## 3 Results  
The method was used to evaluate the maturity of 200 Polish manufacturing companies. The surveyed entities belonged to small- and medium-sized enterprises (SMEs) and operated in diverse sectors. These sectors included food, chemicals, textiles and clothing, electronics, machinery, wood and furniture, packaging, household appliance manufacturing, and suppliers of components to the automotive industry. SMEs are the largest employers and contribute the most to EU development. However, their development needs help accessing capital, external funding sources, modern technology, innovation, and a highly skilled workforce. A disruptive factor is more familiarity with modern process management methods. In each case, the company was classified into the described group based on fulfilling the following conditions: having less than 250 employees and an annual turnover of not less than EUR 50 million or an annual balance sheet total of not more than EUR 43 million. The participants who responded were individuals with managerial or decision-making positions in investment planning, corporate digital vision, and strategy creation. During the survey, we identified the current level of maturity in a key area and defined a target state for the next three years. Table 8 summarizes the study on initial and target maturity levels for automating production processes. In total, 38% of enterprises in the survey are at the KA1-ML1 maturity level, using conventional machinery. A total of 6% of enterprises plan to maintain the status quo due to the craft-based nature of operations and the need for more potential to automate production processes. Eighteen percent of respondents plan to use automated or numerically controlled machines at the KA1-ML2 level without implementing technological process robotization. Moreover, 14% of respondents at the KA1-ML1 level plan to implement automated machines or production lines operated by industrial robots. A total of 44% of the surveyed companies are at the second maturity level (KA1-ML2), indicating that they own automated or numerically controlled production machinery. In this case, manual quality control and support for auxiliary operations are used to identify machine failures or detuning. In total, 10% of respondents reported no change in their \begin{table}
\begin{tabular}{c c c} \hline \hline
**Area** & **Subarea** & **Application in the Proposed Method** \\ \hline \multirow{6}{*}{Social and environmental changes (A3)} & Global warming (A3.1) & Increasing the importance of informed machinery and equipment selection, considering extended service life, retrofitting options, and future integration into management systems, \\ \cline{2-3}  & The digitally connected society (A3.2) & Implementing employee-friendly technology to reduce information overload and increase comfort by generating clear and readable reports without significantly increasing employees’ workload, \\ \cline{2-3}  & Lifestyle and demographic changes (A3.3) & Application of flexible automation in processes with staff shortages, and the automation of monotonous and repetitive activities. \\ \hline \hline \end{tabular}
\end{table} 
Table 7: _Cont._ \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Maturity Level**} & \multirow{2}{*}{**Initial Maturity Level**} & \multicolumn{3}{c}{**Target Maturity Level**} \\ \cline{3-4}  & & **Maintaining the Current Level** & **Moving to the Next Level** \\ \hline KA1-ML1 & 38\% & 6\% & - \\ KA1-ML2 & 44\% & 10\% & 18\% \\ KA1-ML3 & 12\% & 2\% & 36\% \\ KA1-ML4 & 6\% & 6\% & 22\% \\ KA1-ML5 & - & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Summary survey of the initial and target maturity levels in automating production processes. achieved level, while 22% upgraded to KA1-ML3 by integrating industrial robots into their technology, assembly, and handling processes.