Product innovation management model based on manufacturing readiness level (MRL), design for manufacturing and assembly (DFMA) and technology readiness level (TRL)

Abstract

Many companies have been reorganizing from a sequential to an integrated path known as simultaneous engineering, which aims to reduce development time and costs. The main problem during technology and product development is the integration of the design and manufacturing areas in the product development phase. This paper proposes a model to improve the use of simultaneous engineering by integrating project and manufacturing knowledge areas based on concepts of manufacturing readiness level, design for manufacturing and assembly and technology readiness level. Based on a bibliographic review and a preliminary study conducted over 1 year in a multinational metalworking company, a model was proposed as a method to be applied in the early stages of product development. The results show an integration of proposed engineering areas into a product development process, a cost reduction of 20% and a manufacturing investment reduction of 25%.

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Journal of the Brazilian Society of Mechanical Sciences and Engineering (2021) 43:360
https://doi.org/10.1007/s40430-021-03080-8
TECHNICAL PAPER
Product innovation management model based onmanufacturing
readiness level (MRL), design formanufacturing andassembly (DFMA)
andtechnology readiness level (TRL)
CristianoVasconcellosFerreira1 · FernandoLuizBiesek1· RégisKovacsScalice1
Received: 20 July 2020 / Accepted: 14 June 2021 / Published online: 23 June 2021
© The Brazilian Society of Mechanical Sciences and Engineering 2021
Abstract
Many companies have been reorganizing from a sequential to an integrated path known as simultaneous engineering, which
aims to reduce development time and costs. The main problem during technology and product development is the integration
of the design and manufacturing areas in the product development phase. This paper proposes a model to improve the use of
simultaneous engineering by integrating project and manufacturing knowledge areas based on concepts of manufacturing
readiness level, design for manufacturing and assembly and technology readiness level. Based on a bibliographic review and
a preliminary study conducted over 1year in a multinational metalworking company, a model was proposed as a method to
be applied in the early stages of product development. The results show an integration of proposed engineering areas into a
product development process, a cost reduction of 20% and a manufacturing investment reduction of 25%.
Keywords Product management· Innovation process· Technology innovation· Manufacturing
1 Introduction
The product development process (PDP) is complex for its
multidisciplinary knowledge [1]. A structured PDP is essen-
tial for an industry’s competitiveness and survival and is
composed of multifunctional activities influenced by many
internal and external factors [2]. Many companies compet-
ing in today’s international scenario consider the PDP an
important factor to hold competitive advantages [3].
Project success requires maturity from technologies that
will be used in the products. Innovation projects employ
technologies that need research and development. An exam-
ple of a management approach for such type of project is
given by Marxt etal. [4], which state that, in a context of
innovative projects where technologies are yet to mature,
some initial stages should be added to the traditional PDP
for technology finalization and confirmation of its commer-
cial potential (products that it can generate). The authors
propose the inclusion of such initial stages, which they call
the stage-gates of technology, into the traditional stage-gate
model of Cooper [5]. In Cooper’s model, the development
of new products is organized into a list of predetermined
stages, with a list of parallel cross-functional activities and
gates for decision making [6].
Regarding innovation management, Araújo and Mock-
zdlower [7] created a category of innovation named pre-
competitive technological innovation, through which a
company’s mastery for certain technologies, which can be
adopted in the development of new products, is sought. In
this context, the technology maturity evaluation matters
because low-maturity projects need time to mature.
To evaluate the maturity of new technologies, the
National Aeronautics and Space Administration (NASA)
introduced a scale called the technology readiness level
(TRL) [8, 9]. In addition, the US Department of Defense
(DoD) has a manufacturing readiness level (MRL) scale
to measure the maturity of manufacturing technologies
Technical Editor: Monica Carvalho.
* Cristiano Vasconcellos Ferreira
cristiano.v.ferreira@ufsc.br
Fernando Luiz Biesek
fbiesek@hotmail.com
Régis Kovacs Scalice
regis.scalice@ufsc.br
1 Joinville Technological Center, Federal University ofSanta
Catarina (UFSC), Rua Dona Francisca, 8300 – Bloco U,
Zona Industrial Norte, Joinville, SCCEP89.219-600, Brazil

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similarly to the Office of Secretary of Defense (OSD) Manu-
facturing Technology Program.
In an industrial scenario in which companies are affected
by an increasing global pressure for more competitiveness,
businesses have been reorganizing their product develop-
ment processes from a sequential to an integrated path
known as concurrent engineering or simultaneous engineer-
ing [3] [10].
Simultaneous engineering is a systematic approach to
integrated and concurrent product design and related pro-
cesses, including manufacturing and support, which aims
to reduce development time and costs by improving qual-
ity and competitiveness through the integration of different
areas of knowledge during a product’s life cycle, with the
Design for Manufacture and Assembly (DFMA) as one of
the main approaches to achieve concurrent engineering (CE)
applications [11].
In that scenario, seeking to reduce product development
time and cost through the integration of the design and man-
ufacturing knowledge areas, using tools such as the TRL and
the MRL, the main objective of this work is to propose a
systematic model for the integration of design and manufac-
turing during the development stage of technology products,
through the use of MRL, TRL and DFMA.
Considering that the use of the simultaneous engineering
approach during the PDP is important to increase a product’s
chance of success, Valle [3] concluded that the execution of
overlapping project activities and the integration of cross-
functional teams and teamwork positively affect the PDP
regarding time for incremental and cost-effective changes
and for radical innovation. Incremental changes are those
affecting existing products, while radical changes happen
to new products with a low technology maturity that need
research and development.
A PDP involves a complete product development cycle,
from research and development up to implementation.
There are many PDP models available in the literature and
most can be organized into five phases, namely: (1) basic
research; (2) technological development, when research and
development take place and can later result in a product; (3)
conceptual studies; (4) preliminary design; and (5) detailed
design and product certification, which is a macro-phase of
product innovation. Phase 2 is an important stage called pre-
competitive technological innovation by Araújo and Mock-
zdlower [7].
The product development process (PDP) is important for
industrial competitiveness. On the other hand, the integra-
tion of the design and manufacturing areas into the product’s
technology development phase can be a problem. In this
context involving basic research and pre-competitive tech-
nological innovation as a path to a good product design, the
main justifications, as well as the motivations for this work,
are observed as follows:
• The lack of integration between the design and manu-
facturing areas during the technology development and
product development phases, and the organizational
structure and the way work is organized, limiting the
implementation of simultaneous engineering and its
potential benefits. [3, 7]
• The need for real metrics to help assess uncertainties in
manufacturing-related research and development, such
as the degree of difficulty [12].
• The need for tools that enable a common language for
design and manufacturing teams. [13]
• The need for tools to clearly present manufactur-
ing design requirements and to measure the evolution
throughout the maturity phases. [13]
This work’s motivation is the development of a process to
integrate the design and manufacturing areas in the product
development phase mainly to reduce cost, risks and time to
market.
Another justification of this paper is based on the research
developed by Högman and Johannesson [10]. According the
authors, if a company wants to apply the stage-gate model to
technology development, it should consider developing an
adapted model. The level of sophistication of such model,
including, for example, the number of stages, explicitly
showing model iteration or formalism, should be based on
the needs of the organization. The size of the organization
and the number of organizational interfaces will impact the
model design, as will the degree of uncertainty of its tech-
nology development. Furthermore, the company needs to
accommodate a more flexible approach to apply the model,
when compared to product development. Iterations, loop-
backs, recursive model use, redefinition of development
goals and objectives based on generated new knowledge
and flexibility in timing are approaches which need to be
considered for the model to be beneficial to the company.
This research is based on the following hypothesis: the
use of DFMA in projects contributes to reduce costs, fail-
ures and time, as the project is carried out with manufactur-
ing and assembly in mind. The use of DFMA associated
with TRL and MRL, which measure maturity, can also help
reduce cost, risk and time, as the more mature the technol-
ogy and the process, the lower the chance of failures.
2 Literature
2.1 Product development process andinnovation
Innovation management is central in academic and business
environments. However, the implementation of effective
innovation management necessarily involves the adoption

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of models that guide the construction of organizational pro-
cesses through which innovation must be conducted [14].
Innovation is a multistage process through which organi-
zations transform ideas into new or significantly improved
goods, services or processes with the aim of progressing,
competing, or successfully standing out in the marketplace
[14]. Models with such purposes have been published in the
last decades and reflect the great plurality of approaches, a
consequence of innovation management being a multidis-
ciplinary area.
The product development process is represented by mod-
els composed of phases, stages, activities and tasks, through
which a multidisciplinary team develops a product, simulta-
neously considering, throughout its development, the needs
and constraints of the product’s life cycle [15].
In the literature, there are several models for the prod-
uct development process. For this work, the models used as
reference and theoretical basis are the traditional stage-gate
of Cooper [5, 16], the technological stage-gate (TSG) pro-
posed by Marxt etal. [4] and the reference model proposed
by Rozenfeld etal. [17]. The first was chosen because it is
mature and used by companies today, the second because it
is a generic model that proposed an adaptation of the tradi-
tional one, and the third because it is a current model applied
to manufacturing companies and consumer goods.
The stage-gate is characterized by the procedural form
that materializes the knowledge along the proposed stages.
This model is organized as a list of predetermined stages
called gates, which control the processes and serve as evalu-
ation points, as follows: (a) selection of ideas; (b) research
and development; (c) implementation; and (d) introduction
to the market.
Cooper [16] presents a next-generation idea-to-launch
system—the triple-A system. According Back etal. [15],
the practices and recommendations of firms creating new
idea-to-launch systems look a lot like the traditional pro-
cess; there are still stages where work gets done, and there
are still gates where decisions are made. But the details of
the process and its functions are different: what emerges is
a more agile, vibrant, dynamic, flexible gating process that
is leaner, faster, more adaptive and risk based. These are the
challenges about the stage-gate models. Figure1 presents
an overview of the next-generation idea-to-launch system.
Technology stage-gates (TSG) include the stages of tech-
nology development. Such phases are introduced during
product ideation. These TSG can start in the research and
development phase of the Cooper model [5], going all the
way to the end of the product’s life cycle. In the TSG, there
are technical reviews (TRs), which are formalized through
a technical review committee (TRC). The main purpose of
such reviews is to ensure the scope of a project throughout
the product’s life cycle. Like so, the phases of research and
development (R&D) can be associated with the phases of
traditional product development. The main use of the TSG is
in projects whose technologies are still in development, with
high levels of uncertainty as to the real market potential, that
is, in typical cases of R&D projects.
An experience from six hardware-oriented companies
applying stage-gate to technology development is presented
by Högman and Johannesson [10]. According to the authors,
the stage-gate model has been proposed for application in
uncertain technology development. Reports on industrial
experience from such implementations are quite limited,
however. In those scenarios, Högman and Johannesson [10]
explore, in six companies, what adaptations have been made
to facilitate the model’s usefulness for technology devel-
opment and the companies’ experiences from their practi-
cal model application. The results indicate that important
Fig. 1 Next-generation idea-to-
launch system [16]

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aspects for the operational success, or failure, of the model
include the level of adaptation to the characteristics of tech-
nology development and a more flexible use than that nor-
mally found in product development.
Högman and Johannesson [10] identified that all six
companies employed the stage-gate model to manage the
technology development process, but the implementation
details differ in a number of gates, the level of adaptation,
and whether a dedicated model was developed. Nonethe-
less, Högman and Johannesson [10] conclude that adapting
the model to the high level of uncertainty characterizing
technology development and the need for exploration has
proven to be a successful strategy. Furthermore, Högman
and Johannesson [10] also found a more flexible use of the
model than what is normally acceptable in product develop-
ment. Employed strategies included loopbacks over one or
more stages, delaying gates, redefining projects, conducting
development as a project relay race, and using the model
recursively. These were adaptations in the different compa-
nies to manage the inherent uncertainties.
The model proposed by Rozenfeld etal. [17] is divided
into three macro-phases called pre-development, develop-
ment and post-development, which can be generally divided
into some design phases called:
• Strategic product planning: Considers market strategies
and technologies.
• Project planning: Considers aspects related to the project
plan itself.
• Informational project: Tries to define target specifica-
tions.
• Conceptual design: Deals with product design, prelimi-
nary specifications and macro-production process.
• Detailed design: Has a homologated product and its final
specifications as the output.
• Preparation for production: Releases process production
and homologation.
• Product launch. Deals with the sales process, technical
assistance, distribution and customer service.
2.2 Technology readiness level (TRL)
andmanufacturing readiness level (MRL)
To support project development from the research phases,
two technology-maturity measurement scales are presented
for both the product that is being created and the manufac-
turing processes. Such scales are called technology readiness
level (TRL) and manufacturing readiness level (MRL).
According to Olechowski etal. [18], TRL is a scale cre-
ated by NASA in the 1970s to measure the maturity of tech-
nologies during the development of complex systems.
The MRL, as initially referred to in the OSD Manu-
facturing Technology Program [8, 9], was developed by
the US Department of Defense (DoD), whose idea was to
create a scale to serve manufacturing the same purpose
that TRL served technology, so there would be a common
vocabulary, and evaluations of manufacturing maturity
levels could be made into projects.
Maturity measurements start with the maturity scale
of technology, TRL. Mankins [8, 9] considers time, scope
and budget constraints to establish a technology maturity
rating scale. The author adds that, in the mid-1970s, the
American National Aeronautics and Space Administration
(NASA) improved the concept to allow for a more effec-
tive maturity assessment of new technologies. In 1995,
the scale was improved, making the definition of each
maturity level clearer. Since then, it has been adopted by
the Department of Defense (DoD) and the Government
Accountability Office (GAO) in new technology develop-
ment projects. In general, TRL has been highly effective
in communicating the state of new technologies between
different areas and organizations.
NASA’s technology maturity scale has 9 levels described
as: TRL 1—basic principles observed and reported, TRL
2—technology concept or application formulated, TRL
3—experimental and/or analytical proof-of-concept for
critical function and characteristics, TRL 4—component
or breadboard validation in a laboratory environment, TRL
5—component or breadboard validation in a relevant envi-
ronment, TRL 6—system or subsystem model or prototype
demonstrated in a relevant environment, TRL 7—system
prototype demonstration in an operational environment, TRL
8—actual system completed and “flight qualified” through
test and demonstration and TRL 9—actual system “flight
proven” through successful mission operations.
In NASA’s TRL, products presented up to level 5 are
components or circuit boards that, in later levels, will be
connected to larger systems or subsystems. The 9 levels of
maturity go from just the basic research principles observed
and reported up to real systems approved through success
on a real mission.
As Mankins [8] points out, the scale shown in Fig.1 was
not born all at once. Its development has had many approval
steps from the aerospace technology community for sev-
eral decades, from the first uses by closed NASA research
groups to the preliminary use by the industry and other space
agencies. In order to integrate the traditional PDP with the
development of technology, Araujo and Mockzdlower [7]
applied the PDP to the technology maturity levels, including
the R&D stages, in an aeronautical company. This process is
divided into two major phases called pre-competitive tech-
nological innovation and product innovation, in addition to
the basic research phase.
Basic research and pre-competitive R&D are correlated
with levels 1 through 6 of the original TRL scale. Note that
the TRL, despite being designed for aerospace applications,

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can be easily adapted to any type of environment, including
other industrial sectors.
According to Araújo and Mockzdlower [7], pre-competi-
tive technological innovation essentially addresses the acqui-
sition of mastery by a given company on certain technolo-
gies of interest that may later be adopted in the development
of new products. Such technologies present a low maturity
level and need maturation before they can be definitively
employed.
Simultaneously to the development of a technology
maturity scale, there was the need for a similar scale for the
manufacturing area, called the MRL, which, according to the
OSD Manufacturing Technology Program [8, 9], was devel-
oped by a DoD working group under the coordination of the
Joint Defense Manufacturing Technology Panel (JDMTP).
Figure2 shows the acquisition life cycle proposed in the
Manufacturing Readiness Level Deskbook [19] and its rela-
tion to the TRL scale. Three milestones are condensed in the
model, represented by A, B and C.
Milestone A aims to validate the ability to produce the
technology in a laboratory environment, B validates the abil-
ity to produce the product in a relevant production environ-
ment, and C validates the ability to produce the product on
a pilot line.
The developed MRL scale comprises 10 steps from basic
identified manufacturing implications to demonstrated large-
scale capacity. At such stage, the product is already being
manufactured in a normal production environment; that is,
it is about business maintenance, showing no correlation
with the TRL scale.
After the DoD’s 10-step MRL implementation, many der-
ivations have come up. Ward etal. [13] presented the Rolls-
Royce aircraft turbine development scale, which created a
9-step scale based on the DoD scale, called the manufac-
turing capacity readiness level (MCRL). Ward etal. [13]
also cited two other scales aimed at determining the level of
maturity of manufacturing processes.
In order to avoid budget delays or disparities, Mankins [9]
proposed a matrix evaluation model called technology readi-
ness and risk assessment (TRRA) that would help project
managers make technology maturity clear and documented
in the initial stages of the project. The model takes three
factors into account: The TRL, to know the level of tech-
nology maturity, the R&D3, which measures a technology’s
probability of success or failure in relation to the degree of
research and development difficulty, and the technology need
value (TNV), which refers to the importance of the technol-
ogy development for the project.
Then, for any technology development effort, the tech-
nology readiness and risk assessment (TRRA) summarizes
the risks in the form of two axes: probability of failure (Pf)
and consequence of failure (Cf).The probability of failure
is directly related to R&D3 and addresses the question of
how likely this new technology is to fail.The consequence
of failure tries to answer what the consequences or benefits
of a failure would be and is directly related to the TNV and
the TRL. In other words, the further the development stage
and the greater the development value, the worse the fail-
ure consequence. For both Pf and Cf, 5 levels were created
regarding the probability and consequence of failures that
should be related to the risk matrix (TRRA) in Fig.3.
The Cf levels are 1 for remote, 2 for unlikely, 3 for likely,
4 for highly likely and 5 for almost certain. The Pf levels are
A for minimum impact, B for some impact, C for moderate
impact, D for high impact and E for unacceptable impact.
After classification, each evaluated technology should be
Fig. 2 DoD acquisition lifecycle (adapted from [19])

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located in a quadrant of the graphic shown in Fig.3. If it
falls into the green region, it does not need any meaning-
ful worries or actions, if it is in the yellow area, it must be
looked into and, if it is in the red region, the process should
be stopped until a solution is found.
2.3 Design formanufacturing andassembly (DFMA)
The term design for manufacturing refers to the design for
easy manufacturing of parts that form the product after
assembly, while design for assembly is related to product
design for easy assembly. Design for manufacturing and
assembly (DFMA) is a combination of DFA and DFM [20].
There are several DFMA and DFA methods or techniques
for concurrent engineering development. The three best
known are the Boothroyd–Dewhurst DFMA method, the
Hitachi Assemblability Evaluation and the Lucas DFA [21].
The Lucas DFA method was developed by the Uni-
versity of Hull and has the same research base as Boo-
throyd–Dewhurst [20], so they present some common char-
acteristics, such as the reduction of the number of parts and
the analysis of the parts’ geometry regarding the assembly
process [22].
The methods proposed by the authors present some dif-
ferences. The Boothroyd–Dewhurst method tends to require
more product information, such as processing and assem-
bly times. On the other hand, the Lucas method is based
on standardized and tabulated parameters, which allows
for greater flexibility in input data and even in evaluation.
Thus, we chose the Lucas method for this work, which will
be further elaborated below.
Seven steps are recommended to apply the method.
Steps 1 and 2 are project specification and product analy-
sis. The process only begins with the specification or exist-
ence of a product design. With it, a preliminary analysis
can be made of the general constructive aspects in order
to get the project team acquainted and prepared for the
next stage, which is the functional analysis, when the main
questions arise.
Step 3 is a functional analysis, which is considered a
fundamental step in the process because it determines the
minimum theoretical quantity of parts and stimulates the
project team to think about product concept optimization,
in order to merge functions into a single part and under-
stand the work required to offer technical assistance.
Mital etal. [23] suggest an analysis that has, as its basic
principles, the evaluation of relative movement between
components, the need for components to be made of dif-
ferent materials and, finally, the real need for components
to be separated from each other. The analysis is performed
using a flowchart sequence, dividing components into 2
groups: type A, essential; and type B, nonessential.
Knowing the product’s essential parts allows the evalu-
ation of design efficiency regarding assembly, as presented
in Eq.1, where A is the minimum theoretical number of
parts and A + B is the total number of parts.
The suggested design efficiency threshold is 60%, but
anything above 45% can often be considered good in prac-
tical terms [24].
(1)
AEf
=
A
(A+B)
Fig. 3 Matrix of technological
risks (TRRA) (adapted from
[9])

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Step 4, manufacturing analysis, uses the concept of tech-
nology groups to sort the components based on design and
material characteristics, which is estimated through an index
called the Manufacturing Cost Index (Mi), used to analyze
the adaptability of manufacturing processes and operation.
The index can be calculated from Eq.2, where the coef-
ficient Rc is the relative cost and Mc is the material cost
calculated from Eqs.3 and 4, since Pc, which is the pri-
mary processing cost, is a tabulated value. The values for
Pc, as well as for the other coefficients, are standardized and
detailed in the Lucas method. Despite not presenting a real
cost, it helps the team to see an already relativized result.
The primary processing cost (Pc) is based on the con-
cepts of near net shape, where the first manufacturing step is
very close to the final form. Like so, the best manufacturing
process is chosen based on the component having most of
its final characteristics. Another piece of information is the
relative cost (Rc), which incorporates the design complexity
and is associated with the processing of the characteristics
that such complexity brings. This index is composed of the
coefficients (Cc), which is relative to the complexity of the
form, (Cmp), relative to the complexity of the material, (Cs),
relative to the complexity of manufacturing regarding the
smallest section of the component and (Cr or Cf), related
to the complexity of meeting design tolerances or surface
finish.
To calculate the material cost (Mc), as shown in Eq.4, it
is enough to multiply the component’s volume (V) by its loss
coefficient Wc, and the standard material cost by volume
Cmt, both of which are found in Lucas method’s standard
table. After this step, the project team may decide to go back
to the beginning for another improvement iteration.
Step 5, handling analysis, is associated with the handling
of components and subassemblies before they are admitted
into the assembly system. In answering a set of questions
about a part’s size, weight, handling difficulties and orien-
tation, its index can be calculated from Eq.5. This index
considers a handling factor Z and the quantity of essential
components A, with the goal to be less than or equal to 2.5.
In order to calculate the handling factor, Eq.6 is intro-
duced [25], with coefficients a (size and weight), b (handling
difficulties), c (component orientation) and d (component
rotation orientation) presented in one of Lucas method’s
standard tables.
(2)
Mi =Rc ×Pc ×Mc
(3)
Rc =Cc ×Cmp ×Cs (Ct or Cf)
(4)
Mc =V×Cmt ×Wc
(5)
Handling Index =Z∕A
For step 5, the joint and union analysis is similar to the
handle analysis: an index of less than or equal to 1.5 is a
reference. However, there is usually greater variation and it
can be readjusted to less than or equal to 2.5.
Its calculation considers a joint and union factor H and
the quantity of essential components A, as presented in
Eq.7.
Equation8 shows the calculation method for the joint and
union factor, which has its coefficients a, b, c, d, e, f taken
from a standard table presented on Lucas method.
3 Model development proposal
The model proposed to improve the integration between the
design and manufacturing areas in pre-competitive techno-
logical research and development is composed of the follow-
ing phases: technology development, analysis of solutions
and advanced technological development. Figure4 presents
the structure.
In the presented model, those phases are associated with
technology maturity levels: selecting alternative technol-
ogy (SAT), generating alternative product (GAP), reviewing
component design (CDR), and evaluating project scalability
(PSE). These steps are, in turn, correlated with the levels of
TRL and MRL presented by the US Department of Defense
in its Manufacturing Readiness Level Deskbook [19].
Thus, in the end of the proposed model, there is a product
and manufacturing project ready to enter the development
phase with the following defined characteristics: (1) product
features such as dimensions, critical dimensions and defined
materials, (2) product design maturity evaluation from the
DFMA point of view, (3) investments and costs updated with
a high level of assertiveness, which will enable a good feasi-
bility analysis and (4) risk analysis to aid in decision making
and definitions on the next steps.
As this model is based on a literature review and a pre-
liminary case analysis, to synthesize the knowledge, Table1
presents a description of the main connection points between
the proposed methodology and the bases.
This model must be applied before the traditional PDP,
but they can be developed simultaneously, depending on the
project. Figure5 presents a connection overview, where (A)
is the design phases of the reference model proposed by
Rozenfeld etal. [17], (B) is the steps of a generic model
(6)
Z=a+b+c+d
(7)
Joint & Union Index
=
H
A
(8)
Z=a+b+c+d+e+f

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presented by Araújo and Mockzdlower [7], (C) is the steps
of this proposed model, and (D) is the MRL maturity levels.
The model proposed (C) initiates with basic research and
ends with a product design and optimized manufacturing
processes, but not necessarily approved for sale. The final
phase of proposed model (C) corresponds to the detailed
project (model A) and preliminary project (model B).
The proposal for the design and manufacture knowledge
integration model was organized in four large blocks, pre-
sented in Table2, which correspond to the proposed manu-
facturing technology levels of maturity, detailed by steps,
inputs, outputs and resulting documents.
A technical review meeting, involving a multifunctional
team from the design and manufacturing areas, should be
held at the end of each phase. At this moment, the project
team must check the generated documents to evaluate if the
project is ready to go to the next phase. The main documents
that must be used in such evaluation are: a MRL check list
in SAT level, DFA, DFM and risk matrixes for all maturity
levels. Information about the DFMA matrix is considered in
the DFA and the DFM matrix to evaluate the assembly and
manufacturing process in detail.
It is important to say that the proposed approach has some
relationship with Design for Six Sigma (DFSS). Accord-
ing to Creveling etal. [33], DFSS is a problem-prevention
methodology from a management perspective, built on
an integrated and balanced portfolio of statistical tools
focused on six sigma performance and best practices that are
Fig. 4 Proposed model framework [26]
Table 1 Synthesis of knowledge and connection with methodology
Base Model proposal References connection
1. Literature review Risk assessment matrix for manufacturing technology Adapted to the methodology for risk assessment in products
[8, 9]
Manufacturing maturity levels evaluation Using the Manufacturing Readiness Level Deskbook [19]
scale references and also reused or adapted by other
authors [9, 13, 27–31]
Managerial framework of the management process and
pre-competitive technological innovation from the point
of view of DFMA
Both the TRL and MRL proposals of the Manufacturing
Readiness Level Deskbook [19] [19] present a managerial
framework to refer to the product development cycle with
its main decision points in each phase
2. Preliminary
study of proposed
model
Assembly’s maturity level evaluation from a design point of
view—DFA
Adaptation of the product evaluation matrix with some DFA
rules [32], where qualitative inputs are translated into num-
bers, with rules of calculation based on design rules[25]
Manufacturing maturity level evaluation from the design
point of view—DFM
Adaptation of the proposal matrix by Miles and Swift [25]
Generation of DFMA indicators that can be used to follow
the evolution of manufacturing maturity
Proposition of a matrix that combines the two already pre-
sented for DFA and DFM

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Fig. 5 Connections between the proposed and previous models [26]
Table 2 Model integration guide
Maturity level Inputs Steps Outputs Generated document
SAT—Selecting Alterna-
tive Technology
1. Market problem
2. Technology list
1. Identify and classify
technology gaps
1. Identified technology
opportunity gaps
2. Created critical tech-
nologies list regarding
manufacture and product
3. Potential benefits
4. Classified maturity lev-
els (MLR) and (TRL)
1. Technology road map
2. Classification table of
technologies
3. Expert opinion
4. Lessons learned
5. TRL Assessment
6. MRL Assessment
7. Risk matrix filled
SAT step 1 outputs 1, 2, 3
and 4
2. Prove new technology
concepts
1. Technology feasibility
tests
2. Development gaps
3. Cost variation, invest-
ment and risks
1. MRL check list
2. Risk matrix filled
GAP—Generating Alterna-
tive Product
SAT step 1 and step 2
outputs
3. Generate conceptual
product model and define
its sub functions
4. Evaluate product con-
cept under DFMA point
of view
1. Product model design
with dimensions and pre-
liminary specifications
2. Design maturity evalua-
tion—DFMA
3. Cost variation, invest-
ment and risks
1. DFA matrix [32]
2. DFM matrix
3. Risk matrix filled
4. Specialist analysis
CDR—Component design
revised
GAP step 3 and step 4
outputs
5. Optimize product design
under DFMA and auto-
mation view
6.Produce components in
prototype tooling
7.Assemble product in
laboratory
1. Basic product model
design review with opti-
mized components
2. DFMA indexes reviewed
3. Cost variation, invest-
ment and risks review
1. DFA matrix review [32]
2. DFM matrix review
3. Risk matrix review
4. Design for automation
rules
PSE—Project scale up
evaluated
CDR step 5, 6 and 7
outputs
8. Assemble product in an
advanced manufacturing
laboratory to approve
tooling and technology
9.Review product analysis
based on DFMA rules
1. Defined product model
design review with
critical dimension and
materials
2. Reviewed product
DFMA evaluation
3. Reviewed cost variation,
investment and risks
1. DFA matrix review [32]
2. DFM matrix review
3. Risk matrix review

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implemented at the phases of a PDP, providing qualitative
and quantitative results that are summarized in scorecards
in the context of critical parameter management against a
clear set of product requirements based on the customer’s
voice. The authors also argue that DFSS integrates three key
tactical elements to help achieve an organization’s business
objectives such as cost reduction, high quality and reduced
product development time.
The proposal presented in this paper can be applied along
with the DFSS methodology, as it can complement the DFSS
approach or any other methodology that supplies process
information. Both methodologies provide a way to create
and develop technology and product design and to develop
the manufacturing process, helping eliminate or reduce time,
costs and failures before large-scale production.
Another aspect is that, according to Creveling etal., one
of the key components of DFSS is the Critical Parameters
Management (CPM). During design for Six Sigma, teams
use quantitative metrics to define and measure customer
satisfaction and, then, incorporate the identified critical-to-
customer characteristics into the products and production
process design. Such metrics can be used to track the product
through its entire life cycle, providing quality feedback, and
the proposed matrix can help track the metrics through the
defined index.
3.1 Preliminary case study
A preliminary case study was performed during the tech-
nological development of a new subsystem of a valve spin-
dle assembly (called Project X), represented in Fig.6. The
objective was to validate the application of three matrices,
the DFA, the DFM and the DFMA, already presented in
Table2, as a generated document. Those matrices are the
main communication tool for the process.
The proposal of Biesek and Ferreira [26] aimed to
evaluate the use of DFMA project guidelines organized
in evaluation matrices to be used by the project team as a
means of making a product more time and cost competi-
tive and to follow the maturity in aspects related to man-
ufacturing. The proposed model considers DFMA tech-
niques as technical drivers and proposes the generation
of reference indicators correlated with the three stages of
manufacturing maturity.
The tools used were DFA and DFM evaluation matrices
with the results ordered in a DFMA matrix that yields per-
formance indicators to follow the product maturity evolu-
tion considering aspects of manufacturing and assembly.
To understand Project X’s level of maturity then, a cor-
relation was made between the stage definitions proposed
in the MRL scale with the maturity stage definitions of
the Enterprise Product Development Process R, and the
remaining maturity stages defined by MRL2, MRL3 and
MRL4.
To apply the model, the matrix proposed in Fig.7 was
used in step 1, adapted from Stienstra [32] example, where
the components are evaluated in relation to the DFA crite-
ria using the letters Y (Yes) and N (No). In this matrix, the
maturity evaluation is performed based on project guide-
lines and penalty factors proposed in Miles and Swift’s
[25] methodology, which are used to calculate the assem-
blability indices, called measures of performance (MOP).
This makes the process more agile, mainly by allowing
the extraction of results from a project without requiring
numerical indices such as operational cycle time.
The DFA evaluation matrix has 3 main fields, identified
in Fig.7 as A, B and C, with field A presenting the general
and partial project guidelines based on the DFA, aligned
with the Stienstra [32] and Miles and Swift [25] criteria.
There are 6 general guidelines presented as topics at Level
N1. The partial guidelines are 21 and topics or questions
are presented in N2.
In field B, the product’s components are described,
evaluated and compared with the N2 level rules. The com-
ponents are organized into subsets (SB01, SB02, …).
Field C shows the evaluation responses, which are the
numerical indices calculated based on the general and par-
tial guidelines. N5 is meant to transform the answers Y
and N into numbers using Eqs.9 and 10. Equation9 only
points out the number of Y responses and is valid for col-
umns from (a) to (f). Equation10 points out the number of
Y or N responses and multiplies them by the penalty fac-
tors related to the DFMA guideline level 2 (N2) proposed
by Miles and Swift [25] Luca’s method of calculation.
Equation2 is valid for columns (g) through (u). These
values are the numerical basis to calculate the indicators
at levels N6 and N7.
Levels N6 and N7 group level 5’s numerical responses,
generating partial and general indices of DFA that will
be used to track design maturity evolution over the PDP.
(9)
Tota l =count Y
(10)
Tota l =count N×PFMax +count Y×PFMin
Fig. 6 Component and technology that need to be developed

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N6 relates to the specific DFMA guidelines presented in
N2, and N7 groups the guidelines presented in N1. This is
done through Eqs.3, 4, 5, 6 and 7. Equation11 shows how
much, in percentage, the evaluated components comply
with the DFA guidelines. It is used in N6 for the indices
from A to D, and its best score is 100%.
Equation12 is applied for the indices from E to S and
shows a relationship between the penalties applied to the
project in N5 and the theoretical minimum number of
parts, which is the quantitative index b, with the intent to
compare not only the evolution within the same project,
but also to others, since the theoretical minimum number
is a standard used to measure project efficiency in terms of
DFMA. Its best score is zero, which means that no penalty
was applied.
In N7, AA is obtained from Eq.13, presented in the
Lucas method to calculate the efficiency of the assembly
design, with the best score of 100%.
(11)
(
Ato D)Indexes =∑YES
∑
YES +
∑
NO ∗100
%
(12)
(
Eto S)Indexes =
Tota l
b
BB and CC follow Eq.14, which is an average of two
partial directives. BB is called the Bill of Material (BOM)
cost and needs the product’s BOM to be composed, since it
works on a comparative basis between the components. It is
linked to the partial guidelines 3 and 4, analysis of standard
components and analysis of project cost impact. The lower
this index, the more disorganized and/or with higher cost
impact components exist.
CC is a relative assembly analysis from the quality point
of view through the Poka-Yoke concept, which aims to
ensure that the product assembly is error proof and is linked
to guidelines 5 and 6, which regard the possibility of mount-
ing the wrong component or assembling the component in
the wrong way, already presented in Fig.2. The lower this
index, the less this criterion is met by the project.
DD and EE are related to Eq.15, which is the sum of
the penalties within the general design guidelines 4 and 5,
handling, joining and union. FF is equal to T, because it is
a design guideline chosen to be individually measured by
(13)
(
AA)Index =
b
a
(14)
(
BB to CC)Indexes =
1
2
(A+B)or
1
2
(C+D
)
Fig. 7 DFA evaluation matrix [26]

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its control complexity in the manufacturing processes. The
lower this index, the more the project meets the criteria.
The second stage of the study involved the DFM analy-
sis, through the proposed DFM matrix, based on the meth-
odology of Lucas (1993) [34], as illustrated in Fig.8. The
component manufacturing analysis aims to identify indices
of manufacturability to help measure the design evolution
in terms of form changes or manufacturing processes. Only
components which need further manufacture development
should be considered for this analysis, leaving out standard
components already available for purchase in the market.
The DFM indices, such as the DFA, are also obtained by
means of three partial and one general guideline, the partial
ones being presented as: relative manufacturing costs (Rc),
which are associated with the analyzed component’s design
complexity and generates the partial index T, calculated
using Eq.3; processing costs (Pc), which are associated with
how close the component is to its final form in a single pass
and generates the partial index U, obtained from the table
in Annex G; and material costs (Mc), which relativize each
component’s manufacturing by standard cost-per-volume
and losses that are associated with the material and the cho-
sen manufacturing process, generating the partial index V,
which is calculated using Eq.4.
The three combined partial guidelines result in the gen-
eral guideline called general manufacturing costs (Mi),
which is calculated using Eq.2 to obtain the general GG
index. The indices T, U, V and GG are obtained from the
sum of the indices referring to the manufacturing process of
each assembly or subassembly (SB), as shown in Eqs.16,
17, 18 and 19.
(15)
(
DD to EE)Indexes =
k
∑
i=E
ior
R
∑
i=L
i
Equation20 shows the logic to find the value of A, which
is obtained by adding the results for each manufacturing
stage from the respective subset (SB), and must be followed
by the other items B, C, D, An, Bn, Cn and Dn.
All those indices for DFA and DFM must be input into
the matrix from Fig.9, which numerically summarizes the
project’s analyses according to the DFMA criteria and ena-
bles following up weak and strong project points analysis, as
well as the project’s evolution. Figure9 presents the results
of this preliminary model study.
Field A is the table header, where the maturity stages
and their general criteria (AA, BB, CC, DD, DD, FF, GG)
obtained from the DFA evaluation matrix (Fig.7) applied
in the study, are presented. This field also presents the ref-
erence values for each general criterion. When there is no
reference value for some criterion, Bt2 will be used, which
(16)
T
Index =
An
∑
i=A
i
(17)
U
Index =
Bn
∑
i=B
i
(18)
V
Index =
Cn
∑
i=C
i
(19)
GG Index
=
Dn
∑
i=D
i
(20)
A
=
An
∑
i=A
i
Fig. 8 DFM evaluation matrix (adapted from [25])

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means that the last evaluation stage should have a better
value than the previous one.
Field B presents a list of the partial guidelines and their
respective indices, each considering the last evaluation step,
in this case, step MRL4. The scores are the indices resulting
from the DFA analysis, brought from the DFA evaluation
matrix (Fig.7) applied in the study.
Field C connects the partial to the general guidelines or
criteria, already presented in the study.
Based on the model’s results, summarized in Fig.9, it
is possible to verify that the proposal allowed to follow
the project’s evolution based on the general and partial
guidelines obtained through the use and adaptation of the
DFMA techniques in the DFA, DFM and DFMA matrices
throughout the project’s maturity stages defined as MRL2
and MRL4 on the table header. It is notably easy to iden-
tify the points of product improvement by looking at the
guideline indices presented in fields B and C. Those prod-
uct improvement points were key elements that guided the
changes in the product’s concept.
The product concept changes are reflected in the
increasing of the general and partial guideline values.
The main impact was the 25% product cost and 20% pro-
ject investment reductions evaluated by the project team.
The earlier manufacturing and assembly project notice-
ably allowed a more reliable product debugging, yielding
a reduction in the execution time.
Fig. 9 Maturity evolution matrix [26]

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The increase from 47 to 70% in the DFA general guide-
line in the MRL2 to MRL4 maturity stages is an example of
a result obtained from design reduction and simplification,
which, in addition to reducing the transformation and invest-
ment costs, reduces assembly risks, replacing unknown or
complex technologies for simpler ones, serving the same
functional requirements.
The second important generated document, which guides
decisions to finish SAT maturity level, is the SAT checklist
adherence. This checklist, presented in Table3, is composed
of some important criteria and topics to be evaluated. 100%
compliance is ideal.
The last important document is the risk matrix, which
must be filled following previously presented instructions
(in the “literature” section).
4 Evaluation
The model evaluation aims to identify its potential use in
project environments during preliminary stages of develop-
ment, as well as improvement opportunities.
The proposal follows the experiments already conducted
by Margarita and Inthamoussu [35] and will take place in
two stages: a workshop for the presentation and development
of an experiment with a project team composed of 16 peo-
ple working in research and development at a multinational
metal mechanic company, and an evaluation questionnaire
for the professionals who participated in the case study, in
order to reflect on the potential results with the system’s
application.
The proposal evaluation is meant to verify the fulfillment
of the needs of product and manufacturing professionals
who work in project development environments in the pre-
competitive stage. In addition, the proposal was evaluated
considering aspects of form, clarity, completeness and oth-
ers. The first set of criteria for this evaluation intends to
verify the model as a work tool, while the second verifies
the model as a work tool for the involved company and the
third one is a reference model.
For the evaluation of the method proposal, a three-hour
workshop was held with a multifunctional team that works
with advanced technology development projects, with 16
attendees. Initially, the problem under study was presented
through the application of a real example. Then, the method
and its connections with the theoretical reference were intro-
duced in order to clarify the scientific basis of the study.
The third step was the presentation of a case involving
Table 3 SAT Checklist (adapted from [19])
Topics to be evaluated (Y/N) (Y/ N)
Is the technology ready to TRL3 or higher? Have material scale problems been identified?
Were the technology manufacturing sources identified? Has an initial assessment of potential supply chain capacity
been completed?
Have manufacturing technology concepts been identified
through experiments/models?
Has an initial assessment of potential regulatory requirements
and special material handling concerns been completed?
Have the relevant materials/processes been evaluated for fabri-
cation using experiments/models?
Have potential special handling procedures been applied in the
laboratory?
Are the main performance requirements related to the new
process defined?
Have special handling concerns been assessed?
Were the pros and cons of the design options evaluated based
on experiments?
Have the proposed manufacturing concepts or productivity
requirements been identified based on high-level process flow
models?
Have the technical and product life cycle requirements been
considered?
Have high-level manufacturing processes been documented?
Have cost and risk objectives been identified? Have critical manufacturing processes been identified through
experimentation?
Has a cost base model been developed, even at a high level? Have initial estimates of efficiencies been completed based on
experience or prior art?
Have cost technology models been developed for new process
steps and materials based on experiments?
Have the new manufacturing skills been identified?
Has a sensitivity analysis been performed to define cost drivers
and production development strategy (i.e., laboratory for
pilot to factory)?
Were the manufacturing skills required to produce, test and
support the proposed concepts evaluated?
Does the program/project have reasonable budget estimates for
achieving MRL 4 by Milestone A?
Were the manufacturing skills required to produce, test and
support the proposed concepts evaluated?
Have the properties of the materials been validated and evalu-
ated for basic fabrication using experiments?
Have the requirements/needs of specialized facilities been
identified?

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technologies of the company in question applied using the
proposed model, which lasted for 1.5h in an oral presenta-
tion format with practical examples of open application for
group discussion. At the end, the evaluation questionnaire
was applied.
The interviewed group consisted of 16 professionals
working in the research and development environment of a
metalworking multinational with more than 10,000 employ-
ees and an annual turnover of more than 1.5 Billion dollars.
Their multifunctional experiences contributed to improving
evaluation efficiency. The group was composed of senior
engineers for manufacturing and products, research and
development managers, an applied product researcher, a fel-
low researcher, the research and development director and
a PMO analyst.
4.1 Model evaluation results
The results were analyzed according to the three following
criteria: (1) evaluation of guideline contribution as a work
tool for simultaneous engineering, through the application
presented at the workshop; (2) evaluation of the contribution
to the company where the workshop and the case study were
held; and (3) evaluation as a reference model.
In order to evaluate it as a work tool, the workshop par-
ticipants answered 4 questions: (1) Does the model propose
a flow and tools that help to structure, integrate and systema-
tize the simultaneous design and manufacturing engineer-
ing during the initial phases of design? (2) Does the model
enable better information recording as well as facilitate pro-
ject decision making? (3) Do the presented matrices improve
the effectiveness of DFMA application in the initial phases
of design? (4) Does the model, through its maturity and risk
levels (MRL, TRL and TRRA) allow a better temporal ori-
entation of the project in relation to the stage of development
as well as the risks involved?
All participants responded yes to questions 1, 2 and 3, and
question 4 had 80% of positive responses.
Regarding question 1, the answers made it clear that the
model does exactly what was asked. That is clear in the reg-
istered comments, such as "It systematizes and improves
what is already done", "It helps remove what is in our head
and systematize the work” and "Interesting methodology. We
have to learn more about usage."
Regarding question 2, two participants made comments in
order to ratify the positive response: "It can help in directing
decisions" and "In specific cases, it may be useful to help
guide the decision".
Some comments also corroborate the applicability of
question 3 and were addressed by participants as follows:
"Clear examples of problems we are experiencing", "Actu-
ally evaluating the design following DFA criteria became
simpler", "Verify integration with DFSS (Design for Six
Sigma)", "We can apply in subsystems with unprecedented
characteristics" and "I have already applied the DFMA
Matrices in a project whose manufacturing technical team
I lead, and the answers we got about the design assessment
helped us show, based on systematized requirements on a
scientific basis, how we could improve the design in terms
of manufacturability".
Finally, regarding question 4, 20% of the participants said
they partially agreed, but no comments were made that could
help to better understand why.
The evaluation also proposed a fifth question with the
possible answers "Yes" (meets the guideline), "Partially"
(partially meets the guideline) or "No" (does not meet the
guideline). Participants were asked about the use of the
model in the company where they work. The vast major-
ity believe that the model could already be applied within
the company as it was presented. This is represented in the
graph because 90% of the answers are yes. The 10% who
responded as partially meeting the guideline believe that
there should be some adaptations.
In order to evaluate this model as a reference, the partici-
pants answered 7 questions [36], which are: (1) Does the
method application to the business reality require knowl-
edge about integrating manufacturing and project areas?
(2) Does the graphical representation of this model (pro-
cess flow and matrix) present the phases and activities in a
clear and friendly way? (3) Does the representation of this
model (process flow and matrix) objectively present phases
and activities so that there is no redundancy? (4) Does the
model contain all the necessary information to carry out the
integration of the manufacturing and project areas? (5) Can
the model be used for the development of various types of
technologies? (6) Can the model framework be adapted for
use in other types of business? (7) Is the execution of the
system lean in terms of resources and time while maintain-
ing adequate execution quality, in order to maintain a cost-
effective versus time-effective relationship?
Each participant is requested to answer to what degree
the model meets each criterion of a reference model with the
four options: fully meets, highly meets, partially meets and
does not meet. Most answers were fully and highly.
Regarding question 1, 95% of answers were “fully meets”
and only 5% said “partially meets.”
For the representation criteria, which are addressed in
questions 2 and 3, 90% of the participants understand that
they meet the criterion of clarity and friendliness, and 85%
understand they are objective and avoid redundancies. The
other 15% would like to see a little more of the generated
input data, but find this important and believe it may be an
opportunity for improvement. Two comments are related to
these opportunities: "It could include pre-existing analysis
of components on other platforms" and "Before commenting,
it is important to know whether the technology in question

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will be developed within the company or will be outsourced
to avoid unnecessary efforts of internal resources."
Finally, the evaluation addresses four questions to evalu-
ate the criterion of method content, which talks about com-
pleteness, robustness, reusability and economic efficiency
of the proposal.
Regarding completeness, which evaluates whether the
method contains all the necessary information to carry out
the integration of the design and manufacturing areas, 95%
of the responses were affirmative.
Answering if it is robust enough to serve the development
of different types of technology, 100% of the participants
answered “fully meets” or “highly meets.”
To evaluate the possibility of reuse in other types of busi-
nesses, even though 80% of participants answered “fully
meets” and “highly meets,” 20% still cannot clearly see this
applicability.
Regarding the method being lean and keeping cost x
benefit feasible, 95% of the responses were positive (fully
meets).
The evaluation was proposed to meet two main criteria.
The first focused on the needs of design and manufacturing
professionals working in development environments. The
second was to evaluate the characteristics of the proposal
as a reference model. For those two, 3 global indices were
proposed, the first regarding the fulfillment of the questions
as a work tool, the second on the contribution as a work tool
for the company where the workshop was conducted, and
the third to evaluate the model as a reference. The possible
answers are “meets,” “partially meets” and “does not meet.”
These responses are directly correlated with the applied
questionnaires and results are presented in Fig.10.
The values show that the model satisfactorily meets the
evaluation represented by the respective indices from Fig.7,
leading to the conclusion that it is a working tool that helps
the integration of the design and manufacturing areas, works
as a reference model and can be applied “as is” in the com-
pany where the workshop was held.
5 Final conclusions andrecommendations
The contribution presented in this paper can be a new prod-
uct innovation management model or a new design method
to integrate TRL e MRL at the early stages of innovation.
The proposal can be understood as a new product innovation
management process since, for its application, the technol-
ogy and the product design process must be adapted. The
product TRL evaluation is associated with the product devel-
opment phase and the respective gates. On the other hand,
it can be a methodological proposal of integrating the two
indexes (TRL and MRL) with DFMA analysis in order to
indicate design improvement aspects at the early stages of
the innovation process.
The proposed model contributes to simultaneous engi-
neering in the reduction of time to market, the increasing of
cost savings, ensuring competitive market position, optimiz-
ing resource allocation, improving the production planning
process, improving the communication and collaboration
between departments, improving an effective establishment
of cross-functional integration, identifying appropriate
cutting-edge technologies in prototyping and aligning with
strategic plans.
The objective of this work was to propose a model for
the integration of the knowledge areas of design and manu-
facturing in the development stage of product technologies
using DFMA, MRL and TRL.
The proposed model shows that integrating the DFMA
with MRL and TRL deepens and potentializes the results
beyond what is already known with the individualized
application.
The use of 3 matrices, which are key documents of
this proposal, results in a change of product design and
manufacturing process with a product cost reduction of
20% and project investment reduction of 25%. The main
elements modified in the project, which are reflected in
the matrices through its general and specific guidelines
and allowed to obtain these results, were: a 33% reduction
Fig. 10 Overall indices of
evaluation of the method [37]

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in the number of parts, which is reflected in the increase
of the DFA index from 47 to 70%, and was stimulated by
the functional analysis of the product with the design and
manufacturing teams; a change in the concepts of compo-
nent joining, mainly eliminating the need to use adhesives,
which is reflected in the decrease of the index referring to
the DFA guideline, from 2.9 at the level MRL2 to 1.1 in
MRL4; a change in component manufacturing concepts,
represented by the improvement in the overall manufac-
turing costs guideline, which was 166 at the MRL 2 level
and was reduced to 88 at MRL4. The main impact was
caused by changes in concepts that require manufacturing
processes with high investment levels, such as Grinders for
finishes and Machining Centers for complex shapes, mov-
ing to simpler processes with lower levels of investment,
such as tools stamping and machining with conventional
lathes.
The product cost reduction of 20% and the project
investment reduction of 25% were obtained for one spe-
cific case, however. These levels of reduction cannot be
always guaranteed.
The model application was validated through the pres-
entation of the method in the form of a table with tasks
and tools to be applied in research and development pro-
jects, along with the maturity evolution divided into three
macro-phases and four levels of maturity. The evaluation
was performed with a 16-member multifunctional team of
professionals with experience in research and development
(R&D) from a multinational metalworking industry with
more than 10,000 employees and an annual turnover of
more than 1.5 billion dollars, during a workshop with an
application presentation through a practical example. The
answers for the questions related to the selected criteria
proved the effectiveness of the results through three indi-
ces: the first one referring to the model as a work tool—
with 95% agreement; the second one regarding whether
the model contributed to the company where the workshop
was applied, with 90% agreement; and the third one evalu-
ating the proposal as a reference model, which obtained
92% of positive answers.
It is important to emphasize that the proposed model con-
tributes to improving the results of projects that start in the
technological development phases, as it allows for a better
integration between the design and manufacturing teams.
The proposed model is effective if used in companies
that have research and development (R&D) projects in their
structure and work with physical products. Software, chemi-
cal, medication, clothing, among others, are then excluded.
Another aspect is that the proposed model is restricted
to applications in preliminary phases of projects, in the
research and development (R&D) stage.
Future work can be developed to study how to extend
the use of this methodology to a product with faster design
and life cycles (electronics, software, others), faster devel-
opment process, to the final consumer or even to technical
assistance.
The literature review shows that there is a gap between
the use of these scales and assessments for companies of
consumer goods and manufacturing. Within the standard
rules and tables of DFMA, there is still the opportunity for
an update that increases the scope of the analysis to a greater
number of manufacturing processes.
Funding Not applicable.
Declarations
Conflict of interest Not applicable.
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