# A Framework for Assessing Manufacturing SMEs Industry 4.0 Maturity
## 1 Introduction  
The overwhelming majority (99.8%) of enterprises active within the EU 28\({}^{\prime}\)s non-financial business economy in 2015 were SMEs [1]. In the same year, these types of companies represented a share of 55.6% of the total gross added value of that same economy [1]. In 2017, Portuguese SMEs accounted for over two thirds of their economy's overall added value [1]. In countries like Germany, where the added value of SMEs is lower than the European average, these types of companies still account for more than half of their economy's overall added value [1]. SMEs are indispensable to all economies and can be described as a driving force for businesses, growth, innovation, and competitiveness, all while being a very important employer [2]. Society is currently undergoing an industrial revolution that goes by the name of The Fourth Industrial Revolution [3]. There is an urge for companies to take part in it as fast as possible in order to benefit from the competitive advantages and lead the way [4]-or at least, not to get left behind. This worldwide industrial revolution can be witnessed in different forms and initiatives, for example, the World Economic Forum has been succeeding in raising awareness of the impact of digital transformation in more than 220 organization across the globe [5]. This and other initiatives are paramount for this revolution's development and establishment, as it will bring multiple benefits for individual firms, whole supply chains, the industrial sector as well as for the society itself [6; 7; 8; 9]. Although the adoption of Industry 4.0 (I4.0) and its components seems unavoidable in the long run, there are several struggles that prevent companies from promptly embracing this paradigm shift [3; 4; 9]. A survey conducted with a German equipment manufacturing association (VDMA) (Verband Deutscher Maschinen- und Anlagenbau) members postulates that I4.0 readiness increases sharply with the size of the company [3], suggesting that SMEs have an especially a hard time when it comes to approaching this concept. Infact, years later, [PERSON] et al. identified the size of a company as a critical factor to understanding the process of adopting new manufacturing technologies [10]. The typical owner(s)-centered or family-owned organization and the limited financial budget of SMEs are some of the barriers that stymie these enterprises' position in the I.40 maturity ladder. Since its presentation, I.4.0 has been a popular subject in the research environment, and [11; 12] separate it into eight different topics: big data and analytics; autonomous robots; simulation; horizontal and vertical system integration; the industrial internet of things; cyber security; additive manufacturing; and augmented reality and the cloud. Within these topics, there are already various tools to aid in the involvement of companies in I.4.0, but a tool for a systematic approach that predicts a company's hurdles in implementing I.4.0 was not found to exist nor found to be in development. Additionally, the existing tools essentially focused on advanced technologies and occasionally on specific areas of this concept such as, technology or processes. Therefore, none of these tools were found to be broad enough to comprehend the whole concept of I.4.0, nor did they have enough granularity in the initial maturity levels--which is paramount for the accurate maturity assessment for SMEs [13]. Based on the work of [PERSON] et al. [14], the main objective of the presented research is thus the development of a specialized I.4.0 maturity model tailored to SMEs that encompasses \"level 0\". In their work, [PERSON] et al. defend that \"_defining a level 0 for SMEs is a necessary starting point to elevate their position along both the short- and long-terms_\". Our proposed maturity model represents symbolizes this \"starting point\" [14]). The proposed model aids SMEs who are transitioning to I.4.0 by creating a framework that combines different I.4.0 dimensions with existing maturity models.