Articulo 16

sustainability
Article
Towards Lean Automation in Construction—Exploring Barriers
to Implementing Automation in Prefabrication
Finn G. Feldmann
Chair of Supply Chain Management, Friedrich-Alexander-University Erlangen Nuremberg, Lange Gasse 20,
90403 Nuremberg, Germany; finn.feldmann@fau.de
Abstract: As a sustainable alternative to conventional cast-in-situ construction, modular construction

(MC) offers several promising benefits concerning energy and waste reduction, shorter construction
times, as well as increased quality. In addition, given its high degree of prefabrication, MC offers ideal
conditions to solve the industry’s long-lasting productivity problem by implementing manufacturing
concepts such as lean production and automation. However, in practice, the share of automation
and robotics in the production process is still relatively low, which is why the potential of this
construction method is currently far from being fully exploited. An overview of the particular barriers
to implementing automation in the context of MC is still lacking. Therefore, a qualitative study was
conducted including eight MC manufacturers from Germany, Austria, and Switzerland. Following
a comprehensive literature review, expert interviews were conducted based on an academically
proven framework. Thereby, seven barrier dimensions with 21 sub-categories could be identified. The
findings of this study contribute to the understanding of current barriers to implementing automation
in prefabrication and how they can be overcome most effectively. Additionally, recommendations for
future research are proposed within a research agenda.
Citation: Feldmann, F.G. Towards

Keywords: automation; lean construction; construction 4.0; modular construction; prefabrication;
Lean Automation in Construction— off-site construction; barriers; sustainability; qualitative study
Exploring Barriers to Implementing
Automation in Prefabrication.
Sustainability 2022, 14, 12944.
https://doi.org/10.3390/ 1. Introduction
su141912944 With the highest amounts of energy consumption and CO2 emissions among all
Academic Editor: industries, the building and construction industry is urged to take immediate action to meet
Valentino Sangiorgio the sustainable development goals [1]. However, on the path towards more sustainable
operations, there are several problems inherent in the industry’s culture that need to be
Received: 10 September 2022
addressed. Since the creation of value in the construction industry is generally project-
Accepted: 4 October 2022
based, low levels of value chain integration with a large number of ever-changing project
Published: 10 October 2022
participants limit learning effects and productivity gains drastically [2]. Accordingly, it
Publisher’s Note: MDPI stays neutral is not surprising that the industry’s productivity has been stagnating over the last three
with regard to jurisdictional claims in decades, while the efficiency of producing goods in the general manufacturing industry
published maps and institutional affil- almost doubled in the same time [3]. As a result, more often than not, building projects
iations. suffer from cost and time overruns [4].
One promising solution to solve these problems could be found in modular construc-
tion (MC). As a distinctive form of off-site construction (OSC), it is defined as a modern
method of construction that uses pre-finished volumetric units (so-called modules) to
Copyright: © 2022 by the author.
assemble the final building on-site [5]. Scholars have shown that applying MC has the
Licensee MDPI, Basel, Switzerland.
potential to reduce construction times [6], as well as improve building quality and working
This article is an open access article
distributed under the terms and
conditions [7,8]. Moreover, environmental sustainability can be achieved by reducing waste
conditions of the Creative Commons
and energy consumption [9]. In addition, by relocating the vast majority of construction
Attribution (CC BY) license (https:// operations to a controlled factory environment, an integrated value chain can be created,
creativecommons.org/licenses/by/ building on concepts such as Design for Manufacture and Assembly (DfMA), lean produc-
4.0/). tion, and modularization [10]. Furthermore, MC offers ideal conditions for implementing
Sustainability 2022, 14, 12944. https://doi.org/10.3390/su141912944 https://www.mdpi.com/journal/sustainability

Sustainability 2022, 14, 12944 2 of 22
advanced manufacturing procedures using automation and robotics, which has been re-
garded as a cornerstone of the recently advocated Construction 4.0 (C4.0) approach [11–13].
While these advantages over conventional cast-in-situ construction have led to a
considerable uptake of this construction method in several countries worldwide [14],
recent studies consistently showed that the adoption of automation in MC and OSC is
still relatively low [15–17]. Current applications of MC are oftentimes only a mere shift of
construction operations to a structured factory environment, where tasks are still carried
out manually based on the craftsmanship approach [18]. As a consequence, productivity
gains, as could be observed in the general manufacturing industry, remain far from being
reached. In addition, although factory-based production enables MC manufacturers to
make use of economies of scale, there are currently no significant cost reductions compared
to conventional construction [19]. In the heavily cost- and profit-driven construction
business, this circumstance hinders big players (i.e., developers and housing corporations)
to apply this construction method in their projects [20].
It is therefore decisive to understand why automation has not yet been transferred
to the production process of MC, despite the well-known benefits that are observed in
other industries. A comprehensive overview of the barriers that MC manufacturers face
when implementing automation in their production is still lacking. Therefore, the following
research question is formulated:
What Are the Barriers to Implementing Automation into the Production Processes of MC?
Accordingly, this study aims to identify, categorize, and evaluate the respective barriers
in a suitable framework to close this research gap. Based on a comprehensive literature
review, eight in-depth expert interviews with high-ranked representatives of companies
that are actively producing modules in their facilities were conducted. Experts from the
respective companies were interviewed using semi-structured interviews. In addition, a
considerable number of secondary materials were integrated into the data set.
The remainder of this paper is structured as follows. Section 2 gives an overview of
the theoretical background concerning the concepts of LC and C4.0, introduces MC as a
potential means to efficiently implement lean automation in construction, and highlights
the research gap and contributions of this paper. Section 3 states the applied research
methodology. Section 4 presents the results structured along the identified barrier dimen-
sions. Subsequently, the results are discussed in Section 5. Lastly, a conclusion is provided
in Section 6.
2. Theoretical Background
In the following, Section 2.1. gives a brief overview of the concepts of lean construction
and Construction 4.0. Section 2.2 introduces MC as a potential means to fully exploit the
benefits of the aforementioned concepts by applying lean automation.
2.1. Lean Construction and Construction 4.0

The term lean construction (LC) originates from the concept of lean production [21] and
refers to the adaptation and application of the underlying principles from manufacturing to
the context of construction [22]. Lean production itself has its roots in the Toyota Production
System [23], which is based on one core principle: focus on value-adding activities by
eliminating all kinds of waste [24]. Lean process design is built on continuous improvement
and pull production to reduce lead times and production costs, while increasing the quality
of products and the efficiency of the underlying production system [25]. The simplicity of
lean production combined with its potential to increase productivity has made it one of the
prevailing management approaches over the last three decades [26].
Similarly, the concept of C4.0 originates from the concept of Industry 4.0 (I4.0), which
is referred to as the fourth industrial revolution [27]. Driven by widespread digitalization
and the emergence of advanced digital technologies, such as Artificial Intelligence (AI),
Big Data, and the Internet of Things (IoT), the manufacturing industry is on the edge of
a paradigm shift [28]. This shift towards the fourth industrial revolution is characterized
by automated, decentralized, and smart value creation networks enabled by IoT tech-
nologies [29]. It enables the creation of a cyber-physical environment, in which machines
are enabled to interact with each other (machine-to-machine communication) without
any human intervention [30]. I4.0, therefore, has the capacity to fundamentally improve
processes in every stage of value creation and thereby boost operational effectiveness and
productivity [31].
In construction, there have been numerous approaches to adopt and transfer both
concepts from manufacturing to construction operations. Accordingly, within LC, several
concepts and techniques have evolved to enhance the productivity of construction projects.
For instance, frequently applied methods include the Last Planner System [32], application
of 5S (sort, straighten, shine, standardize, and sustain) to the construction site [33], and
KANBAN for material storage on-site [34]. Among others, applying these techniques has
been proven to significantly reduce the risk of project time overruns [35].
Similar to the adaptation of the principles of lean production, there have been efforts
to apply the underlying principles of I4.0 to construction projects [36]. While the number
of research papers has been continuously increasing over the last years, three scholars have
attracted considerable attention [11–13]. In 2016, Roland Berger [11] coined the term ‘Con-
struction 4.00 to describe the future developments driven by the digital transformation of
the industry. In their conceptualization, they listed the following four key factors: automa-
tion, connectivity, digital access, and digital data. Sawhney et al. [12] conceptualized those
efforts in three transformational trends: industrial production, cyber-physical systems, and
digital technologies. Craveiro et al. [13] emphasized that the construction industry would
have to transform towards the fourth industrial revolution through the industrialization of
the construction process and the general digitization of the construction industry.
Notably, all three conceptualizations include the transformation towards increased
use of prefabrication (i.e., automation, industrial production, and industrialization of
the construction process). Considering the characteristics of the current value creation
process in conventional construction, this development can simultaneously be regarded
as a great challenge, as well as a great opportunity [30,37]. More precisely, implementing
innovations in the construction industry is hampered by several obstacles: Originating from
the project-based structure, the complexity of processes is generally higher compared to
other industries [38]. In theory, this complexity has mainly been ascribed to high uncertainty
and interdependence in construction projects [39]. Due to many different participants in
the overall value creation process, there are numerous interfaces between the distinct
construction trades and the respective companies, leading to inefficiencies [34]. Some
described this supply chain design as a “loosely coupled system”, hindering participants
to innovate and making use of learning effects hardly possible [40]. Effectively, pursuing
technical innovations in a less integrated supply chain rather hampers collaborations than
lets them flourish, since many partners are not capable or willing to take the same path [30].
Koskela [22] stated that characteristics such as temporary project-based collaborations,
unique building designs, and on-site work lead to inefficient workflows and the generation
of waste, contradicting the main principle of lean production.
Therefore, to fully exploit the benefits of best practices from the manufacturing indus-
try in the context of construction, the value creation process including the general supply
chain structure would have to be redesigned and re-engineered [34,41]. The construction
process should be aligned with manufacturing processes (product-based) [22], rather than
improving traditional construction procedures with technological advancements [42]. By
industrializing the construction process using high levels of prefabrication, the concepts
of lean production and I4.0 could even be implemented simultaneously, which is referred
to in the manufacturing industry as lean automation [43]. Recent research found that
the combined use of both approaches not only facilitates the implementation of each con-
cept [44], but also leads to additional benefits. Accordingly, I4.0 tools complement lean
production by increasing flexibility, as well as higher customization of products, allowing
more effective responses to market fluctuations [45]. In addition, further improvements

within all three dimensions of the TBL of sustainability could be observed [46], which
highlights the immense potential that adoption would have for the construction industry.
However, while research on LC and C4.0 has been growing during the last few years [36],
research on the actual implementation of automation in OSC production is still scarce.
2.2. Introducing Lean Automation in Modular Construction

As a feasible solution to automate construction processes, MC has been intensively
studied from various perspectives over the last two decades [47]. The term MC is used
interchangeably with denotations such as modular building [5], modular integrated con-
struction (MiC) [10], or prefabricated prefinished volumetric construction (PPVC) [48].
Generally, it can be defined as a distinctive form of OSC with a very high degree of pre-
fabrication. More specifically, it is characterized by fully furnished volumetric units that
are manufactured in a factory environment and transported to the building site for final
assembly [5]. Researchers reported its superiority over conventional construction from an
economic point of view in terms of construction times and technical quality [8]. Further-
more, from an environmental perspective, waste generation and energy consumption can be
decreased [9], while resilience and timeliness in the production process can be achieved [49].
With up to ninety percent of the value creation taking place off-site [18], the centerpiece
of this construction method is the manufacturing process of the modules. Given the produc-
tion in a structured factory environment, MC offers the optimal conditions to fully exploit
the benefits of lean production [10] and even allows the implementation of more progressive
concepts from the manufacturing context, such as I4.0 [50]. In addition, it enables an OEM-like
industry structure known from the manufacturing industry [42], as opposed to the fragmented
supply chain design in conventional construction [40]. Accordingly, by introducing state-of-
the-art production designs based on lean automation, not only tremendous productivity gains,
but also a transformation of the entire construction process, can be achieved [18]. Besides
shifting the value creation from a cost-driven to a value-driven approach, the use of fully au-
tomated and lean processes significantly improves overall transparency and access to relevant
information during all stages of the construction process [51].
However, in practice, the potentials of this construction method are far from being
fully exploited. Accordingly, Albus and Drexler [15] found in their practical-oriented study
with German MC manufacturers that, although the manufacturing process of the modules
has high levels of prefabrication, the level of automation is still relatively low. Similar
observations were made in the context of New Zealand’s OSC market [16]. According
to the researchers, most manufacturers still rely on production setups, in which the vast
majority of tasks are done manually with minimal use of automation. According to Bock
and Linner [18], the flow of materials in the production of most OSC approaches is still
organized like a workshop, rather than in a production line, as opposed to state-of-the-art
production facilities. Consequently, current approaches to manufacturing modules can
mainly be described as a shift from on-site to off-site craftsmanship.
2.3. Research Gap and Contributions

Concerning the extant literature focusing on the implementation of automation in
construction, two research streams can generally be distinguished. First, there is research
on automation in construction on a general level. While there have been numerous rele-
vant studies referring to automating on-site construction operations [17,52,53], only a few
scholars are specifically directed towards automation in OSC and MC [54]. Most existing
studies investigated barriers of prefabrication as an integrated step of the traditional build-
ing approach (e.g., prefabrication of building components), rather than as a stand-alone
construction approach. Accordingly, Davila Delgado et al. [17] examined the challenges of
automation in OSC as only one of four parts forming activities to automate processes in the
construction industry. In addition, most research on barriers to implementing automation
and robotics in construction has been primarily conducted from the perspective of technol-
ogy [55], despite recent findings stating that the adoption of automation is rather dependent
on environmental and organizational circumstances than the technology itself [56].
Second, recently, many relevant studies examined hindrances to applying MC and
OSC as an alternative to conventional construction [14,19,48]. While the barriers to the
widespread adoption of this construction method can be regarded as well-known [20],
research on barriers to the implementation of automation and robotics in the underlying
production system is still scarce. Darlow et al. [16] devoted a section of their study to
the status quo of automation in OSC in New Zealand, while Pan and Pan [57] investi-
gated determinants to implement automation in precast concrete production. However,
no study has specifically addressed barriers to applying automation in the context of MC,
despite it offering ideal conditions for effective implementation. Consequently, a compre-
hensive overview of the underlying factors inhibiting the adoption of this technological
advancement is still missing.
To close this research gap, this study aims to identify, categorize, and evaluate the
underlying barriers to implementing automation in MC. It contributes to the academic
literature by introducing a comprehensive framework of current barriers expanding the
perspective to various dimensions of inhibiting factors. By revealing the underlying
reasons for the currently low level of adoption from the perspective of MC manufacturers,
researchers are equipped with numerous starting points for future research to effectively
overcome pending barriers. The study, thereby, paves the way to an efficient application of
LC and C4.0, resolving the long-lasting problem of stagnating productivity.
3. Research Methodology
In order to identify the barriers that MC manufacturers face when automating their
production processes, a qualitative research approach was applied. As a comprehensive
overview of the respective hindrances is still lacking, an explorative study design is partic-
ularly suitable in this context [58].
The study is based on a comprehensive literature review and in-depth expert in-
terviews. Experts were interviewed using a semi-structured interview design to allow
openness of responses while collecting data in a structured way [58]. The interviews were
conducted between December 2021 and February 2022 with eight managers from MC
manufacturers in Germany, Austria, and Switzerland. Considering the selection of experts,
special emphasis was placed on high expertise in the field of prefabrication (more than 10
years of professional working experience), as well as active involvement in the decision
process of developing the module manufacturing process. In addition, the selection of
companies was limited to companies operating their own production facility to allow
well-founded evaluations of potential barriers and challenges of implementing automa-
tion. This restriction can be regarded as the primary reason for the relatively low number
of interviewed experts, as MC manufacturers in the aforementioned countries owning a
production facility are still scarce. Table 1 gives an overview of the position of interviewed
experts in their respective companies, as well as the company size according to the number
of employees. For reasons of confidentiality, the names of the interviewees and companies
have been anonymized.
Table 1. Data sample. Experts from MC manufacturers.
Expert Position Employees

E1 Head of Research & Development 100–1000
E2 Head of Research & Development <100
E3 Head of Business Development <100
E4 Head of Quality Management 100–1000
E5 Head of Business Development 1000–10,000
E6 Managing Director 100–1000
E7 Head of Product Management 1000–10,000
E8 Head of Modular Construction 100–1000
about their position, as well as their professional background and working experiences.
In the second part, the underlying research context of this study was explained to the
interviewees. Ultimately, in the third part, experts were asked to provide their detailed
opinion on barriers that they expect to encounter or have already encountered in their
practical experience when implementing automation into production processes. Inspired
by the overview of risks of adopting Industry 4.0 by Birkel et al. [29], the experts were
asked the following questions:
The interview guideline consisted of three parts. In the first part, experts were asked
about their position, as well as their professional background and working experiences.
• What are the economic barriers
In the second part, to
theautomating manufacturing
underlying research context of thisprocesses?
study was explained to the
• What are the ecological barriers
interviewees. to automating
Ultimately, manufacturing
in the third part, processes?
experts were asked to provide their detailed
• What are the social barriers to automating manufacturing processes? encountered in their
opinion on barriers that they expect to encounter or have already
practical experience when implementing automation into production processes. Inspired
• What are the process
by the barriers
overview of to risks
automating
of adoptingmanufacturing processes?
Industry 4.0 by Birkel et al. [29], the experts were
• What are the technical
asked thebarriers
followingto automating manufacturing processes?
questions:
• What are the IT barriers
• What toareautomating manufacturing
the economic barriers to automatingprocesses?
manufacturing processes?
• What are the ecological barriers to automating manufacturing processes?
• What are the regulatory barriers to automating manufacturing processes?
• What are the social barriers to automating manufacturing processes?
The expert interviews
• were
What conducted
are the via an
process barriers online meeting
to automating tool and
manufacturing lasted between
processes?
• What are the technical barriers to automating manufacturing
30 and 53 min. To ensure all relevant informationwas captured, the interviews were au- processes?
• What are the IT barriers to automating manufacturing processes?
dio-recorded and transcribed.
• What areSubsequently, qualitative
the regulatory barriers content
to automating analysis [59]
manufacturing was applied
processes?
to analyze the collected data by identifying
The expert interviews werecommonconducted patterns and
via an online themes.
meeting Tolasted
tool and structure
between
the data, following Gioia et al. [60], a systematic coding procedure consisting of three steps
30 and 53 min. To ensure all relevant informationwas captured, the interviews were audio-
recorded and transcribed. Subsequently, qualitative content analysis [59] was applied to
was applied (see Figure 1). Initially, first-order categories were derived from the interview
analyze the collected data by identifying common patterns and themes. To structure the
data. As a second step, these
data, categories
following Gioia et al.were
[60], asynthesized
systematic codinginto second-order
procedure concepts
consisting of three stepsin-
was
spired by previous findings of the
applied (see extant
Figure literature
1). Initially, [61].
first-order Ultimately,
categories the identified
were derived second-
from the interview data.
order concepts were As a second step, these categories were synthesized into second-order concepts inspired
consolidated into seven barrier dimensions. The resulting dimen-
by previous findings of the extant literature [61]. Ultimately, the identified second-order
sions, as well as second-order
concepts were(top-codes)
consolidatedand into first-order (sub-codes)
seven barrier dimensions. Theitems, can
resulting be foundas
dimensions,
in Table 2. well as second-order (top-codes) and first-order (sub-codes) items, can be found in Table 2.
1. Systematicbased
Figureprocedure
Figure 1. Systematic coding coding procedure
on Birkelbased on[29]
et al. Birkeland
et al.Gioia
[29] and
etGioia et al. [60].
al. [60].
Table 2. Top-codes and sub-codes within barrier dimensions.
Dimension Top-Code Sub-Code 1 Exemplary Expert Statement

High initial investment (7)
“The investment costs are disproportionate to the benefits.” (E6)
Financial Higher fixed costs (2)
“We would need IT specialists that have different wage structures compared to craftsmen.” (E8)
Higher personnel costs (3)
Economic Low production quantity (3)
“Due to small quantities, automation is not economically viable.” (E6)
[17,18,55] Demand Low capacity utilization (2)
“I would have to ensure high capacity utilization of the production facility.” (E2)
Small project scale (1)
Profitability of conventional con. (3) “This expensive technology cannot compete with the prevalent wage structure of the industry.” (E7)
Competition
Loss of flexibility (4) “We are customer-oriented and project-based. Creating a repetition effect using robots is therefore difficult.” (E1)
Transport
Ecological [51,62] Longer transport distances (3) “Through automation, I am more bound to one location. Transport distances will increase.” (E8)
emissions
Internal resistance (3)
Corporate culture Communication (3) “Older employees are skeptical about automation and digitization. And I think there is also great fear.” (E4)
Fear (2)
Individual customer requests (6)
“The industry is very traditional. I need my architect, my structural engineer, my landscape planner.
Industry culture Negative attitude (4)
Authorities have certain procedures that do not allow industrialized construction.” (E7)
Social Traditional thinking (2)
[63–65] Own Knowledge (2)
“Industrial planning is much, much more complex. You have to deal with the system much more. You are
Knowledge Industry partners’ knowledge (3)
almost a mechanical engineer when you plan with modules.” (E7)
Authorities’ knowledge (1)
Job losses (2)
“The craftsman who currently screws the drywall panels onto the walls will no longer be able to find a job in an
Workforce Missing qualification (4)
automated production line because he simply cannot handle this relatively complicated technology.” (E1)
New job descriptions (2)
Late design changes (3)
“Also, the consistency. I must control the entire process chain to make it work optimally.” (E8)
Industry Fragmented industry (5)
“The construction sector is still very fragmented with thousands of two-person and three-person offices.” (E3)
Tendering not suitable (1)
Process Low standardization (7) “Currently every building is a prototype.” (E2)
[18,62,66] Production Production sequence (5) “The process would require restructuring. Flow principle should be implemented.” (E4)
Depth of planning (3) “Shift from drawing to parameterizing an element.” (E8)
Transport restrictions (1)
“If we want to increase quantity, we have to stock more material, as there have been frequent
Logistics High stock of inventory (1)
supply shortages recently.” (E4)
Space for finished products (1)
Table 2. Cont.
Dimension Top-Code Sub-Code 1 Exemplary Expert Statement

Technical feasibility of robotics (6)
Machinery “How do I tile or paint a wall? How does outfitting work using automation?” (E6)
Availability of machinery (2)
Technical Loss of flexibility (5)

[2,56,67] Material Availability of main material (2) “I have to commit myself to a building material: I cannot weld wood, but I need to weld steel.” (E3)
Component assembly (2)
Building “Varieties in requirements of clients, construction sites, and federal states make high quantities
Distinct construction sites (2)
geometry hardly possible.” (E3)
IT infrastructure IT capabilities of partners (2) “Externally, we cannot use BIM because our partners do not know what to do with it.” (E1)
Build-up of a database (2) “Each product that is purchased should be included in a database. [ . . . ] However, the administrative
IT Database
Maintain a detailed database (2) effort is high.” (E2)
[51,54,68]
Transfer of 3D models to machines (3)
“Our plans are 3D and purely digital. The question is if we can transfer those to machines adequately.” (E2)
Software Software interfaces (6)
“There is no seamless IT solution like in the manufacturing industry. We are forced to work with interfaces.” (E7)
Availability of suitable software (2)
Regulations in each state differ (7)
“It would be very helpful to have the same building regulations Germany-wide and all over Europe.” (E3)
Regulations Unspecified construction method (4)
“There are no appropriate regulations. There is no norm that is called ‘modular construction’.” (E4)
Outdated industry norms (2)
Extensive inspection and testing (4) “Every part is produced with the same reinforcement. However, reinforcement acceptance must
Permissions No standardization of permissions (5) always take place.” (E7)
Regulatory
Inefficient public authorities (3) “There is a lack of knowledge among authorities concerning this construction method.” (E2)
[16,19,69]
Tendering and Low standardization of tenders (2) “Tender several projects at the same time that are built with the same system.” (E2)
contracting Low requirements in contracting (2) “Bidders must meet stricter requirements concerning working conditions.” (E7)
Changing subsidies for clients (2)
“If one energy standard is promoted more than another, I have to adjust the product.” (E8)
Funding Lack of financial support (2)
“Know-how funding through consulting services regarding the implementation of automation.” (E1)
Lack of know-how funding (1)
1 (number of mentions), multiple answers possible.
4. Results
The results reveal the following seven barrier dimensions: economical, ecological, social,
process-related, technical, IT-related, and regulatory. The dimensions are further classified into
21 second-order and 53 first-order categories that hinder the implementation of automa-
tion in MC. Table 2 gives an overview of the dimensions and sub-categories, including
exemplary expert statements.
4.1. Economic
4.1.1. Financial
Concerning the financial barriers to implementing automation, it has already been
shown in other sectors that replacing manual process steps with automated machinery
and robotics comes with high costs [17]. Therefore, it is not surprising that the high initial
investment for setting up fully automated and digitized factories for MC is also a major
challenge in this context. Manufacturers cannot currently estimate the economic benefits
of this technological innovation or they even expect the returns to be not high enough
yet. Besides large investments beforehand, practitioners fear a loss of flexibility in their
production system due to higher capital and fixed costs. More precisely, the costs for loans
to acquire the machinery, as well as the operation and maintenance, are significantly higher
than employing craftsmen workers to assemble the modules manually. In addition, the
implementation of automated production systems would require hiring employees with
different job profiles (i.e., IT specialists and mechanical engineers), likely leading to higher
personnel costs, or, respectively, specific intensive training for current workers.
4.1.2. Demand
With regard to the current demand for MC, practitioners emphasized that the pro-
duction volume is still too low for an economically viable implementation of automation.
Accordingly, for a profitable application of robotics, the production output would have
to be sufficiently high and stable over many years to ensure high capacity utilization and
a considerable good return on investment, which is currently at least questionable. One
problem in this context is the low degree of standardization concerning individual projects.
Oftentimes, orders placed by customers are very individual and of a small scale, so the pro-
duction line has to be re-adjusted with every new project and the repeatability is relatively
low. Accordingly, the costs for implementing a highly complex infrastructure including
state-of-the-art machinery and software are currently not considered to lead to the desired
cost savings (i.e., economies of scale) that would be expected for such an investment.
4.1.3. Competition
Generally speaking, MC manufacturers are competing with traditional contractors.
Due to the cost- and profit-driven nature of the construction business, low-wage structures
in conventional on-site building projects are the reference. Considering the higher costs of
manufacturing buildings in a fully automated factory environment, MC manufacturers can
hardly compete with their competitors applying the conventional construction approach.
Accordingly, E7 stated: “This expensive technology cannot compete with the prevalent
wage structure of the industry”. Some practitioners additionally claimed that to make
automation a viable business case, the industry would have to change from a cost- to a
value-driven approach. More precisely, commercial customers should focus more on other
factors, such as the delivered quality, rather than the cheapest offer, when awarding a
contract. Another problem MC manufacturers face is the still high economic feasibility of
conventional construction. Consequently, applying conventional operations (craftsmanship
approach) themselves in a factory environment yields profits that are considered high
enough. The risk of changing these procedures and contributing to large investments is
therefore considered to be inappropriately high. Another problem lies in the loss of flexi-
bility regarding individual customer requests. Practitioners fear that their high customer
orientation could suffer from increased automation of their production processes.
4.2. Ecological
Transport Emissions
From an ecological point of view, barriers to automating the MC production process
appear to be manageable, which might be due to the general superiority of OSC over
conventional construction in terms of environmental sustainability [20]. Nevertheless,
practitioners emphasized that, for an economical application of automation, the produc-
tion would have to be bundled at one location to ensure a high production output with
highcapacity utilization. As a consequence, the total transport distances from the factory to
construction sites would very likely increase. Accordingly, the resulting increased transport
emissions compared to closer, non-automated production facilities have to be considered.
4.3. Social
4.3.1. Corporate Culture
The socio-cultural perspective on barriers can be distinguished between a company-
internal and an external, industry-wide perspective. It equally applies to both that the con-
struction industry is well-known for conservative and risk-averse thinking [63]; challenging
the status quo of operation procedures (i.e., craftsmanship vs. automation) traditionally
attracts resistance [70]. Concerning internal factors, one problem lies in the resistance of
MC manufacturers’ employees towards this technological advancement. While shopfloor
operators might fear their job security due to the potential obsolescence of their current
manual tasks, managers could view this change in operating procedures with skepticism,
as they are oftentimes used to traditional craftsmanship approaches.
4.3.2. Industry Culture

From an external perspective, industry participants mostly view off-site approaches
with skepticism, which may be due to a negative attitude or aversion towards change in
general. Another problem is the prevailing order mechanism of the industry. Accordingly,
customers of MC manufacturers or general contractors are used to ordering highly indi-
vidualized buildings rather than being offered standardized solutions. One expert stated:
“When comparing cars and buildings, with buildings customers are less likely to accept
design fixations”. Consequently, the customer expectations towards value delivery based
on an engineer-to-order approach limit the application of high levels of standardization
and automation in the production of MC.
4.3.3. Knowledge
Since most employees, including managers and executives, of MC manufacturers
have a professional background in architecture, engineering, and construction (AEC), their
knowledge of manufacturing approaches, including the automation of manufacturing
processes, might be limited and therefore a considerable barrier to introducing automation.
Another problem lies in the industry partners’ knowledge. For instance, architects are
oftentimes not used to planning with high levels of prefabrication and automated systems.
Since the final design has to be fixed earlier in the process and hardly allows later changes,
planning can generally be regarded as more sophisticated and time-intensive compared to
conventional construction. One expert stated that it would almost require the planner to be
a “mechanical engineer”.
4.3.4. Workforce
Considering problems related to the workforce, current field operators do not have
the qualifications to control and configure an automated production line, as they are mostly
craftsmen used to assemble building components manually. Therefore, workers either
would have to be adequately trained to fit this new job description or would have to
be replaced by workers with other job profiles. While this would open the chance of
attracting younger people, thereby counteracting the problem of an aging workforce, MC
manufacturers have to consider the social factor of potential job losses, as well as the
required time and costs for the respective training of current employees.
4.4. Process
4.4.1. Industry
Concerning process-related barriers, practitioners emphasized the unfavorable prevail-
ing value-delivering approach of the construction industry. Since the integration along the
construction supply chain is very low, there are many individuals and companies involved
requiring many interfaces, leading to inefficiencies during the overall construction process.
More precisely, the traditional approach includes specialists from different areas, such as
architects, structural engineers, and landscape planners, that work independently from
each other and are oftentimes organized in small offices. Due to this fragmented industry
structure, many smaller players are not capable to innovate and adopt the measures to
deal with industrialized construction. In addition, practitioners raised that authorities’
working procedures (such as permissions) are incompatible with the OSC approach (also
see Section 4.7).
Another problem that is hindering the automation of processes is late design changes.
Since customers, as well as project participants, are used to on-site changes of the original
design in the traditional approach, it is expected to be also possible in MC. However, late
design changes require adoptions and configurations of production lines that sabotage
the whole manufacturing process. All in all, the production process of MC is currently
oftentimes controlled by external participants requiring late changes to the production
facility or, respectively, manual changes.
4.4.2. Production
One of the most mentioned barriers to automation is the low level of standardization in
current MC productions. Practitioners claimed that every building is planned and produced
very individually (“Prototype”, E2), which requires the adoption of the production process
with every new project. Many MC manufacturers do not have fixed module sizes, which
additionally results in higher variability and complexity.
Another problem is the current production set-up. The flow of material is organized
like a workshop, rather than as a production line, which is not favorable for the application
of advanced automation technologies. Consequently, the entire factory design and setup,
as well as operating procedures, would have to be re-structured to enable an efficient
implementation of robotics. Lastly, practitioners emphasized that the design and the corre-
sponding work instructions are still based on drawings, rather than being parameterized.
More precisely, automated machines would need to have digitized information to work
with, so drawing would have to be translated into a parametric language readable by
machines (computer-aided manufacturing).
4.4.3. Logistics
Concerning logistics, practitioners emphasized the required high production volume
for introducing economically viable automation would bring several logistical challenges
with it. Accordingly, the warehouses in which production materials are stocked would have
to be expanded. One expert specifically mentioned that just-in-time construction would
hardly be possible due to supply problems of essential components, such as insulation.
Another expert claimed that, occasionally, modules that are ready for assembly on-site have
to be stored close to the production facility until being transported to the construction site.
Limited factory space might therefore hamper further increase in production output.
4.5. Technical
4.5.1. Machinery
From a technical perspective, many practitioners expressed skepticism towards the
technical feasibility of robotics for the manufacturing of the modules. Questions arose
about how specific operating procedures that are currently done manually could be done
using robotics. For instance, E6 stated: “How do I tile or paint a wall? How does outfitting
work using automation?”. While the joining of large components such as walls and
ceilings are of less concern to most practitioners, the steps inside the module (i.e., the
furnishing of the modules) are seen as a major challenge for implementing automated
machinery. In this context, the flexibility of the machinery to perform the required tasks is
especially questioned. Another problem according to the experts can be seen in the general
availability of adequate machinery and robotics. Since most machines are designed for
different purposes than building a module for residential living, it was questioned whether
the required technology even exists.
4.5.2. Material
From the perspective of materials used for constructing a module, there are tradition-
ally three different possible choices: wood, concrete, and steel. When implementing an
automated production system, MC manufacturers would have to commit themselves to
one main material and therefore lose flexibility. This is considered to be due to the different
processing for each of these materials. E3 put it as follows: “I cannot weld wood, but I need
to weld steel.” While a change of the main construction material would require various
changes to the production facility, it is assumed that a machine cannot be easily adjusted to
process other materials. MC manufacturers would therefore lose the chance of responding
to changes in regulations or market dynamics for certain production components.
4.5.3. Building Geometry

While the building geometry or, respectively, the geometry of the building site can
also be regarded as a barrier towards OSC in general, this factor is of specific concern
for implementing an automated production. Accordingly, the requirements of distinct
construction sites hinder the introduction of a module with standardized dimensions
(height, length, width) and therefore are expected to limit the application of full automation
due to frequent adjustments to the production line.
4.6. IT
4.6.1. IT Infrastructure
One concern in terms of IT is the digital capability of external stakeholders. Some
practitioners reported that the benefits of collaborating with external partners by using
sophisticated approaches, such as BIM, are still very limited due to their low level of
digitalization. E1 emphasized that this holds for project participants, such as planners of
technical building equipment, as well as the clients themselves. E8 added that there is a
lack of “continuity of the digital chain” from manufacturing to final delivery of the project
to the clients.
4.6.2. Database
In order to implement robotics and automation, there must necessarily be digitization.
Accordingly, a database is required consisting of all information for each component used
in the production process. While E2 emphasized that the effort to implement and maintain
such a database is extremely high, E4 stated: “Without data, there is no digitalization. The
data is needed to communicate with the machines”. Consequently, one challenge is to fully
digitize current procedures before being able to implement automation.
4.6.3. Software
Concerning software, practitioners see three major barriers. First, there is the difficulty
of translating the traditionally used 3D models to parameters that could be used by robotic
applications to perform the required manufacturing procedures. While practitioners stated
that the design of the modules is already fully digitized, some questioned if this translation
from 3D model to parameters would even be possible. Second, there are many intersections
between current software solutions used to manufacture the modules. There is currently
no software that allows a continuous flow through production. Instead, drawings from
architects in the design phase have to be transferred to other software applications for
production plans that can be handled by mechanical engineers and craftsmen in the factory.
Third, current software that would be suitable for automated manufacturing is not designed
for construction, but rather for mechanical engineering approaches. According to an
expert, software suppliers refrain from adapting the software to match industrialized
construction approaches.
4.7. Regulatory
4.7.1. Regulations
Concerning regulations, practitioners claimed that the current regulatory construction
framework is not in favor of OSC and MC. Generally, regulations differ not only between
countries, but even between the states of one country. For instance, in Germany, there
are 16 different state building codes with varying requirements for newly built buildings.
Consequently, MC manufacturers must follow the code in force in the state in which the
building is erected, regardless of where the modules were produced. This means that the
production line needs to keep a certain degree of flexibility to enable meeting the different
requirements in each state to operate nationwide or beyond.
Another barrier is the lack of an appropriate definition of the construction method
itself from a building law perspective. More precisely, there is currently no guide for test
engineers, such as structural engineers, on how to provide the required proof for proper
execution for buildings built applying MC. As a consequence, the process of proof testing
gets more complicated, leading to delays. Lastly, there are outdated norms that hamper the
automation of production. One expert stated that some norms that are valid in conventional
construction do not match OSC procedures. More precisely, not all norms make sense in
the context of MC because the requirements can be met in other ways.
4.7.2. Permissions
In contrast to quality management approaches known from the general manufacturing
industry, the grants of permissions in OSC are still oriented towards one-of-a-kind produc-
tions (i.e., an individual building). Accordingly, inspections and testing are the same as in
conventional construction, although large parts of the underlying structure do not change
from project to project and have therefore already been approved. While in conventional
construction thorough inspections and testing are necessary to ensure the building’s safety,
in industrialized construction, it might be redundant and instead interrupts the production
flow. As a consequence, the production capacity utilization and the respective production
output are affected, which again hampers the potential for automation.
Besides the granting of permissions still being oriented towards conventional con-
struction projects, many practitioners criticized that there are no standardized permissions.
Although there is high repetition and modules are produced the same way in every batch,
the underlying structure of the modules has to be approved in every project. This is not
only time-consuming, but also costly for the builder who has to pay the inspection fees.
Lastly, some experts claimed that there are inefficiencies concerning the authorities who
grant the permissions to realize a specific construction project. Obtaining the appropriate
permits still takes too long and thus delays the construction process.
4.7.3. Tendering and Contracting

Some experts considered current tendering approaches unfavorable for scaling up
production with high levels of automation. More precisely, it was stated that many tenders
are not suitable for MC because there are many requirements concerning specific parts of
the building, such as individual dwelling designs that are fixed late in the process (e.g., the
developer lets buyers choose the color of the tiles). E2 emphasized in this context that the
first step would be to specifically tender MC, and the second to consolidate similar tenders,
which would save time and costs for all involved parties.
Concerning contracting, experts criticized the still prevailing approach of the industry
to focus primarily on the price of an offer, rather than giving more emphasis on other evalu-
ation criteria in the decision-making process. E7 claimed that public contracting authorities
in particular should act as role models by placing a higher emphasis on decision criteria
such as working conditions, quality of the work, or level of digitization when awarding a
contract. By implementing higher requirements for bidding companies, contractors would
be incentivized to implement automated production systems.
4.7.4. Funding
The funding aspect can be divided into funding received by MC manufacturers
themselves and funding received by potential customers. The latter relates to government
aid provided to builders if the newly erected building meets certain requirements. For
instance, in Germany, buildings with a high level of energy efficiency are incentivized with
financial subsidies or low-interest loans. However, this funding is subject to short-term
changes that can decrease the attractivity of a certain building conceptualization from one
day to the next. For MC manufacturers, this circumstance results in a certain degree of
uncertainty regarding the requirements of the offered product. In practice, the production
line would have to be adjusted to meet the new requirements.
Concerning funding directed to MC manufacturers, experts criticized that there are
currently no adequate public subsidies to incentivize the implementation of automated
production systems. According to some experts, public authorities would either have
to offer direct financial subsidies for acquiring the respective machinery and software or
have to offer better depreciation options. Besides financial aid, E1 stated that funding for
consultancy on an efficient implementation of an automated system would be even more
desirable. Since most practitioners have a professional background in AEC, it would be
favorable to obtain guidance from professionals with extensive knowledge of automation
in manufacturing.
5. Discussion
Implementing automation into the production processes of MC has the potential
to significantly boost productivity and production outputs. However, the adoption of
automated production systems in the context of prefabrication is still relatively low. To
facilitate widespread adoption, it is decisive to identify and understand the underlying
barriers for MC manufacturers. In the following, the key findings of this study are reflected
upon and discussed under consideration of the extant literature.
As illustrated in Table 2, numerous factors aggravating the implementation of au-
tomation were identified. Based on the identified dimensions and their underlying sub-
categories, a comprehensive framework illustrating the barriers to automation in MC has
been created (see Figure 2). Notably, in addition to the high number of individual factors
(53 sub-codes), there are numerous interrelationships between the respective barriers that
contribute to the complexity of the framework.
From an economic perspective, with one of the most mentioned of all factors, the high
initial investment can be regarded as a severe barrier to implementing automation. To
replace craftsmanship operations with automated machinery, significant investments have
to be made in terms of technical equipment [71], as well as training or even new person-
nel [65]. While this observation could also be made in other industries where automating
processes use advanced technologies [29] and for adopting robotics in construction in
general [17], in the case of MC, it is highly related to the demand and the production
volume. Since the production output is currently considered too low, implementing an au-
tomated production system does not appear to be economically viable. Recent estimations
proposed that 1000 units per year would be required to achieve the desired economies of
scale with significant cost reductions [72]. In accordance, Bock and Linner [18] reported

that productivity and efficiency increase significantly with a higher production output (Per-
formance Multiplication Effect). However, sufficient yearly outputs are yet to be achieved.
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be achieved. In addition, results reveal that practitioners cannot currently estimate the may be because,
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practice,
production facility, shorter production and construction times generally reduce the required
which has also been reported by Chen et al. [54]. In addition, research on barriers to gen-
energy and thereby the environmental impact of the overall project [49]. However, longer
erally adopting MC has shown that financial barriers are highly influenced by other fac-
tors [20]. Therefore, offering adequate funding in the form of financial subsidies and
knowledge consulting services to MC manufacturers may lower the economic barrier to
implementing automation.
transport distances due to consolidations of production volumes in one location need to be

taken into account [51].
From a socio-cultural perspective, a major barrier to implementing new technologies
goes back to the prevailing culture of the construction industry, which is characterized
by conservative and risk-averse thinking with a strong resistance to change [63]. While
this circumstance can be regarded as a general challenge for adopting MC at all, even
within MC manufacturers, this cultural peculiarity poses a significant barrier. Accordingly,
internal employees often view the implementation of new technologies with skepticism. One
major reason for that might be the fear of being replaced by automated machinery and robotics,
resulting in job losses [65]. To lower this resistant attitude, adequate communication and change
management are required, which are currently lacking for the greater part [30,50]. Naturally,
as a prerequisite of applying change management, there has to be the commitment of the
top management [56].
Externally, the prevailing industry culture hampers the implementation of automation
in multiple ways. Most considered by the experts are the expectations of customers for
highly individualized buildings. Due to changing product specifications, the opportunities
for standardization are considered to be low. Since this specific factor is highly interwoven
with the process barrier concerning the current value creation, it did not get much attention
in the extant literature as a stand-alone barrier. However, it is recommended to consider
this challenge separately, as it refers to the attitude of customers that would need to change
to overcome this barrier. Related findings from the literature include the lack of reference
architectures [50] and the requirement of adapting business practices to meet customer
expectations using prefabrication [64].
Concerning the process, the results reveal barriers in the context of the industry,
production, and logistics processes. While industry and production processes both include
challenges that have been mentioned by many experts in this study, problems in terms
of logistics were only mentioned by a few practitioners. This may imply that automating
production processes does not induce significant logistical restrictions. While there are
certainly challenges comparing conventional and industrialized construction [62], barriers
specifically referring to automation can mainly be limited to a higher stock of inventory
and more space for finished products resulting from an increased production output.
With regard to the industry process, barriers can generally be ascribed to the frag-
mented industry structure [30]. Since the construction business is characterized by many in-
terconnections and interdependencies between its stakeholders and project participants [22],
the successful implementation of innovative technologies relies on collaborating partners
taking the same path. However, since there are numerous small offices and medium-sized
companies that are either not able or willing to financially commit to these innovations,
the benefits of automation may not be fully exploited [51]. A countermeasure may be
increasing integration of MC manufacturers along the value chain [54]. Accordingly, by
creating a continuous process that incorporates decisive tasks of the overall process, such
as design and construction operations, the information exchange can be significantly im-
proved, resulting in less iterative work and fewer reworks on site. In contrast, Davila
Delgado et al. [17] reported that the fragmented industry structure cannot be regarded as
a severe barrier to implementing robotics, which may be due to their wider perspective
including on-site applications of robotics.
In terms of the number of mentions, low standardization in the context of production
is among the most challenging factors for implementing automation. According to the
experts, current production operations have a low degree of standardization due to the
individuality of the ordered buildings. This is indirectly in line with findings from Pan
and Pan [56], who reported that introducing product standardization could be a significant
driver to integrate robotics into production. Bock and Linner [2] emphasized that the current
structure of the final product (i.e., a conventional building) does not fit the production
process using automation. Consequently, the product structure would have to be changed
towards a robot-oriented design. Similarly, the current production sequence is aligned
with conventional construction operations in a workshop-like organization, rather than in

a production line, which would require significant changes to the production facility when
implementing automation [18].
Lastly, the results reveal that there is a barrier concerning the depth of planning.
In this context, a great challenge appears to be machine-ready planning and design by
architects and engineers. Accordingly, during the planning and design phase, architects
already have to be able to incorporate the requirements for building a modular rather than
a conventional building [51]. In this regard, it is decisive to work towards parametric and
computational designs that are transferable to manufacturing machines because, otherwise,
the “translation” may turn into a bottleneck for the whole production system [68].
From a technical perspective, barriers concerning the machinery that is supposed
to perform the tasks that are currently mostly done manually were encountered. Many
experts voiced their doubts about the feasibility of implementing robotics for assembling
parts of a module. Similarly, researchers have reported the immaturity of robotics for
handling non-standardized elements [56] or the immaturity of available technologies in
general [17]. In line with this finding, Buchli et al. [74] reported that most automation
and robotics technologies are not generally applicable, but rather domain-specific. Conse-
quently, technologies used in other production contexts would either have to be adopted or
re-engineered to fit the specific context of MC. It is therefore advisable to test these doubts
for reasonability by creating prototype production lines [41]. Since this testing requires
considerable amounts of financial resources, forming a consortium of MC manufacturers or
collaborating with companies from other industries could facilitate conducting such a project.
In addition, experts raised attention to difficulties concerning the choice of main
construction materials when implementing automation. Accordingly, since there are doubts
that an automated production line can respond efficiently to a change in main materials
(wood, steel, or concrete), there is a loss of flexibility compared to manually performed
operations. In this context, Bock and Linner [18] stated that the choice of material is
already a restriction in terms of customer preferences. Accordingly, the use of steel-framed
buildings is used for functional buildings, such as hospitals, hotels, and offices, rather than
residential buildings. Since implementing automation is a long-term commitment for MC
manufacturers, and a change of materials may occur over time, the compatibility of robotics
to handle the different materials should be verified in advance.
Concerning IT barriers, one of the most severe challenges investigated in this study is
software interfaces. In particular, difficulties were observed in converting the geometric
design to parametric and computational information that can be processed by automated
machines. This echoes findings from Tibaut et al. [68], who investigated interoperability
requirements for applying automated manufacturing systems in construction. According
to the authors, the processing of the geometric data using computer-aided manufacturing
(CAM) software still has some limitations. The resulting information that is readable for
machines is still too low for complex building productions. Therefore, there is a need
for integrated software solutions to streamline the generation of tasks for automated
manufacturing machines that supersede the interfaces when processing geometric and
parametric data. However, as also stated by an expert, suppliers of software for robotics
and automation in the manufacturing environment have recently shown low interest in
cooperating with firms that operate in the building industry [52].
Another barrier again refers to the fragmented supply chain structure of the industry.
Accordingly, many industry partners are not able to implement state-of-the-art IT solutions,
such as BIM, and therefore interrupt the digital chain [51]. Lastly, the results of this study
reveal that there is an additional effort in terms of setting up, as well as maintaining, an
appropriate database to implement automation [50]. Interestingly, concerns regarding data
and cybersecurity driven by an increased digitalization that have been reported in other
studies focusing on the implementation of advanced digital technologies [29,50] were been
mentioned by experts in this study. The reason for this may be the early stage of adoption
that the participating companies are in.
With regard to regulatory barriers, the results reveal the dimensions of regulations,
permissions, tendering and contracting, and funding. Concerning regulations, most experts
emphasized that the lack of a uniform building code is a critical barrier to implementing
automation. Due to regional differences in terms of building codes, production has to stay
flexible to be able to meet the requirements in each state. However, this is considered to
be placed to the debit of product standardization. Consequently, authorities have to align
codes and policies to ease the implementation of automation and robotics. In the extant
literature, this barrier has not received much attention, which might be due to the specific
regional circumstances in the context of this study.
Considering the granting of permissions, the results reveal that there is a lack of
standardized permissions. Experts in this study criticized that, although there is a high
repetition in their production, the required time and costs for receiving permissions are
inappropriately high due to long and complicated approval procedures [16]. This is also in
line with findings from Bock and Linner [18], who report that the construction method is
not sufficiently defined, but rather considered “nonstandard”, which even brings further
difficulties with it, such as aggravated granting of permissions for mortgages by financial
institutions for customers. This may result in a lower attractiveness of prefabricated
construction and, consequently, further compounds the problem of insufficient demand for
implementing automation and robotics.
Within contracting and tendering, current approaches are still heavily directed to-
wards the lowest price of a certain service in the context of construction, rather than placing
a higher emphasis on other evaluation criteria. Public authorities may either lead by ex-
ample by considering criteria such as working conditions, quality of work, and the level
of digitization more thoroughly, or implement mandatory regulations [56], defining the
respective requirements in terms of the aforementioned criteria. Consequently, by imple-
menting higher requirements for bidding companies, contractors would be incentivized to
implement automated production systems.
Lastly, barriers concerning governmental funding have to be considered. As already
reported by other researchers [17,56], there is currently a lack of adequate governmental
incentives in the form of financial support. Since implementing an automated production
system requires high initial investments, as well as high operating costs, MC manufac-
turers have to be subsidized to facilitate the adoption of this technological innovation.
In accordance, Pan and Pan [56] reported that a supportive regulatory environment in-
cluding incentives is a decisive driver for adopting automation and robotics. In addition,
the lack of knowledge support has to be considered. Since most practitioners in the MC
business have a professional background in AEC, experts with high expertise in automated
manufacturing and robotics are needed to efficiently introduce automation and robotics.
Therefore, authorities may subsidize consulting services for MC manufacturers planning
to implement automated production systems. Alternatively, cross-industry collaborations
could be pursued.
6. Conclusions
As an OSC approach with a very high level of prefabrication, MC offers ideal condi-
tions to implement manufacturing concepts that are known for fundamentally increasing
productivity, such as lean production and automation. However, currently, the share of
automation and robotics in the production process of MC is still relatively low. Conse-
quently, the potential of this construction method is far from being fully exploited. Given
the well-known benefits of digitizing and automating production processes, questions arise
regarding why MC manufacturers have not yet implemented the respective systems and
what the barriers to this implementation could be. In the extant literature, a comprehensive
overview of the particular barriers is still lacking.
Therefore, this study aimed to systematically investigate the factors hampering the
implementation of automation and robotics in MC. Based on a comprehensive review of the
extant literature, as well as in-depth expert interviews with highly experienced practitioners,
the results of this study reveal a framework of barriers constituting seven dimensions:
economical, ecological, social, process-related, technical, IT-related, and regulatory barriers.
From a theoretical lens, this study generally adds to the understanding of the underly-
ing barriers to implementing automation in MC. Considering the developed framework,
researchers are provided with plenty of opportunities for future research. For instance,
future studies may investigate the identified factors quantitatively, measuring the severity
of each barrier to determine which factor should be tackled first or with the most amount
of resources. Similarly, the study reveals several interrelationships between the respective
barriers (such as funding influencing the economic attractiveness of the implementation).
Future studies may investigate the interaction between the respective barriers by applying
appropriate research methods, such as multi-criteria decision-making analysis approaches.
From the perspective of practitioners, the results include multiple recommendations
for action to efficiently lower the barriers to implementing automation and robotics. Gener-
ally, the developed framework can be used as a guideline for decision makers planning
to implement the required measures for automating their production. The study thereby
paves the way to an increased level of digitization and automation in the construction
industry, which is likely to resolve the long-lasting problem of stagnating productivity.
While the results provide multiple practical implications, three applicational contributions
should be stressed in particular.
First, the study emphasizes the need for MC manufacturers to integrate along the value
chain to create a continuous process, lowering the dependencies on project participants that
are not capable or willing to innovate operation procedures. Second, low standardization
and individual customer requests were identified as major barriers to implementing an
automated production. While the latter can only partially be influenced, an increase in
standardized production is a necessary condition to introduce economically viable automa-
tion. MC manufacturers are therefore advised to reconsider the general product structure
of the modules. While current designs are based on conventional construction operations,
a design approach is needed to enable high levels of robotic applications (robot-oriented
design). Third, the results reveal that many practitioners even questioned the technical
feasibility of implementing automation in MC production processes, highlighting the sever-
ity of this barrier. It is, therefore, indispensable to either engage in close collaboration
with other MC manufacturers or firms from other industries with comparable production
processes to enable testing and the creation of low-scale prototypes.
Naturally, this study is not without limitations. As already indirectly mentioned above,
since this study is of an explorative and qualitative nature, the identified severity of the
barriers, as well as the corresponding interrelationships between the factors, can only partly
be assessed. Consequently, quantitative research approaches are needed to deepen the
findings of this study. In addition, although countermeasures and recommendations for
actions are discussed in this study, future research may investigate possible solutions more
thoroughly in a practical context using in-depth case studies. Lastly, expert interviews
are limited to eight representatives of companies from German-speaking regions. While
the low number of participants can be ascribed to the low number of MC manufacturers
in the countries under study in general, some results may be bound to specific regional
circumstances. Future studies should, therefore, strive to verify the findings of this study
in other regional settings.
Funding: I acknowledge financial support by Deutsche Forschungsgemeinschaft and Friedrich-Alexander-

Universität Erlangen-Nürnberg within the funding programme “Open Access Publication Funding”.
Acknowledgments: The authors thank the anonymous reviewers for their suggestions and
recommendations.
Conflicts of Interest: The authors declare no conflict of interest.
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sustainability

Abstract: As a sustainable alternative to conventional cast-in-situ construction, modular construction

Citation: Feldmann, F.G. Towards

Sustainability 2022, 14, 12944. https://doi.org/10.3390/su141912944 https://www.mdpi.com/journal/sustainability

2.1. Lean Construction and Construction 4.0

more effective responses to market fluctuations [45]. In addition, further improvements

2.2. Introducing Lean Automation in Modular Construction

2.3. Research Gap and Contributions

Table 1. Data sample. Experts from MC manufacturers.

Expert Position Employees

Table 2. Top-codes and sub-codes within barrier dimensions.

Dimension Top-Code Sub-Code 1 Exemplary Expert Statement

Dimension Top-Code Sub-Code 1 Exemplary Expert Statement

Technical Loss of flexibility (5)

4.3.2. Industry Culture

4.5.3. Building Geometry

4.7.3. Tendering and Contracting

Sustainability 2022, 14, 12944 15 of 22

transport distances due to consolidations of production volumes in one location need to be

with conventional construction operations in a workshop-like organization, rather than in

Funding: I acknowledge financial support by Deutsche Forschungsgemeinschaft and Friedrich-Alexander-

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