## 4 Discussion
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Knowledge Base** & **Applied H.0 Technologies** & **Decision Support Regarding Automatic Completion of Customised Orders** \\ \hline
[6] & Parameters of a personalised product & Artificial Intelligence tools & Giving the opportunity to move the production process into distribution, which means increasing the possibility of the individualisation of supplied products \\ \hline
[7] & Centralised storage of data and their processing, and communication or transfer of information & Cloud technologies & Allowing for checking availability and the feasibility of customer orders by allowing machines to communicate with each other in order to deliver personalised products as quickly as possible while supporting the customisation of products by centralising management \\ \hline
[8] & Collected data directly from sold products & Artificial Intelligence tools & Forecasting and planning the demand for products \\ \hline
[24] & Centralised storage of data and their processing, and communication or transfer of information & Internet of Things & Various electronic devices are connected to the global network and can exchange data regarding customer preferences and can optimise the production process with each other without human intervention \\ \hline
[25] & Data about the order and the production process & Blockchain and Internet of Things & Decision support mechanism for customers, and data persistence, traceability, transparency, and reliability \\ \hline
[26] & Information on customer specifications and data from the production process & Blockchain & Generating a plan for mass-customised production systems to fulfil the demand, deepening the interoperability of the system \\ \hline
[27] & Data about manufacturers, suppliers, and consumers & Blockchain, big data, Cloud computing, Artificial Intelligence tools, and Internet of Things & Data flow between consumption and production allowing flexibility between manufacturing resources and the mass-customised production processes \\ \hline
[28] & Engineering characteristics definition and customer requirements & Big data and a Kano questionnaire optimisation function & Quick response product configuration system \\ \hline This article & Customer preferences, integrated specialist & ERP systems, Natural Language Processing, rules for converting specialist knowledge, and an algorithm for the automatic completion of orders & Attendance in verifying the feasibility of the order tailored to the needs of the customer in relation to the production capacity of the company and the parameters of the raw materials used for mass-customisation production \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comprising the proposed approach from existing related works. available in the enterprise's ERP system and specialist knowledge. For this purpose, a knowledge base for a cyber-physical system was built, rules were developed to generate individual customer orders, and a cyber-physical system was applied for an exemplary real mattress-manufacturing company. In our case study, the following further directions for our work are indicated. It would be possible to create another group of products already delivered to the customer, to which changes could be introduced. These changes would provide information for more satisfactory and optimal implementation of similar future orders. One of them would include articles where configuration changes could be made, taking into account possible customer complaints. The second one would concern products, the configuration of which could be changed in terms of, for example, the technological efficiency of the assembly by analysing the perceptions of employees participating in the production process. The application can also be extended with other groups of personalised products that COWAN Textiles GmbH offers to its customers, especially the seats of motorhomes.