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|title=The role of people and digitalization as an enabler of resource efficiency in manufacturing
|pdfUrl=https://ceur-ws.org/Vol-3239/paper11.pdf
|volume=Vol-3239
|authors=Awwal Sanusi Abubakar,Steve Evans,Emanuele Gabriel Margherita,Xiaoxia Chen
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==The role of people and digitalization as an enabler of resource efficiency in manufacturing ==
https://ceur-ws.org/Vol-3239/paper11.pdf
The role of People and Digitalization as an Enabler of Resource
Efficiency in Manufacturing
Awwal Sanusi Abubakar 1, Steve Evans 1, Emanuele Gabriel Margherita2 and Xiaoxia Chen 3
1
University of Cambridge, Old Schools, Trinity Lane, Cambridge, CB2 1TN, United Kingdom.
2
University of Tuscia, Department of Economics Engineering Society and Organization – DEIM, Via del
Paradiso, 47, 01100, Viterbo, VT, Italy.
3
Chalmers University of Technology, Hörsalsvägen 7A, 412 96 Göteborg, Sweden.
Abstract
Global sustainability challenges have been escalating in recent times, resulting in climate
change, pollution, and resource scarcity. Reducing the amount of resources being used can help
to mitigate these challenges by lowering our carbon footprint, reducing waste and improving
our economic resilience. To achieve these benefits, researchers and industries have begun
looking into Industry 4.0 technologies as a tool to drive resource efficiency gains. In this paper,
the research question explores the challenges that hinder companies from adopting digital
technologies. Other topics discussed include how digital technologies can support resource
efficiency, and how people can support resource efficiency.
Data for this study was collected from a face-to-face workshop event which included expert
participants from industry, academia, and the UK Government. This workshop aimed to gain
insights into the adoption barriers and opportunities for digital technology to target
environmental performance.
The main adoption barrier identified was lack of knowledge. Other barriers include lack of
trust, lack of finance and lack of expertise. Environmental performance is usually not targeted
because it is not a priority for many organizations. Nevertheless, external stakeholders are
putting pressure on companies to incentivize sustainable change.
This paper identifies the challenges that hinder companies from adopting digital technologies
and gives insights into how digital technologies can support people for resource efficiency.
Keywords 1
Industry 4.0, digitalization, digital technologies, people, resource efficiency, sustainability,
manufacturing, Industry 5.0.
1. Introduction
Sustainability can be defined as the ability to meet current needs without compromising the future
generation [1]. According to the United Nations environment program, “the unsustainable use of
resources has triggered critical scarcities and caused climate change and widespread environmental
degradation” [2]. This stresses the urgency and need to reduce the amount of resources being used.
Resource efficiency has become vital for the above reason, as extracting more value from resources
inherently reduces the amount of resources needed. The benefits of resource efficiency directly impact
the economic and environmental dimensions of sustainability [1], [3]–[5]. From an economic
perspective, less resources needed lowers the operating expenditures of factories and makes them more
8th International Workshop on Socio-Technical Perspective in IS development (STPIS’22), August 19th– 21st 2022, Reykjavik, Iceland.
EMAIL: asa69@cam.ac.uk (A. 1); se321@cam.ac.uk (A. 2); emargherita@unitus.it (A. 3); xiaoxia.chen@chalmers.se (A. 4)
ORCID: 0000-0003-4873-9894 (A. 1); 0000-0003-1757-6842 (A. 2); 0000-0001-5528-6817 (A. 3); 0000-0001-8655-7958 (A. 4)
©️ 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
111
resilient in times of resource scarcity [6]. From an environmental perspective, less resources needed
reduces the carbon footprint and waste generated [6].
In factories, people can use resources a lot more efficiently than they currently do, and digital
technologies are often argued to serve as an enabler to help attain this goal [7]. Sensors and data
analytics tools can provide awareness as well as performance tracking. Artificial intelligence and
blockchain technology introduce novel ways to improve traceability and transparency throughout a
product’s lifetime [7]. This supports workers with the visibility and information to make better decisions
for resource efficiency benefits.
Yet, in order to gain the aforementioned value, there are still many challenges to be solved and gaps
hindering the sustainable adoption of digital technologies. Hence, the following Research Question
(RQ) was formulated:
RQ: What are the challenges that hinder companies from adopting digital technologies for resource
efficiency benefits?
In addition to the research question, insights into the following topics were discussed:
1. How can digital technologies support resource efficiency?
2. How can people support resource efficiency?
To answer the research question and discuss the above topics, the researcher completed a literature
review and organized a face-to-face workshop. The workshop included expert participants from
industry, academia, and the UK Government.
2. Literature review
The database used for this literature review was Scopus. Three sets of keywords were chosen: digital
(set A), resource efficiency (set B) and manufacturing (set C). All the sets included related terms with
singular and plural forms, as shown in table 1.
Table 1
List of keywords in the Scopus search box
Search box: Set A AND Set B AND Set C
Set A Set B Set C
Digital* OR {resource efficiency} Production OR
“Industr* 4.0” Manufacturing OR
Factory OR
Factories
The search taxonomy retrieved articles that had a combination of words from Set A, Set B and Set
C within the article title, abstract, or keywords. Through a thorough filtering process by abstract
evaluation relative to the research questions, 85 non-relevant articles were eliminated, leaving 52
articles.
The literature extracted from these articles can be categorized into Industry 4.0 and resource
efficiency. After exploring these two components independently, this review aims to combine them
together and identify the role of Industry 4.0 and people for resource efficiency benefits. Any potential
gaps identified would be mentioned in section 2.3.2.
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2.1. Industry 4.0
Based on the literature, Industry 4.0 is also referred to as industrial digitalization technologies,
digitalization technologies, and digital technologies. In the context of this paper, they all share the same
meaning. However, Industry 4.0 was used more often than other phrases. Hence, Industry 4.0 has been
selected as the phrase for this literature review.
Industry 4.0 can be defined as an intelligent horizonal and vertical networking of people, machines,
and information systems with the aim of dynamically controlling more complex industrial systems [10].
These systems need to be integrated for horizontal and vertical networking to occur. Horizontal
integration can be described as “the linkage of value creation modules throughout the value chain of a
product life cycle and between value chains of adjoining product lifecycles” [11]. This enables
traceability, which can be referred to as the ability to track materials, products, and processes, thereby
generating real-time information on the supply of materials, production of goods, and post-consumption
of resources [9]. Integrating through value networks enables collaboration between suppliers,
customers, and other external stakeholders [12], [13]. Vertical integration on the other hand, describes
system integration at different hierarchical levels [14]. For example, sensors on the shop floor level,
Manufacturing Execution Systems (MES) on the production management level, and Enterprise
Resource Planning (ERP) systems on the corporate planning level [14]. Vertical integration enables
flexible, reconfigurable manufacturing systems [15], which allows for a higher level of organization
and control over the whole value chain [11].
The United Nations Industrial Development Organization (UNIDO) points to the following six
attributes of Industry 4.0 [16]–[18]. These include virtualization, interoperability, modularity, service
orientation, real-time capability, and decentralization [14], [16]. Virtualization enables the creation of
virtual versions of physical systems, facilitating simulation processes [17]. Interoperability allows
systems, products, or applications to connect and communicate in a coordinated way without much
effort from the end user [17]. Modularity supports coupling or decoupling system modules; this grants
flexibility and allows for the rearrangement of production lines [19], [20]. Service orientation entails
services as an integral part of the production processes [21]. Real-time capability enables the instant
collection of information [17]. Decentralization can be described as distributed control; in the form of
independent, self-organized, and self-deciding entities [17], [22]
To attain the above attributes, the following technologies can be adopted by manufacturing
industries: additive manufacturing (3D-printing), artificial intelligence (machine learning), augmented
reality, autonomous robots, big data analytics, blockchain, cloud computing, digital twin (simulation),
Industrial Internet of Things (IIOT), sensors, and virtual reality [23].
There are several benefits and opportunities granted by Industry 4.0. These include; improved
product customization using additive manufacturing, increased operational productivity, accuracy, and
efficiency using autonomous robots, enhanced data visualization through augmented and virtual reality,
and improved data security using blockchain technology [14], [16], [24].
Despite these advantages, multiple barriers hinder the adoption of Industry 4.0. The main obstacles
are the cost of implementation, lack of expertise, and employees’ attitudes [16]. Other obstacles include
security issues, lack of trust, lack of management support, lack of policies, and lack of government
support [25].
Nevertheless, several authors believe that Industry 4.0 has significantly more benefits than the
challenges incurred [16], [23], [26].
2.2. Resource efficiency
Resource efficiency can be defined as extracting more value from resources [27]. This allows
companies to do more with less resources (material and energy), providing several benefits such as;
waste reduction, cost savings, and lower carbon footprint [27].
According to Duflou et al., resource efficiency approaches should address multiple levels [28],
ranging from technological improvements on a machine level through to the restructuring of
manufacturing sequences, factory layouts, and entire value creation networks [28], [29].
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In many industries, resource efficiency efforts are hindered by a lack of awareness about resource
consumption trends [27]. For instance, food factories may have generic data showing the amount of
resources consumed via utility bills [30]. However, these factories are often unaware of the resource
use and waste generated at a production-line level or even down to a machine level [30].
2.3. The role of Industry 4.0 and people for resource efficiency
Industry 4.0 is not just about technology, it is a socio-technical system in which technological, social,
and organizational aspects interact [14]. Hence, this section presents literature on how Industry 4.0 can
support people for resource efficiency benefits.
2.3.1. Current state of research
The current state of research can be categorized into health and safety, decision making, and
production on demand.
For improved health and safety, robots can replace humans in tasks that are considered dangerous
[13], [31], which leads to a reduction in work accidents and injuries [17], [32]. Robots can also work
alongside humans in physically demanding workstations, to help alleviate stress and preserve the
employees’ health and productivity [10]. Autonomous systems can handle repetitive and monotonous
tasks, this frees up time for people to undertake more mentally stimulating tasks and think about avenues
for resource efficiency improvements [31], [33], [34].
Decision making processes can be supported using information from Industry 4.0 technologies.
Industry 4.0 enables the collection and analysis of resource data down to the machine level [27]. This
provides the management team with information about the resource consumption of machines and
production lines [27]. Identifying the most inefficient parts of a system is key to making better decisions
for resource efficiency improvements. According to Muller et al., (2018), decision making processes
could fall to autonomous systems in a decentralized manner [10] . Klimant et al. (2021) adds to this
point by stating that “the human is still an important guarantor for the production of the future”; as an
intelligent problem solver, observer, and final decision maker [35].
Production on demand is another feature enabled by Industry 4.0. The higher the Industry 4.0
maturity level of a company, the greater its ability to match supply with demand [36]. Siltori et al.
(2021) supports this claim and elaborates on the subject by stating that Industry 4.0 enables a better
understanding of customers’ needs and consumption trends, making it possible to produce small batches
of highly customized products to meet demand [17]. This inherently reduces resource use since items
that are not demanded would not be produced [17], [18], [34].
In contrast to the expectations from academics and practitioners [36], Beier et al. (2022) argues that
“Industry 4.0 will not automatically lead to environmental improvements”, the digital transformation
needs to be accompanied by supporting measures such as regulation and incentivization [36].
2.3.2. Gaps in current research
There is an extensive amount of literature on Industry 4.0, but very few articles explore and establish
a connection between Industry 4.0 and resource efficiency. Resource efficiency is often treated as a co-
benefit rather than an integral part of Industry 4.0. Consequently, the resource efficiency dimension is
not researched comprehensively, and possible potentials are yet to be identified. In addition to this
knowledge gap, the researcher did not find articles specifically targeting “the role of people and Industry
4.0 for resource efficiency benefits”. Hence, this qualitative study was created to fill the gap in the
literature. The researcher also investigates several challenges that hinder the sustainable adoption of
Industry 4.0.
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3. Methodology
This section explains how the researcher gathered and analyzed data for this research.
3.1. Data collection
The data for this study was collected from a face-to-face workshop event titled “Strengthening
sustainability through Digitalization”. This workshop was conducted on the 31st of March 2022 at the
University of Cambridge, Institute for Manufacturing. There were 18 participants involved in the
workshop, from which three groups were formed. Out of these participants, eight were from industry,
six were from academia, and four were from the UK Government (civil servant on industrial policy).
To ensure diversity in ideas, each group included people who did not know each other and were from a
different background (academia, industry, and the UK government).
The workshop aimed to discuss and answer the following questions: “1. What is hindering you from
using digital technologies to improve environmental performance? 2. What is encouraging you to use
digital technologies to improve environmental performance?” We began the workshop by asking the
participants to try answering the above questions on post-it notes, one post-it note per idea, and no
discussions between members. After 15 minutes of silence, we asked the participants to share their post-
it notes with other members of the same group and discuss their ideas. They were encouraged to note
down any new ideas inspired by their conversations on the post-it notes. After 15 minutes of knowledge
sharing, the groups were asked to take their post-it notes and place them on an A0 paper. The A0 paper
contained the following headings: Design, Production, and Distribution on the X-axis, Brakes and
Accelerators on the Y-axis. After 30 minutes of organizing the post-it notes and discussing, the three
groups were asked to move around and see the A0-paper of the other groups while having discussions
and taking notes of any new inspirational ideas. After 30 minutes of knowledge sharing, the three groups
were asked to present their ideas, findings, and insights to everyone else. Once the presentations were
done, all the groups merged to discuss further for 90 minutes. The researcher took notes of the great
ideas shared during this meeting. Overall, the experts developed 229 post-it notes from the 3 A0-papers
and 35 post-it notes from the discussions afterward.
3.2. Data analysis
Data was transferred from the workshop post-it notes into an excel spreadsheet and analyzed by the
researcher. During the data analysis process, the researcher aimed to find relevant information on either
of the following topics: 1 The challenges that hinder companies from adopting digital technologies for
resource efficiency benefits. 2 How digital technology can support resource efficiency. 3 How people
can support resource efficiency. The researcher categorized relevant information based on the level of
priority shown by the participants. For example, data that was emphasized by the participants had a
higher level of priority over data that had no emphasis; data that was presented multiple times in a group
had a higher level of priority over data that was presented once; overlapping data from multiple
workshop groups had a higher level of priority over data that was presented by a single workshop group.
The researcher connected data with the highest level of priority to other relevant pieces of data. This
provided great insights into the most valuable information from the workshop and its connection to the
rest of the datasets.
4. Results
This section presents the analyses of all the information derived from the workshop data. Based on
the workshop participants, the phrase “digital technologies” was used in the place of “Industry 4.0”.
Hence, the result and discussion sections would continue with this phrase.
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4.1. Challenges that hinder companies from adopting digital technologies
The main challenges in adopting digital technologies were identified as lack of knowledge, lack of
incentive, lack of skills, lack of finance, lack of data sharing and lack of data integration.
The core of these challenges was found to spiral from a fundamental lack of knowledge about digital
technologies. According to the participants, many companies are unaware of how to implement digital
technology in a useful way to extract valuable information, they are also unaware of the benefits that
these technologies provide. Participants believe that there is a mindset in the industry which perceives
the implementation of digital technologies as too difficult and too expensive. This presumption adds
another barrier.
Organizations were considered to lack incentive to act first and take the risk. The identified risks
include 1 Losing a business advantage due to short-term product disruption and/or change in processes
required. 2 Risk of investing in technology that is soon outdated. 3 Risk of investing in a digital solution
that is unreliable and difficult to maintain. 4 Risk of workers not being able to adapt promptly.
All the workshop groups independently concluded that there is a skill gap in the industry as some
workers are unaware of how to operate digital technologies. This was believed to cause concerns in the
top-level management team regarding the in-house expertise required to administer, operate, and
manage these digital tools. Workers were described to have a busy schedule, making it difficult to find
time and learn a new skill, especially in small companies with less bandwidth.
Lack of finance was identified as another barrier. Participants claim that smaller companies may not
have the financial headroom to invest in digital technologies. They also pointed out that it is very
expensive to implement digital technology on a large scale to a high level of maturity.
4.2. How digital technologies can support resource efficiency
This sub-section is categorized into the design, manufacturing, and distribution stages of a product.
In the design stage, participants suggested modeling of products using software such as computer
aided design, product lifecycle management, and other simulation tools. They claim that these tools
provide early visualization and insights into how the product looks and operates, allowing for design
alterations to be made before investing in resources for manufacture. Without this technology,
participants were confident that a lot of resources would have been wasted in the trial-and-error phase
before finally creating the desired product. Data from these technologies was identified to enable more
informed decision-making, which could significantly impact resource use.
In the production stage, all participants supported the notion that digital technologies can improve
awareness of the waste generated by processes within a factory. Among all the benefits of digital
technologies, participants were most enthusiastic about traceability. They claim that traceability has a
high impact on resource efficiency as it allows factories to track materials and potentially retrieve them
for re-use and refurbishment.
In the distribution stage, participants stated that digital technologies could link consumers data
directly to the manufacturer, for the analysis and prediction of future consumption trends. They claim
that this information enables the manufacturer to supply just enough to meet the demand. In the case of
perishable goods like food, it was identified that this technology could have large resource saving
impacts as there would be less waste generated downstream.
4.3. How people can support resource efficiency
Based on responses from the participants, people within the leadership team, workers, and external
stakeholders can all be supported by digital technologies. These people can have an immense impact
on resource efficiency, but they need to educate themselves first and make it a priority.
The most important stakeholder to drive change in a company is the leadership team. It is presumed
that data from these technologies can help the leaders to make better and more informed decisions. One
of the workshop groups added to this point by stating that real-time data of workers can provide the
management team with insights into the sectors that require a larger allocation of human resources and
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vice versa. All the workshop groups independently mentioned that there is a shortage of skilled workers
that are digitally knowledgeable in the manufacturing industry, so training new workers is of great
importance. One of the industrial participants stated that “it is easier to take people from manufacturing
and give them the digital skills rather than the other way around, this is because manufacturing is more
complex”. It was noted that training should ideally be handled by skilled workers, but these workers
require the time to do so. Automation technology was recognized as a solution to this problem, as the
machines can handle repetitive laborious tasks, thereby freeing up the workers time and allowing them
to train others. It was identified that this training process can be supported using visualization
technologies like virtual reality, which can significantly speed up the training process while increasing
the workers’ confidence and reducing any potential risks, especially for workers in hazardous roles.
From a compliance perspective, all participants agreed that digital technology could provide reliable
information to support Environmental Social Governance (ESG) auditors during the auditing process.
Many of the industrial participants added to this point by stating that “digital technology can help to
counter-act greenwashing as we can accurately legitimize claims made by factories and suppliers”.
From a policy perspective, the government and policymakers were recommended to focus more on
resource efficiency rather than labor productivity. Participants from the UK government and industry
stated that “policies, regulations, and carbon taxation need to be put in place to incentivize factories to
comply with environmental sustainability goals”.
From a community perspective, digital technology was perceived to provide new avenues for
companies to engage with customers and suppliers. Investors and customers were recommended to
support resource efficiency by only investing in and buying from companies that are actively trying to
be more sustainable. This external pressure is said to incentivize companies to make resource efficiency
a priority.
5. Conclusions and discussion
In factories, people and digital technologies can improve resource efficiency, but our data shows
that it all begins with the leadership team. They need to have a vision and culture that supports the
incorporation of resource efficiency goals, this way, people can be encouraged to actively try and find
ways to improve. External stakeholders like the government, customers, and investors can help to
accelerate this process through policies, purchasing decisions and investment decisions. Once the right
culture is in place and there is a plan, technology can help with its execution. Digital technology can
provide awareness, enable performance tracking, and support traceability [7]. This equips people with
visibility and information to make better decisions. The above findings support Beier et al. (2022), who
argues against most of the literature by stating that “Industry 4.0 will not automatically lead to
environmental improvements, instead this transformation towards a more sustainable economy needs
to be accompanied by supporting measures” [36]. The researcher firmly agrees with Beier et al. (2022)
and recommends supporting measures such as, incentives, regulation, and education.
Most participants in the study believe that in the future, all systems within the factory and supply
chains would be connected to create an end-to-end holistic view. This view is expected to enable the
identification and investigation of resource efficiency hotspots [11], [37]. Bai et al. (2020) adds to this
point by stating that “It is necessary to address sustainability concerns from a holistic perspective” [23].
The participants recognized traceability as another major benefit of the end-to-end holistic view.
Traceability allows resources to be tracked and potentially retrieved for re-use and refurbishment [9].
According to the researcher, both benefits combined could compound to a high magnitude of resource
efficiency. Nevertheless, members of the supply chain need to be willing to share their data between
one another [24], [38]. Companies also need to share best practices to accelerate resource efficiency.
The main adoption barrier for digital technology was clearly identified by the experts to be lack of
knowledge. Companies were felt to be unaware of how to implement digital technology in a useful way,
they were also felt to be unaware of the benefits that these technologies provide.
The second adoption barrier is lack of finances. Factories that are interested in adopting digital
technologies may not be able to afford the cost of implementation and maintenance [39].
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The third adoption barrier is lack of trust. In factories that have implemented digital technologies,
there is still a lack of data sharing and integration due to trust issues. Companies are afraid of
accidentally revealing intellectual property and losing their competitive advantage [24]. Companies are
also afraid of security breaches that could happen when using digital technologies and sharing data [24].
The final adoption barrier is lack of standardization. For factories that are willing to share their data,
this data cannot easily be integrated due to different data formats and platforms [10], [14], [16].
Through this research, we have gained a better understanding of the connection between digital
technologies and people for resource efficiency benefits. We have learnt more about the adoption
barriers and the significant benefits of digital technologies when organizations target resource
efficiency rather than their historical use towards labor efficiency.
6. Acknowledgements
Firstly, I would like to thank my father (Alhaji Sanusi Abubakar) for funding this research and
making the journey possible. Secondly, I would like to thank my supervisor (Professor Steve Evans)
for his incredible support and guidance during the entire process of this research. Finally, I would like
to thank Xiaoxia Chen for collaborating with us and helping to organize the workshop event.
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