## 2 Methods  
### Literature Review  
Group technology (GT) is an approach of production management, in which part families are formed from a plurality of various parts that are manufactured in a treated production system and that use the same group of machines to be transformed from an input material into the required final shape and property of the product.  
The methods designed to search families of parts and the group of machines they belong to are treated in the literature as cell formation techniques. Based on a proposal of various authors [PERSON] et al. [14] proposes the following overview of the cell formation technique:  
1. Descriptive procedures (part family identification, machine group identification, part families/machine grouping simultaneously);
2. Cluster analysis;
3. Graph partitioning;Artificial intelligence;
* Mathematical programming (linear programming, linear and quadratic integer programming, dynamic programming, goal programming).  
Descriptive procedures part families/machine grouping were first represented by [PERSON] as a Production flow analysis [15]. [PERSON] et al. [16] extended the [PERSON]'s production flow analysis and called it the extended production flow analysis. The extended material flow analysis included two steps:  
1. Macroanalysis is analysing the material flow (flow of parts) on a macro level, i.e., between departments of a company. The goals of these analysis were: identification of extra paths between the departments of the company and their elimination (usually by changing a technological method) and determination of a standard material flow between the departments of the company.
2. Microanalysis is included in a material flow analysis within an individual department. The goals of this analysis were: simultaneous identification of part families and groups of needed machines for their manufacturing and formation of production cells for the part families. A cluster analysis method and an incidence matrix method were proposed for the formation of cells.  
[PERSON] et al. [17] propose, in particular, metaheuristic techniques such as: genetic algorithm, artificial neural networks, fuzzy set theory, colony systems, tabu search, branch and bound method, simulated annealing.  
Nowadays, the goals of group technology and formation of various shapes of production systems (cells) need to be connected, especially with the goals of leanness, flexibility and agility of production. Due to market demands, a large number of different, yet mutually similar parts appear in the production process. That means that the production program contains a large number of different products that are similar to each other, as the companies emphasizes the possibility of making a tailored products for each customer to maintain its competitiveness in global markets. It is quite common in smaller companies that the record of material flow has never been made. They simply lack the time and the human resources, while trying to maintain acceptable production and make profit. With time and production line updates, the layout becomes increasingly non-optimal and the diversity of products only increases this problem.  
So, it is not reasonable to analyse a material flow and a value flow on the entire amount of available data. Within thousands of pieces, representative parts (hereinafter representative elements) need to be selected. This is made possible by the methodology for searching representative elements, MIRE, which can relatively quickly give us a sufficient approximation of the material flow, which serves as the basis and the first step towards lean production, consequently increasing the company's competitiveness in the global market.  
The methodology is most suitable for smaller companies that throughout their growth and development simply did not have the time, resources and competences to create a material flow inventory because their priorities were mainly focused on delivering the products and keeping up to date with the latest technological trends.