Analysis on the Technological Needs and Requirements of SMEs in Rail

Abstract

Change is the permanent situation we live in, fostered by three main drivers identified in the new European Industrial Strategy plus by the COVID-19 pandemics, which on the one hand is pushing SMEs towards digitalisation and on the other hand is pushing us all towards the need to recover and build a resilient – and sovereign – industry for Europe. These necessary adaptations should be exploited as an opportunity to improve their environmental footprint and economic resilience. One path to achieve this is the uptake of advanced technologies. This chapter identifies the needs and barriers for rail SMEs to adopt technologies and advance their level of digitalisation in order to improve their services, production processes and products. The analysis has received funding from the European Union’s Competitiveness of Small and Medium-Sized Enterprises (COSME) programme under the Grant Agreement number: 101037897 — STARS — COS-STRAT-2020-3-05.

1. Introduction

Change is the permanent situation we live in, driven by the double transition we are in the midst of, centred on climate neutrality and digital leadership. According to the European Industrial Strategy, the industrial transformation is articulated around three drivers: global competition, climate neutrality and digital future [1].

The COVID-19 crisis has highlighted the importance of digitalisation and the need to accelerate the progress of technological innovations developed to date [2]. This situation, on the one hand, has pushed SMEs towards digitalisation and, on the other hand, pushes all of us towards the need to recover and build a resilient - and sovereign - industry for Europe. This is why it is important to build on the progress that has been made in the sector towards its digital transformation [3].

The rail sector is one of the most energy-efficient modes of transport as it has significant advantages compared to other modes of transport. Being responsible for 9% of passenger transport and 7% of freight transport [4], it accounts for less than 0.4% of the GHG emissions of the entire transport sector. Rail is set to be a key driver for the decarbonisation of the transport industry [5].

Additionally, after the COVID-19 crisis, a global recovery of the rail supply market is expected with a growth of 3% per year until 2027, reaching an annual volume of approximately 211 billion euros in 2027 [3]. For all these reasons, we can define the railway sector as a technological, efficient and sustainable sector.

The chapter provides an analysis identifying the needs and obstacles that SMEs face in implementing advanced technologies in their organisations, which enable them to increase their digitalisation level in order to improve their services, production processes and products. The analysis has received funding from the European Union’s Competitiveness of Small and Medium-Sized Enterprises (COSME) programme under the Grant Agreement number: 101037897 — STARS — COS-STRAT-2020-3-05.

STARS project aims to boost SMEs in terms of production performances and innovation capabilities as well as sustainability and green transition thanks to the uptake of advanced technologies that can make the change possible. Advanced technologies have proven to give competitive advantages and definitely will build the “Future Mobility”. Several technologies that will drive the future of the Railway and Multimodality industrial meta-ecosystem are: Advanced Manufacturing, Advanced Materials, artificial intelligence, big data, blockchain, cloud computing, augmented/virtual reality and IoT, among others.

The following sections of this chapter describe on the one hand the state of the art and on the other hand the survey design and the methodology. This data was extracted on 27 June 2022 and has been processed to perform the classification and analysis of the SMEs depending on the needs and obstacles shown.

STARS priority lies in the recovery, transition and resilience of passenger and freight mobility to overcome, adapt and boost the several challenges that Europe is facing; to name a few: (1) transition in public mobility of passengers to respond to the megatrends of urbanisation (need to move growing numbers of people in urban areas), (2) the ageing population (need to make stations, vehicles and the whole travel experience accessible to people with reduced mobility), (3) changes in users and transport behaviour (need to adapt to the needs and aspirations of end users, seamless intermodality, etc.), (4) rail freight as the backbone of European logistics, as set out in the EU Green Deal and the new EU Strategy on Sustainable and Smart Mobility and (5) promoting and completing the green transition in our sector.

2. Background

In the last two decades, the European rail sector has undergone major changes. Today, rail transport plays a key role for Europe’s economy and society, but it has the potential to contribute much more. Like most sectors, the rail sector is experiencing the impact of digital transformation, but it is not doing so as fast as it should. In 2021, the European Commission adopted the Communication “The 2030 Digital Compass: the European way for the Digital Decade“, which mentions the importance of digital solutions that promote a more connected and automated mobility that reduces accidents, improves the quality of life and increases the efficiency of transport, as well as reduces its environmental impact.

That is why the sector has to adapt to this new revolution to remain competitive. The development of digital technologies in the rail sector will be key to achieving the ambitions of the European Green Pact and the Sustainable Development Goals. In addition, the digitisation of rail will increase its capacity, reliability and comfort, maintaining the EU’s leadership in rail transport equipment and services. New technologies such as artificial intelligence, big data, cloud computing, connectivity and autonomous driving will have a major impact on the sector. These technologies are creating a new environment in which rail operators will have to be more agile, act faster and continuously change to be successful.

This chapter’s results are aligned with the main principles of the EU Green Deal and the sustainability and mobility policies, also addressing the challenges faced by the railway industry:

1. Changing customer requirements: political, demographic, technological and market trends are changing customer needs. These changes, along with disruptive events such as the COVID-19 pandemic, require rail to be more competitive.

2. Rail as the backbone of a more sustainable European mobility: The need to improve performance and capacity to deliver a more sustainable transportation mix, adapting to increase demand.

3. High cost: currently, rail is often more expensive compared to other modes of transport. To be more competitive and support greater use in the future, it must offer services at a reduced cost.

4. Climate change: rail is one of the most sustainable modes of transport. Greater use of rail is necessary to meet climate targets.

5. Legacy systems and obsolescence: rail system assets are acquired on the assumption of very long life cycles and are based on national approaches.

6. Interaction with other transport modes: rail networks and associated services link well with other transport modes. Still, improvements are needed to better serve customer needs and to make rail a central element for future mobility and to increase its overall attractiveness.

7. Increased competition: the European rail industry is a world leader. However, it faces many challenges on a global level.

This means that the railway industry in the Europe, and specifically the SMEs, must also face these challenges. The survey results served to analyse the capacity of railway SMEs in reaching these challenges and trends.

3. Methodology

3.1 Survey

The implementation of the survey was based on an online European Survey platform. The implemented survey aims to collect data about the needs of enterprises of the railways and multimodal sector. It consists of 3 parts: the introduction, the SME profiling and the SME technological assessment.

The introduction section briefly describes the project, its aims and the purpose of the survey. Additionally, users of the questionnaire are presented with the GDPR statement of the STARS survey. The GDPR statement explains in detail the reasons for collecting the data of the SMEs, how this data is going to be used and by whom and how it will be stored. Users of the survey are also requested to accept and comply with the privacy statement.

As of 27 June 2022, 128 enterprises had answered the survey. After filtering out those outside the scope, a sample of 106 SME companies working or wishing to work in the Railway and Multimodality sector and located in the COSME countries was obtained.

3.2 Questionnaire structure and deployment process

The main section of the STARS survey questionnaire is focused on the evaluation of the status, the needs and the obstacles faced by the SMEs and is structured in the following sections:

• Digitalisation Level – SME’s Today’s Picture. This section contained questions aiming to capture the current level of digitalisation of the SME, the currency of advanced technologies they were using or exposed to and their approach and barriers to digitalisation.

• Strategy and Vision. This section attempted to capture the digitalisation needs and priorities, as well as the digital transition and green transition strategies of the SMEs.

• Future implementation of technologies. In this section, SMEs were requested to specify the expected future degree of use for the advanced technologies in their enterprise.

• Innovate for the Market. In this section, SMEs provided information regarding their obstacles and drivers for innovation in the market.

The process of deploying the survey, result collection and analysis included the following steps: (1) a requirement analysis and specifications for the survey itself, (2) an analysis of the available survey platforms and tools in order to select the most suitable one, (3) an iterative design and authoring of the survey in collaboration with the partners of the STARS consortium, (4) dissemination of the survey through the partner network, (5) initial analysis and classification of the answers data, (6) feedback on the analysis of the answers by the focus groups at regional level and (7) final version of the analysis and grouping of SMEs.

The methodology used for designing and running the survey as well as for the analysis of the answers received can be summarised as shown in Figure 1.

Figure 1.

Survey design methodology and timeline.

The survey was made available online on the 8 February 2022.

The design of the survey was an iterative process between STARS consortium members as well as external experts of the Advisory Group and the supporting Digital Innovation Hubs.

The Advisory Group consists of experts from the STARS consortium, as well as external experts from European initiatives that have committed through the signature of Letters of Support and other relevant European organisations that have been invited to become part of it (IoT4Industry Partnership, ECSO, EU Blockchain Observatory & Forum, EuroXR, ADMA and others). The role of all the entities involved in the development of the survey was to provide advice on how to structure the initial survey to SMEs and how to analyse its results.

In order to better understand the current industrial meta-ecosystem, similar questions to EU statistics were used, such as the EU Flash Eurobarometer 486 “SMEs, start-ups, scale-ups and entrepreneurship”.

A first analysis of the early results took place in March by querying the database of the survey and producing statistics on the answers data.

For the purposes of the analysis and classification of the answers of the survey, we have followed the following workflow consisting of three phases:

1. Realisation of a descriptive analysis of raw data. This provided a complete picture of the survey and also provided some trends.

2. Cleaning up and transformation of data to extract knowledge from raw data

3. Data analysis computation

Cleaning consisted of: (1) deleting blank rows, that is, respondents who did not accept the analysing of their data, or all respondent who were not in the scope of the project, (2) dividing multiple choice questions into binary statements, (3) transforming scale text responses into numerical scales, (4) changing fraction to decimal and (5) replacing null answers by mean values.

After the import and cleaning of raw data, some statistics and more complex calculations were carried out: mean values by countries and classification and clustering.

The data analysis step of the workflow following the steps of data cleaning and data transformation includes the execution of an analysis algorithm that computes the distances of SMEs based on their answers and groups them accordingly. The results of both analyses are explained in detail in Section 4 of this document.

4. Results

The collected sample of SME data presents an almost balanced distribution with a third of micro enterprises (35), a third of small enterprises (49) and a third of medium enterprises (35).

Respondents were segmented as shown in Figure 2 through the different area of the railway domain.

Figure 2.

Areas of the railway domain that the SMEs are operating or planning to operate.

The top three places were engineering, supplies and manufacturing in rolling stock and the design and manufacturing of control command signalling. However, all segments were practically well represented in the sample, with a balanced distribution. Construction works and Infrastructure facilities were the least represented among the respondents.

4.1 Trends on today’s picture about use of technologies

In terms of respondents’ approach to digital technologies, almost 48.5% of companies said that they need to introduce advanced digital technologies, and they had already started to adopt technologies. However, it was found that around 50% of them had not yet reached this point. Of these, 30% were considering adoption, although 10% of them do not have the necessary skills or financial resources to do so. The remaining 20% think that they do not need to adopt any advanced technology.

As can be seen in Figure 3, there are many barriers to digitalisation. Financial resources are the main obstacle to adopting digital technologies, followed by technical risks such as security or standardisation. The lack of skills is also considered a barrier to digitalisation; however, it can be assumed that there is a linkage with the lack of resources (See Figure 4).

Figure 3.

Enterprises’ approach to digital technologies.

Figure 4.

Barriers to digitalisation in the enterprises.

In order to analyse the actual state of technology adoption, the survey asked about the level of adoption for a number of new digital technologies. As can be seen in Figure 5 and Figure 6, the majority of respondents had heard about the majority of the technologies identified but did not use them. The less-known digital technology was photonics and the best-known connectivity, cloud computing, internet of things and cybersecurity.

Figure 5.

Advanced technologies used by the enterprises.

Figure 6.

Levels of knowledge of each of the technologies in the companies.

All the identified advanced technologies can be implemented in different business areas and processes. According to Figure 7, analysis of operations-related data and analysis of machine or device data are the two areas where technologies are the most needed and implemented according to the survey responses, followed by support services/products innovation. The Railway and Multimodal sectors seem to have less interest in data analysis of online customer behaviour or in technologies that could ensure warranty management and service execution.

Figure 7.

Areas in which the companies implement technologies.

However, as can be seen in Figure 8, the SMEs prefer customised solutions, and while in 14% of the cases, solutions are used in their entirety, in almost 20% of cases, future needs are taken into account in a specific solution, and for 15% of respondents, solutions are fully specific and integrated in the complete production process.

Figure 8.

Advanced technologies sources implementation in the companies.

In terms of maintenance strategy (see Figure 9), the majority of the respondents (80%) apply predictive maintenance, while less than 10% rely solely on reactive maintenance (10% answered that they do not apply any maintenance strategy at all). 30% of companies follow fixed time schedules to ensure maintenance plan, while some (19%) manage it according to the use of current technology.

Figure 9.

Maintenance strategy of advanced technologies and tools.

Regarding the use of standards and digital tools to ensure the security and quality of production processes in the companies, 68% of them stated that they were applying engineering standards for products, processes and services and that they relied on digital means in order to ensure at least one of the following requirements: reliability, security or predictability. However, 20% of the answers were negative to the question.

Only 28% of enterprises collected data from sensors or machinery to monitor production and infrastructure. As for cybersecurity, it is fairly well considered (92%), in half of the cases, only by IT departments, but in the other half, in all areas of the company. In this last case, in 70%, cybersecurity standards and tools are installed and maintained internally by the company’s cybersecurity team, while in the other 30%, cybersecurity is outsourced.

4.2 Strategy and vision

After collecting information on the current status of the implementation of digital technologies, it can be seen whether companies have a clear vision of their needs and how they could become more competitive by adopting technologies.

It was found that most companies have identified their technology needs; one-third of them have identified possible use cases that require the adoption of one or more advanced technologies but had not yet implemented them, and another third had not yet identified use cases.

In terms of priorities for the use of advanced technologies by companies, the most prominent would be the optimisation of operations, the development of innovative features in existing products/services and the development of entirely new products/services. There is no clear ranking across the board; each of these three needs seems to be considered of equal priority; however, the development of innovative features has a small lead in preference, followed by optimisation and thirdly by the development of new products or services.

A small majority of respondents do not have a clear digitalisation strategy; almost all of those who do have a clear digitalisation strategy have a time horizon of at least 2 years, and a considerable part of them even have more than 3 years in their time horizon (see Figure 10).

Figure 10.

Time horizon for delivering the strategy.

In the case of investment policies, 50% focus on the cases of the replacement of obsolete machines or software. However, the other half of the SMEs are less advanced in their investment: 13% have plans for a state of the art; 14% have a road map that includes the evaluation of new technologies through feasibility studies, and 17% have a road map that includes a research and development approach for advance relevant technologies to higher maturity levels.

Location of the SMEs	Has your enterprise already identified its development needs and how to address them?	Using advanced technologies to optimise my enterprise’s operations (e.g., manufacturing process, supply chain management, relations with customers, staff management, etc.)	Using advanced technologies to develop innovative features in my current products/services	Using advanced technologies to develop brand-new products-services	Has your enterprise adopted a clear Digitalisation Transition Strategy?	Do you have an investment policy that matches your Digital Transition Strategy?		SUM by country
Austria	2.25	1.25	2.50	2.25	0.00	1.50		11.85
Belgium	2.33	2.33	2.33	2.22	0.44	3.11		14.61
France	2.29	2.29	2.00	2.43	0.71	2.86		14.60
Germany	2.10	2.50	2.40	1.80	0.30	2.30		13.67
Italy	2.08	2.33	2.38	2.29	0.50	2.29		13.92
Serbia	2.00	2.40	2.40	2.60	0.40	2.60		14.66
Slovenia	2.00	3.00	3.00	1.00	0.00	2.00		13.10
Spain	2.17	2.28	2.28	2.33	0.39	2.67		14.11
Türkiye	2.13	2.20	2.47	2.33	0.53	3.13		15.04
United Kingdom	2.23	2.15	2.46	2.31	0.08	2.77		14.16

Looking at each country’s average about innovation strategies (see figure table above), the results are balanced, and all countries seem to have identified their needs.

In terms of green transition, almost 65% of respondents said that there is not a clear transition strategy in their company. Respondents rated the different areas to which they aim to contribute to make the railway and multimodality sector greener as below (the score in parentheses represents the average obtained by each item proposed).

• Energy consumption (4.11/5)

• Material (3.87/5)

• Waste (3.85/5)

• Hazardous (3.48/5)

• Noise and vibration (3.39/5)

• GHC emissions (3.36/5)

• Land use, biodiversity (3.13/5)

In order to analyse the companies’ contribution to a greener rail and multimodal sector, a list of related actions was proposed. This showed that 51% of the companies already implement a strategy to reduce energy consumption and that recycling and the use of more sustainable and advanced materials are also strategies implemented by almost 40% of the respondents, as well as waste reduction. Other avenues proposed were new ways of working, such as hybrid and home working, the production and use of renewable energy or the use of IoT and data analytics for a more robust engineering process (see Figure 11).

Figure 11.

Contributions of the companies.

Despite all these achievements, a big majority of respondents were not compliant with standards or certification, even if 75% of them intended to apply in the future, and 13% had a clear deadline for achieving a targeted eco-efficiency level. Only 12% already had a low footprint certification or a green transition standard like ISO (9001, 14,000, 14,001, 45,001), SA80003, EMAS4 and ECOVADIS5.

Finally, half of the SMEs do not advertise about this point, and from the other half, only 12% follow a specific communication strategy. For the rest, communication is summed up to non-professional advertising or reference on product/services or on websites or social media (see Figure 12).

Figure 12.

Enterprises advertising green products/services.

4.3 View on future implementation of technologies

After understanding the actual state of implementation of technologies and the strategic vision for the coming years, SMEs were asked about the advanced technologies they expect to use in the future and the degrees of each of them (see Figure 13).

Figure 13.

Expected future degree of use of the advanced technologies in the companies.

As we can see in Figure 13, on the one hand, there are advanced technologies which are clearly already implemented or will be in the short term (less than one year). It is the case for internet of things (IoT)/edge computing, connectivity (fixed, mobile), cloud computing and cybersecurity. On the other hand, there are some technologies that seem to be less appealing for SMEs to be implemented, according to those who have answered the survey: blockchain, advanced materials, photonics, nanotechnology, advanced manufacturing technologies, micro- and nanoelectronics and, to a lesser extent, augmented/virtual reality (AR/VR). Big data and analytics and artificial intelligence (AI) will take at least 2 years to be deployed, but they are of interest for the companies.

The main risks or obstacles when fostering innovation in the railway and multimodality market are: regulatory aspects, legacy technologies, internal lack of economic resources for investments, no innovation demand in my market segment clients with low digital capacities.

5. Conclusions and future work

The rail sector is one of the most energy-efficient modes of transport, but being responsible for only 9% of passenger transport and 7% of freight transport, it needs to increase its competitiveness and further reduce its carbon footprint. One way of achieving these goals is by the uptake of advanced technologies for boosting digitalisation and green transition of SMEs’ industrial processes. This chapter presents the work of surveying the technological needs of the SMEs in the domain and their classification and grouping according to those needs. The results of this survey will be the basis of our future work, for advocating the appropriate technologies to the SME groups, the business areas to focus and identifying the use cases and technological solutions for each SME.

Acknowledgments

We thank respondents who provided insight through the online survey and gave us the opportunity to analyse the results offering conclusions.

Funding

This work has received funding from the European Union’s Competitiveness of Small and Medium-Sized Enterprises (COSME) programme in the context of the STARS project under the Grant Agreement number: 101037897 — STARS — COS-STRAT-2020-3-05.

Availability of data and material

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.