms of compressive strength, stress and strain distribution.
1.1.2. High Performance Critical Parts
Some of the transport equipment parts are exposed to extreme conditions and require
high performance designs to function properly [24]. Typical examples include engine
components that are exposed to high temperatures and may benefit from the use of inno-
vative cooling systems which can be produced using AM [15]. Other extreme conditions
include corrosive environments or heavy mechanical loads. As mentioned previously, AM
gives opportunities to use high performance materials which can withstand the extreme
mechanical or chemical loads and optimised designs with improved functionality [15].
Calleja et al. [25] developed a method for ensuring uniform deposition in the manufacture
of blisk blades using the laser cladding AM process. The blades were produced using the
Iconel 718 super alloy for improved mechanical performance.
1.1.3. Producing Spare Parts in Low Volume
Transport companies are often faced with difficulties to manage spare parts inven-
tory [26]. A lot of downtime is experienced while waiting to replace a broken spare part [27].
Sometimes, a lot of inventory is kept, this ties up capital and the parts may become obsolete
in the warehouse [28]. AM offers the potential to switch to digital inventory so that the parts
can be produced on demand since no tooling is required [28]. Obsolete components can be
reverse engineered to obtain the original models so that they can be printed [26]. Using
AM to produce spare parts on demand will eliminate the logistical and warehousing costs.
1.1.4. Production Tools with Special Features
Due to the current trends in technological advancement, transport equipment manu-
facturers are continuously compelled to develop new vehicle designs which require new
parts [2]. Accordingly, flexible production tools are required to cater for the new compo-
nents. AM offers the opportunity to produce flexible tools with specialised features [29].
Typical examples include the use of AM to produce reconfigurable parts [30,31] AM also
allows the production of tools with special features such as embedded sensors or conformal
cooling systems [32]. Marin et al. [33] developed a hybrid process chain for producing an
Metals 2021, 11, 765 3 of 18
injection-moulding tool for an automotive component. The developed tool caused a 60%
reduction in the SLM manufacturing time.
1.2. Importance of Selecting Parts for AM Application
When compared to conventional production methods, metal AM is associated with
higher production costs [34]. Accordingly, not all parts are economically and technically
beneficial for AM application. The success of AM application depends on how the unique
capabilities of the technology can be exploited to cater for the needs of the industry.
Potential AM users often struggle to include AM in their production operations because
they lack the knowledge and skills necessary to identify applications that are beneficial
for AM application [27]. There is a need for more knowledge on the identification of part
candidates, which are suitable for AM adoption for the transport sector. Selection of part
candidates for AM is important to fully realise the economic and functional benefits of
the technology [35]. Klahn et al. [36] proposed a criterion for selecting part candidates
and assemblies with manufacturing processes that can be substituted with AM. In their
study, they concluded that AM can be replaced with conventional processes if there
are opportunities for integration of components, light weighting, efficient designs and
individualisation. After applying the criterion on real life parts, the results showed that
it was both economically and technologically beneficial to produce the parts with AM as
compared to the traditional processes. Booth et al. [37] developed a worksheet for assisting
designers to assess the potential quality of parts manufactured with AM. The worksheet
was also used to identify and rectify bad designs before they were built with AM. However,
the worksheet was purely technical and only focused on design issues. Reiher et al. [38]
developed a trade-off matrix to select part candidates for AM. The selected parts were
further evaluated for technological and economic feasibility of applying AM. This was
followed by redesigning of the selected part(s) to increase the technical and economic
benefits of AM application. However, the matrix was generic and not dedicated to a specific
application. Considering the fact that the needs of industry sectors are different, the matrix
may be subject to change. Yang et al. [39] developed a framework for selecting suitable
assemblies and parts which can be consolidated if manufactured with AM. According
to Materialise, an additive manufacturing company, there are five generic parameters
that determine whether AM is a suitable manufacturing process for a part [40]. These
include size, geometric complexity, value, function and production volume [40]. Although
those parameters are important to provide a general guideline for selection of parts, there
is a need to consider opportunities for design optimisation when considering transport
equipment parts. Yao et al. [41] proposed a machine learning algorithm which can be used
by designers and engineers to recommend part candidates for AM based on the geometric
features. The results obtained indicate that the proposed hybrid machine learning method
is feasible for generating conceptual design solutions for part designers. Merkt et al. [42]
developed a method of measuring geometric complexity of parts to assess whether they
are suitable for Selective Laser Melting (SLM) production. In their paper, they argued that
geometric complexity and lot size are the major factors for selecting parts suitable for SLM.
However, other parameters such as the material requirements, value of the part and its
functionality should also be taken into account. Based on previous studies, there is a need
for more information on screening of parts for AM application in the transport equipment
manufacturing industry to guarantee technical and economic benefits. Thus, the aim of this
paper is to propose an evaluation model for choosing part candidates for metal-based AM
applications depending on the needs of the transport equipment manufacturing industry.
In its structure, the paper firstly presents the parameters to be considered when developing
the model. Secondly, the model is developed using the Analytic Hierarchy process. Thirdly,
the model is evaluated using typical case studies from the literature. Lastly, the results are
discussed and a conclusion is given.
Metals 2021, 11, 765 4 of 18
2. Parameters for Selecting Part Candidates for AM Application
The first step involves identifying all the factors which can be considered in selecting
AM as an alternative manufacturing process. Table 1 gives a summary of the parameters
identified from the literature for selecting part candidates for AM application.
Table 1. Summary of the parameters used to select part candidates for AM application.
Author(s) Criteria for Selecting Part Candidates for AM Type of Method Used
Opportunity for design improvement through:
• Integrated design Selection of part for AM substitution
Klahn et al. [36] • Efficient design depended on the opportunities for
• Lightweight design design improvement.
• Individualisation
• Geometric complexity
• Quality/Functionality Developed a worksheet for identifying
Booth et al. [37] • Material removal part designs suitable for AM application
• Thin features depending on geometric features.
• Tolerances
• Part classification
• Opportunity to suppress assembly
• Geometric factors
• Processing time Developed a tradeoff matrix to screen
Lindemann et al. [35] • Opportunity to improve part through parts for AM application and evaluate
design optimisation the benefits.
• Material factors
• Processing time
• Economic factors
Developed a modularity-based
• Physical attributes of product (Geometry) framework for identifying parts and
Yang et al. [39]
assemblies that can be consolidated
using AM.
Hybrid machine learning method to
Yao et al. [41] • Geometric complexity select potential parts for AM application
depending on geometric features.
Method for measuring geometric
Merkt et al. [42] • Geometric complexity complexity and using it to identify
potential parts for AM application.
• Size
• Geometric complexity
Materialise [40] • Value Analysis of parts based on the criteria.
• Series size (production volume)
• Function
• Raw material optimisation (material usage) The criteria were ranked using three
• Weight savings decision-making approaches in order to
Cruz and Borille [43]
• Time to manufacture part determine whether AM was the most
suitable method.
The parameters in Table 1 are combined and classified into technical and economic
parameters, as shown in Table 2.
In the following sections, each of the parameters are further explained.Metals 2021, 11, x FOR PEER REVIEW 5 of 19
Metals 2021, 11, x FOR PEER REVIEW 5 of 19
Metals 2021, 11, 765 The parameters in Table 1 are combined and classified into technical and 5economic
of 18
The parameters in Table 1 are
parameters, as shown in Table 2. combined and classified into technical and economic
parameters, as shown in Table 2.
2. Summary
TableTable of the
2. Summary parameters
of
Metalsthe 11, xfrom
parameters
2021, the
from
FOR PEERliterature.
the literature.
REVIEW
Table 2. Summary of the parameters from the literature.
TechnicalTechnical Economic
Economic
Geometric
Geometric factors
factors Technical Economic
Geometric
• Complexity factors
Complexity The parameters in Table 1 are combined an
•
• Presence
Complexity •
• parameters,
Production Production
as shown involume
volume Table 2.
Presence of thin
of thin features
features • Production volume
Tolerances
Presence of thin features
Tolerances
Table 2. Summary of the parameters from the literatu
ofTolerances
Size part • Time to manufacture the part
• Time to manufacture the part
SizeSize
of part
Needoffor part
design improvement through • Time to manufacture
Technical the part
NeedNeedfor design improvement
for design throughthrough
improvement
• Weigh reduction Geometric factors
• • Weigh reduction • Material usage
• Weigh reduction
Part consolidation • • Material
Complexity
• Part consolidation • usage Material
Amount of usage
material removed
•
• Part consolidation
High performance material change Amount
Presence of thin removed
of material features
• High performance material change Amount of material removed
• •• Efficient
High performance
Efficient
design design material change Tolerances
•• Efficient
Functiondesign
of part Size of part
• • Function of partof part
Function • Value•of part Value of part
Need for • design Valueimprovement
of part through
In the following sections, each of the parameters • Weigh are reduction
further explained.
2.1. GeometricIn theComplexity
following sections, each of the parameters • Partare further explained.
consolidation
The competitive
2.1. Geometric Complexityadvantage offered by AM is •
freedom of design,
High performance as it allows
materialmanufac-
change
2.1.
turers to Geometric
produce Complexity According to •
The competitive advantage offered by AM is freedom of design, as it allowsthe
complex parts. previous studies,
Efficient AM
design can outperform manu-
conventional The subtractive
competitive processes
advantage foroffered
parts with
by AM•high isgeometric
freedom of
Function complexity
design,AM
part as[44].
it This manu-
allows is
facturers to produce complex parts. According to previous studies, can outperform
mainly becausetoinproduce
facturers AM, thecomplex
complexity of a According
parts. part has noto effect on thestudies,
previous efficiency AM of the
canprocess.
outperform
the conventional subtractive processes for parts with high geometric complexity [44]. This
Unlike
the conventional
conventional processes, no additional effort is required when producing the part.
is mainly becausesubtractive
in AM, the processes
complexity for parts with
of a part In the following sections, each [44].
high
has nogeometric
effect on complexity
the efficiencyof theofThis
the
param
When is itmainly
comesbecause
to conventional
in AM, the processes,
complexity increasing thehas complexity of the part resultsof the
process. Unlike conventional processes, noofadditional
a part no effect
effort on
is required the when
efficiency
producing
in increased
process. production costs. Onprocesses,
the otherno hand, the production costs in AM whenare not
the part. Unlike
When itconventional
comes to conventional additional
processes, effort
increasing
2.1. Geometric is the
required
Complexity complexity producing
of the part
directly
the affected
part. by the complexity of parts [35]. From the literature presented above, it is
results inWhen it comes
increased to conventional
production costs. Onprocesses,
the other increasing
hand,
Thesuitable the
competitive
the complexity
production
advantage costs of
in
offered
the
AMpartareAM
by
notedresults
that high complexity
in increased of parts is considered as more for AM when compared
not directly affectedproduction costs. On
by the complexity of the
partsother
[35].
facturers
hand,
From the
the
to produce
production
literature costs in AM
presented are
above,
to low complex parts. In this study, the approach taken to evaluate complex parts. According
the complexity of
not
it is directly
noted that affected by the complexity
high complexity of parts of parts [35]. From
is considered as morethe suitable
literature presented
for AM when above,
com-
parts is derived from the study that was conducted theby conventional
Booth et al. subtractive
[37]. According processes
to thisfor parts w
it is noted
pared to lowthatcomplex
high complexity of parts
parts. In this is considered
study, the approach as more
takensuitable
to for AM
evaluate the when com-
complexity
study, components with low geometry are classified as parts with basic shapes that are like of a p
is mainly because in AM, the complexity
pared
of parts to low complex parts. In thisthat
study,
wasthe approachby taken to evaluate
al. [37].the complexity
common stockismaterials
derived from theare
or that study
two-dimensional. conducted
process. Unlike
Additionally, Booth
highetcomplex
conventional According
processes,
parts are notoaddi
of
this parts
study,is derived
components from the
with study
low that was
geometry conducted
are classified by Booth
as parts et al.
with [37].
basic According to
those with interior features or those with surface curvatures the part. When whichitare comes to machine. that
shapes
to conventional
difficult process
this study,
arestudy,
like componentsmaterials
common with loworgeometry are classified as parts with basic shapes that
In this medium stock complex parts will that are two-dimensional.
be regardedresults in increased
as parts which Additionally,
production
can be machinedhigh
costs. complex
butOn the oth
are
parts like
arecommon
those stock
with materials
interior or that
features or are two-dimensional.
those with surface Additionally,
curvatures which high
are complex
difficult
require additional operations to achieve the required not directly
geometry. affected by the complexity of parts [
parts are those
to machine. withstudy,
In this interior features
medium or thoseparts
complex withwillsurface
be curvatures whichwhich
are difficult
it is noted thatregarded as parts
high complexity of partscan be
is consid
to machine.
machined
2.2. Value of the butIn this study, medium complex
Partrequire additional operations to parts will
achieve be regarded
thecomplex as
requiredparts. parts
geometry. which can be
pared to low In this study, the ap
machined but require additional operations to achieve the required geometry.
Considering the high production cost of metal of parts is deriveditfrom
AM processes, the study
is important tothat
con-was cond
sider the monetary value of the part [34]. For highthis value partscomponents
study, which are costly with tolowproduce
geometry are
with conventional processes, there is more economic benefit
are like commonwhen stock
AM ismaterials
used as an or alter-
that are two-
native. Typical high-value parts for AM application areare
parts presented
those within the literature
interior [45,46].
features or those w
to machine. In this study, medium complex part
2.3. Production Volume machined but require additional operations to a
Additive manufacturing is more economical for parts produced in low volumes to
eliminate the cost of tooling [38]. If the parts are produced in high volumes, the initial
tooling investment costs are distributed among all the products and the production cost
per part becomes low. On the other hand, if the product is required in low volumes, the
tooling costs are spread over a few parts and this makes the costs of producing individual
parts very high. Production volume can be classified as low, medium and high volume.
In this study, low volume production is when the annual units produced are 1000 or less,
medium volume parts vary from 1000 to 10,000 and high-volume parts are above 10,000.
2.4. Lightweight Design
In the transportation industry, there is an increased need for improving fuel efficiency.
This can be realised by producing lightweight transport equipment parts. To reduce weight,
the design of a part can be altered by removing excess material so that more emphasis isMetals 2021, 11, 765 6 of 18
placed on the functionality [47]. In that regard, geometries that are difficult to attain with
conventional processes are achievable. Another way to reduce weight is by shape and
topology optimisation [18].
2.5. High Performance Material Change
The material of a part can be substituted with a high-performance material to improve
functionality and extend the life cycle of a product. High-performance aluminium and
titanium alloys are material candidates for achieving improved strength of transport
equipment parts [47]. Accordingly, high performance materials can improve the value of
components. Typical examples of materials that are currently under investigation include
composite materials and particle reinforced metal matrix composites [48]. Titanium- and
nickel-based super alloys can also be processed using AM to produce high-performance
parts [49].
2.6. Improved Efficiency
AM gives opportunities to incorporate complex design features to improve the oper-
ating efficiency of engineering components. This includes the introduction of conformal
cooling channels to improve thermal performance of hot stamping tools for the automo-
tive industry [50]. Another typical example is on the use of AM to allow integration of
sensors in engineering components to allow monitoring and control of manufacturing
operations [32,49].
2.7. Reducing the Number of Components in an Assembly
The number of assemblies of a component can be reduced through part consolida-
tion [51]. This helps to reduce the costs and time needed to assemble parts. The function-
ality of the product should not be compromised. It is important to do an initial technical
evaluation before part consolidation is considered [26].
2.8. Material Usage
The amount of material removed from the part using machining should be considered.
Depending on the cost of material, if more than 50% of the material is removed from the
original stock, then the part is a potential candidate for AM application. This is a measure
to avoid material wastage, since AM uses the layer wise addition strategy to produce parts.
2.9. Function of the Part
The functionality of the part should be considered. The more critical the function, the
more suitable it is for producing with AM. This is because AM gives the opportunity for
further improving the performance through design optimisation. Examples of critical parts
which are suitable for AM application are explained in the literature [45,46]. It is important
to ask whether the part is a high-end industrial solution or not. If the functionality of the
product is not of greater concern than the cost, it becomes expensive to produce with AM.
Based on previous studies in the literature, the greatest economic benefits were realised
when AM was applied to produce high-value parts [52].
2.10. Time to Manufacture Component
The time taken to produce the part using the conventional methods should be com-
pared with the time for manufacturing with an AM integrated process chain. In most cases,
the AM route is time consuming; however, depending on the complexity, the conventional
methods may involve a lot of processes. Additionally, the time taken to produce the
necessary tools for conventional manufacturing should be considered.
2.11. Size of the Part
It is important to determine whether the part size can be accommodated by the
machine build envelope. In the event that the part is large, it can be subdivided intoMetals 2021, 11, 765 7 of 18
segments that can be separately manufactured and assembled afterwards [53]. This is
possible if the functionality of the part is not compromised. In summary, the criteria
considered are classified as shown in Table 3.
Table 3. Classification of criteria.
Criteria. Classification
High
Low Medium
Parts with interior features
Parts with basic shapes that Parts which can be machined
Geometric Complexity or those with surface
are similar to common stock but require additional
curvatures which are
materials [37] operations
difficult to machine [37]
Value of Part Low Medium High
Low Medium High
Production Volume (per year)
≤1000 1000–10,000 >10,000
Necessity for Design
Improvement Through
• Lightweight design None of the design At least one of the design More than one of the design
• Improved efficiency improvement methods improvement methods improvement methods
• High performance are necessary are necessary are necessary
material change
• Part consolidation
Low High
Medium
Less than 50% material More than 50% material
Material Removal 50% material removal using
removal using removal using
conventional methods
conventional processes conventional methods
Low High
Function of Part
Non-critical part Critical part
Time to produce a part with
Time to produce a part using
Time to Manufacture an AM-integrated process
the conventional processes is
Component chain is less than using
less than using AM
conventional methods
The part can be subdivided
Size of a part can be into segments which can be The part is larger than the
Size of Part accommodated into the built separately and build envelope and cannot
machine build envelope assembled without be subdivided
the function
Material required for
producing the part is not
Material required for available in powder form. An Material required for
Material producing the part is not alternative AM material can producing the part is
available in powder form be used without available in powder form
compromising the
functionality
3. Development of the Evaluation Model
In the next sections, the analytic hierarchy process is used to develop the evalua-
tion model.
3.1. The Analytic Hierarchy Process
The analytic hierarchy process (AHP) is considered for assigning weights to the criteria
because of its credibility in engineering decision-making applications. The AHP method
was also extensively applied in manufacturing applications [54,55]. In the first step, the
parameters are evaluated in pairs to determine the level of importance between them using
the scale from 1 to 9, as shown in Table 4.Metals 2021, 11, 765 8 of 18
Table 4. Pairwise comparison scale, data from [56]
Level of Importance Rating
Extreme Importance 9
Very Strong Importance 7
Strong Importance 5
Moderate Importance 3
Equal Importance 1
Compromise between the above values 2, 4, 6, 8
The values obtained from the pairwise comparison are used to populate a matrix
using Equation (1) [55]:
a11 a12 ... a1m
a21 a22 ... a2m
PM = (1)
.. .. .. ..
. . . .
am1 am2 ... amm
The matrix is normalised by dividing each element with the column sum as shown in
Equation (2) [56]:
a11 a12 a1m
∑im=1 ai1 ∑im=1 ai2
... ∑im=1 aim
a21 a22 ... a11
PMw = .. .. .. .. (2)
. . . .
am1 am2 amn
∑im=1 ai1 ∑im=1 ai2 ... ∑im=1 aim
The next stage involves calculating the weights of the criteria C using Equation (3) [56]:
C1
..
a11 a12 a1m
.
∑im=1 ai1
+ ∑im=1 ai2
+... ∑im=1 aim
C= ..
= (3)
.
m
..
Cm
.
am1 am2 amm
+ +...
∑im=1 ai1 ∑im=1 ai2 ∑im=1 aim
m
The next stage involves checking the consistency of the calculated weight. To achieve
that, the product of PM and C is calculated using Equation (4):
C
a11 a12 ... a1m 1 x1
a21 a22 ... a2m ..
x2
.
PM.C = = (4)
.. .. .. .. ..
..
. . . .
.
.
am1 am2 ... amm Cm xm
The next stage is to calculate the principal eigenvalue (δa ) using Equation (5) [55].
The principal eigenvalue is obtained by averaging the consistency values obtained from
Equation (4):
1 m ith entry in PM.C
m i∑
δa = (5)
=1
ith entry in CMetals 2021, 11, 765 9 of 18
The consistency measurement CI is calculated as shown in Equation (6) [56]:
δa − m
CI = (6)
m−1
The ratio CI/RI is then used to evaluate the consistency of the weights. The quantity
RI represents the random indices, which are shown in Table 5.
Table 5. Random Indices (Ishizaka and Nemery, 2013).
n 1 2 3 4 5 6 7 8 9 10
RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49
If the ratio is less than or equal to 0.1, the calculated weights are considered consistent.
Likewise, a ratio more than 0.1 indicates inconsistency in the calculations. In the next
section of the paper, the proposed method is evaluated using a typical benchmark part.
3.2. Application of the AHP Method to Assign Weights to Criteria
For the proposed evaluation method, size and material compatibility are considered
the most important factors and are used for the initial screening. The rest of the parameters
are used in formulating the model. As mentioned in Section 2.1, the first step is to come up
with the pairwise comparison matrix of the criteria using Equation (1), as shown in Table 6.
Table 6. Pairwise comparison matrix.
Design Im- Geometric Production Value Material Time to
Function
provement Complexity Volume of Part Removal Manufacture
Design improvement 1 1/3 1/3 1 5 1 4
Geometric complexity 3 1 2 2 6 3 5
Production Volume 3 1/2 1 1 6 5 5
Value of the Part 1 1/2 1 1 5 1 4
Material removal 1/5 1/6 1/6 1/5 1 1/5 1
Function 1 1/3 1/5 1 5 1 5
Time to manufacture 1/4 1/5 1/5 1/4 1 1/5 1
The matrix is normalised using Equation (2), as shown in Table 7.
Table 7. Normalised matrix.
Design Im- Geometric Production Value Material Time to
Function
provement Complexity Volume of Part Removal Manufacture
Design improvement 0.106 0.110 0.068 0.155 0.172 0.088 0.160
Geometric complexity 0.317 0.330 0.408 0.310 0.207 0.263 0.200
Production Volume 0.317 0.165 0.204 0.155 0.207 0.439 0.200
Value of the Part 0.106 0.165 0.204 0.155 0.172 0.088 0.160
Material removal 0.021 0.055 0.034 0.031 0.034 0.018 0.040
Function 0.106 0.110 0.041 0.155 0.172 0.088 0.200
Time to manufacture 0.026 0.066 0.041 0.039 0.034 0.018 0.040
The weights in terms of the degree of importance and consistency values are calcu-
lated using Equations (3) and (4). Table 8 gives the obtained weights and consistency
measurements.Metals 2021, 11, 765 10 of 18
Table 8. Criteria weights.
Criteria Weight Consistency Measure Rank
Geometric complexity 0.291 7.577 1
Production Volume 0.241 7.961 2
Value of the Part 0.15 7.343 3
Function 0.125 7.186 4
Design improvement 0.123 7.255 5
Material removal 0.033 7.251 6
Time to manufacture 0.038 7.122 7
The consistency ratio is calculated as shown below:
0.0642
CR = = 0.0107 (7)
1.32
The computed value is below 0.1; hence, the obtained weights are considered consis-
tent and they are applied in the decision matrix, as shown in Table 7.
3.3. Proposed Evaluation Method
As mentioned previously, the most important factors when evaluating parts for AM
application are the size and material compatibility. Considering that most AM machines
have a build volume of around 250 × 250 × 250 mm, it is necessary to first evaluate whether
the part dimensions will be accommodated into the machine. Large parts can be divided
into subcomponents, which can be built separately and assembled afterwards. However,
this can only be done if the functionality of the part is not affected. Another way is to build
certain portions of the part additively while other portions can be machined. If the material
required for producing the part is not available in powder form, an alternative material
which does not alter the functional properties of the part can be used.
The next stage is to evaluate the part using the calculated criteria in Table 8.
To use the evaluation matrix in Table 9, the total weight of each criteria is calculated
by obtaining the product of weight (C) and level j. The total weight for the part is obtained
by summing all the separate total criteria weights as shown in Equation (8):
6
V= ∑ aij .Ci Criteria i = 1 . . . 6 and level j = 1.2.3 (8)
i =1
Using the total weight (V) obtained from Equation (8), the following conditions apply:
Not suitable for AM application 1 ≤ V ≤ 1.5.
Part is suitable for AM after changes in design 1.5 < V ≤ 2.0.
Part suitable for AM application without necessarily making design changes 2.0 < V ≤ 2.55.
Table 9. Decision matrix for selecting part candidates.
Criteria (a) Weight (C) Classification
Low Medium High
Geometric Complexity 0.291
1 2 3
High Medium Low
Production Volume 0.241
1 2 3
Non critical Critical
Function 0.125
1 3
At least one of the design More than one of the
Opportunity for Design None improvement methods is design improvement
0.123 necessary methods are necessary
Improvement
1 2 3Metals 2021, 11, 765 11 of 18
Table 9. Cont.
Criteria (a) Weight (C) Classification
3
1
Time to produce parts
Time to produce part
with an AM-integrated
Time to Manufacture 0.038 using conventional
process chain is less than
processes is less than
using conventional
using AM
methods
Low Medium High
Less than 50% material 50% material removal More than 50% material
Material Removal 0.033
removal using using conventional removal using
conventional processes methods conventional methods
4. Evaluation of Model
The next stage is to evaluate the model by using case studies from the literature.
4.1. Case Studies
In the following sections, case studies from the literature are presented and analysed.
4.1.1. Case Study 1
The first case study component is a turbine blade. The part has been considered for
AM application by different authors in the literature [57,58]. The turbine blade is a critical
high value component for extracting combustion energy by diverting current flow. As a
result, it is exposed to high temperature conditions. The conventional processes involved
in producing the part are time consuming and costly due to the tooling required [57].
A study was conducted by Dimitrov et al. [59] to measure the cost and material usage
Metals 2021, 11, x FOR PEER REVIEW 12 of 19
when the turbine blade is produced using three process chains. Those include machining
only, forming with machining an AM with machining.
Based on the graphs in Figure 1, using AM results in the least material usage while
machiningBased has aonhigher
the graphs
usageinof
Figure 1, using
material. In AM results
terms in overall
of the the leastcosts,
material usage while
forming with
machining has a higher usage of material. In terms of the overall costs, forming with ma-
machining is cheaper for high volume production (100), machining is the cheapest option followed by AM with machining. However,
machining is the cheapest option followed by AM with machining. However, considering
considering the high material wastage involved in machining, it would be more sustainable
the high material wastage involved in machining, it would be more sustainable to apply
to apply AM for low-volume part production.
AM for low-volume part production.
FigureFigure 1. (a) Material
1. (a) Material usageusage results;
results; (b) cost
(b) cost results,
results, reproduced
reproduced from
from [59],
[59], with
with thethe permissionfrom
permission
from IOP Publishing,
IOP Publishing, 2018. 2018.
4.1.2. Case Study 2
4.1.2. Case Study 2
Case study 2 was obtained from a study by Abdi and Wilderman [60]. In the study,
Case study 2 was obtained from a study by Abdi and Wilderman [60]. In the study,
a brake pedal for a special formula race car was considered for AM application. This was
a brake pedal for a special formula race car was considered for AM application. This
motivated by the need to improve the design through increasing stiffness (reducing com-
pliance) of the pedal. Since the brake pedal is for a customised vehicle, the production
volume is low. The brake pedal is a critical safety component for stopping or slowing
down the special vehicle and is considered a high value component. The shape of the
pedal is shown in Figure 2 and it is considered to be of medium complexity using the
criteria in Table 3.Figure 1. (a) Material usage results; (b) cost results, reproduced from [59], with the permission
from IOP Publishing, 2018.
4.1.2. Case Study 2
Case study 2 was obtained from a study by Abdi and Wilderman [60]. In the study,
Metals 2021, 11, 765 12 of 18
a brake pedal for a special formula race car was considered for AM application. This was
motivated by the need to improve the design through increasing stiffness (reducing com-
pliance) of the pedal.
was motivated Since
by the needthe
to brake
improve pedal
theisdesign
for a through
customised vehicle,stiffness
increasing the production
(reducing
volume is low. The brake pedal is a critical safety component for stopping or
compliance) of the pedal. Since the brake pedal is for a customised vehicle, the production slowing
down the is
volume special vehicle
low. The brakeand is considered
pedal a highcomponent
is a critical safety value component. Theorshape
for stopping slowingof down
the
pedal is shown in Figure 2 and it is considered to be of medium complexity
the special vehicle and is considered a high value component. The shape of the pedal using the is
criteria in Table 3.
shown in Figure 2 and it is considered to be of medium complexity using the criteria in
Table 3.
Figure 2. (a)
Figure Original
2. (a) design.
Original (b)(b)
design. Optimised design
Optimised 1. (c)
design Optimised
1. (c) design
Optimised 3, reproduced
design from
3, reproduced from [60],
[60], with the permission from Inderscience,
with the permission from Inderscience, 2018. 2018.
Figure 3 shows
Figure 3 shows thethe
maximum
maximum Von Mises
Von after
Mises conducting
after conducting simulation
simulationof the designs.
of the designs.
Table
Table 10 10 shows
shows the the volume,
volume, maximum
maximum Von Von
MisesMises and stiffness.
and stiffness. Optimised
Optimised design design
1 was 1
was considered
considered for the application
for the application because
because it it in
resulted resulted in the
the highest highest(lowest
stiffness stiffness (lowest
compli-
compliance).
ance). A maximum A maximum stress constraint
stress constraint was not was not considered
considered in the design,
in the design, althoughalthough
all theall
Metals 2021, 11, x FOR PEER REVIEW 13 of 19
the maximum
maximum Von Mises
Von Mises valuesvalues
were were
belowbelow the yield
the yield strength
strength of theofmaterial
the material
used,used,
which which
is
is a selective
a selective laser-melted
laser-melted Ti-6Al-4V.
Ti-6Al-4V.
Figure 3. (a) Existing pedal (b) Optimised design 1 (c) Optimised design 2 Map showing the Von
Figuredistributions,
Mises 3. (a) Existing pedal (b) Optimised
reproduced design
from [60], with the1 permission
(c) Optimised design
from 2 Map showing
Inderscience, 2018. the Von
Mises distributions, reproduced from [60], with the permission from Inderscience, 2018.
Table 10. Comparison of the three designs.
Table 10. Comparison of the three designs.
Max Von Mises
Volume (m3 ) MaxStress Mises Stress Compliance
Von (MPa)
Volume (m ) 3 Compliance
Existing Pedal (a) 72.1 (MPa)
5012 95.312
Existing Pedal (a) 72.1 5012 95.312
Optimised Design 1 (b) 70.8 458 0.994
Optimised Design 1 (b) 70.8 458 0.994
Optimised Design 2 (c) 54.6 976 2.032
Optimised Design 2 (c) 54.6 976 2.032
4.1.3. Case Study 3
Case study 3 is a hot forming tool for a gear pan for an automotive powertrain com-
ponent [32]. The part is considered a critical component of the powertrain which is pro-Metals 2021, 11, 765 13 of 18
4.1.3. Case Study 3
Case study 3 is a hot forming tool for a gear pan for an automotive powertrain
component [32]. The part is considered a critical component of the powertrain which is
produced in low volumes. The shape of the tool was such that it does not have space
for drilled channels to allow for thorough cooling of the part during hot forming. As
a result, the tool was exposed to increased thermomechanical wear and the produced
parts did not have the uniform hardness required. The conventional tool is considered
Metals 2021,
Metals 2021, 11,
11, xx FOR
FOR PEER to have a medium complex geometry because it did not have internal cooling channels.
PEER REVIEW
REVIEW 14 of
14 of 19
19
The tool is produced as a singular unit; hence, the production volume is considered low.
The additively manufactured tool had innovative adaptive cooling channels, as shown in
Figure 4.
Figure
Figure 4.
Figure 4. (a)
4. Gearpan
(a) Gear
Gear pancomponent;
pan component;(b)
component; (b)gear
(b) gearpan
gear pan
pan tool
tool
tool system
system
system with
with
with adoptive
adoptive
adoptive cooling
cooling
cooling channels;
channels;
channels; (c) temperature
(c) temperature
(c) temperature mapmap
map of
of con-
of con-
ventional tool
conventional
ventional tool (top)
tool and
(top)
(top) and additively
and additively
additively manufactured
manufactured
manufactured tool with
toolwith
tool adoptive
withadoptive cooling
adoptivecooling channels
coolingchannels (bottom),
channels(bottom), reproduced from
(bottom), reproduced from [32],
[32],
withthe
with
with thepermission
the permissionfrom
permission fromiCAT,
from iCAT,2016.
iCAT, 2016.
2016.
According
Accordingto
According tothe
to theresults,
the results,the
results, thecooling
the coolingtime
cooling timewas
time wasreduced
was reducedfrom
reduced from10
from 10to
10 to333s,
to s,which
s, whichtranslates
which translates
translates
to reductionof
to aa reduction
reduction of70%.
of 70%.Additionally,
70%. Additionally,
Additionally, thethe
the quality
quality
quality of parts
of the
of the the
partsparts improved
improved
improved to increase
to increase
to increase the
the hard-
the hard-
hardness
ness uniformity.
ness uniformity.
uniformity. The The additively
The additively
additively manufactured
manufactured
manufactured tool tool
tool waswas
was expected
expected
expected betomore
to be
to be more
more durable
durable
durable as aa
as
as a result
result
result of of reduced
of the
the the reduced
reduced thermomechanical
thermomechanical
thermomechanical wear.
wear.wear.
4.1.4.
4.1.4. Case
4.1.4. Case Study
Case Study 444
Study
Case
Casestudy
Case study444isis
study isa aacabin
cabinbracket
cabin connector
bracket
bracket forfor
connector
connector airbus
for A350XWB
airbus
airbus A350XWB
A350XWBas shown in Figure
as shown
as shown 5 [15].
in Figure
in Figure 55
The
[15].improved
[15]. The part
The improved was
improved part produced
part was using
was produced Selective
produced using Laser
using Selective Melting
Selective Laser (SLM).
Laser Melting
Melting (SLM).
(SLM).
Figure 5.
Figure 5. Cabin
Cabin bracket,
bracket, reproduced
reproducedfrom
reproduced from[61].
from [61].
[61].
The
The part
part is
is aa high
high value
value component,
component, which
which is is produced
produced inin low
low volumes.
volumes. The conven-
tional
tional process
process ofof manufacturing
of manufacturing the
manufacturing the part
part is
part is milling
is millingusing
milling usingaluminium.
using aluminium. The
aluminium. The design
design ofof the
the
the
part
part was
was enhanced
enhancedusing
enhanced usingtopology
using topologyoptimisation
topology optimisationto
optimisation toreduce
to reduceweight.
reduce weight.As
weight. Asseen
As seenin
seen inFigure
in Figure5,
Figure 5,the
5, the
the
original part
original part geometry
geometry can can be
be considered
considered asas having
having medium
medium complexity
complexity using
using the
the criteria
criteria
in Table
in Table 9.
9. When
When the the component
component waswas manufactured
manufactured usingusing the
the laser
laser powder
powder bedbed fusion
fusion
process (LPBF),
process (LPBF), aa weight
weight reduction
reduction of
of 30%
30% waswas archived.
archived. The
The manufacturing
manufacturing timetime was
was
reduced by
reduced by 75%.
75%. Figure
Figure 55 shows
shows the
the original
original and
and improved
improved design.
design.Metals 2021, 11, 765 14 of 18
original part geometry can be considered as having medium complexity using the criteria
in Table 9. When the component was manufactured using the laser powder bed fusion
process (LPBF), a weight reduction of 30% was archived. The manufacturing time was
reduced by 75%. Figure 5 shows the original and improved design.
4.2. Validation of Model Using Case Studies
The next step is to evaluate the model in Table 9 using the case studies presented.
Table 11 shows the calculated weights for the four case studies.
Table 11. Weight calculations using the case studies.
Criteria (a) Weight (C) Classification Case 1 Case 2 Case 3 Case 4
Geometric Low Medium High
Complexity 0.291 0.873 0.582 0.582 0.582
1 2 3
Production High Medium Low
0.241 0.723 0.723 0.723 0.723
Volume 1 2 3
Non critical Critical
Function 0.125 0.375 0.375 0.375 0.375
1 3
At least one of More than one
the design of the design
Opportunity None improvement improvement
for Design 0.123 0.123 0.246 0.246 0.246
methods is methods are
Improvement necessary necessary
1 2 3
Time to
Time to
produce part
produce parts
using
with AM is less
Time to conventional
0.038 than using 0.114 0.038 0.038 0.114
Manufacture processes is
conventional
less than using
methods
AM
1 3
Low High
Medium
Less than 50% More than 50%
50% of material
Material of material of material
0.033 removal using 0.033 0.033 0.033 0.033
Removal removal using removal using
conventional
conventional conventional
methods
processes methods
Total 2.208 1.997 1.997 2.073
4.3. Results and Discussion
In the first case study, the total weight calculated was 2.208, which is within the region
for considering the part for AM application. According to the information from the case
study, it was more economical in terms of costs and material usage to produce the part
with AM in low volumes. However, no further changes were made on the geometry. This
is mainly because the main motivation of using AM was to reduce the effort and time
to manufacture the part. In the second case study, the total weight calculated was 1.997,
which is within the region of applying AM after making changes on the part design. In case
study 2, it was necessary to change the part design as a measure of improving the stiffness.
The improved design had a low Von Mises stress and higher stiffness when compared to
the original design. In case study 3, the total weight calculated was 1.997, and this indicates
the need for design improvement before applying AM as an option. Accordingly, the
design of the hot forming tool was enhanced to incorporate conformal cooling channels.Metals 2021, 11, 765 15 of 18
Based on the information from the case study, a significant economic benefit would be
derived from using the tool in mass production. This is because of the massive reduction
in the cooling time of the part, which can outweigh the initial investment cost of producing
the tool using AM. In the last case study, the total weight obtained was 2.073, which is
within the region for AM application without necessarily making design changes. This is
slightly different from the situation on the case study because the part design was further
improved before it was additively produced. The reason behind this deviation is that the
designer wanted to fully exploit the design capabilities offered by AM since there are no
extra costs for complexity.
5. Conclusions
In conclusion, if proper measures are put in place, AM has the potential to positively
impact the transport sector. The following contributions were made in the present study:
• The opportunities offered by AM in the production of transport equipment parts were
explained using previous studies from the literature. These include producing high
performance parts with improved designs and high value parts which are produced
in low volumes.
• An evaluation model for choosing part candidates for AM application in the transport
sector was developed. To formulate the mode, the AHP processes was used to rank
the criteria and assign weights depending on the needs of the transport equipment
manufacturing industry. The criteria used were obtained from previous studies.
• Different case studies from the literature were used to validate the proposed decision
matrix. The calculated weights obtained from the various case studies were in agree-
ment with the evaluation model. Hence, the proposed model is a suitable tool that
can be used to guide the user to identify parts suitable for AM application.
• The proposed method is not only useful for identifying parts for AM application but
also gives direction on value addition of the selected part candidates through design
improvement. Hence, this study will add to the understanding of how transport
equipment manufacturing industries can effectively screen potential part candidates
and obtain value, thereby promoting the overall sustainability of the AM process in
terms of material conservation, cost effectiveness, and functionality.
• The study will add to the understanding of how transport equipment manufactur-
ing industries can effectively screen potential part candidates, thereby promoting
the overall sustainability of the AM process in terms of material conservation, cost
effectiveness, and functionality.
• Future studies should include a thorough cost–benefit analysis to further provide the
economic justification of the proposed model.
Author Contributions: R.M. developed the model and wrote the paper. K.M. supervised the research
and assisted with the methodology. I.D. assisted with information regarding the case studies and
editing of the paper. All authors have read and agreed to the published version of the manuscript.
Funding: The DSI—NRF SARCHI Chair in Future Transport Manufacturing Technologies funded
this research.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: All the data used are presented in the manuscript.
Acknowledgments: The authors would like to acknowledge the Department of Industrial Engineer-
ing for their support in the research.
Conflicts of Interest: The authors declare no conflict of interest.Metals 2021, 11, 765 16 of 18
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