# Improving the Production Efficiency Based on Algorithmization of the Planning Process
## 4 Research Results
### Basic Algorithm Development
* If the missing product has been fully produced, the algorithm will check for other products their missing amounts. * If nothing else is missing, this product (with priority no. 1) is produced until the end of the production day, which means by 6:00 am the next day. * If another product is missing (product with priority no. 2), this product can be produced. The algorithm will still check if it can be produced by the end of the day--whether there is enough time. If there is not enough time to produce the entire volume, then the algorithm evaluates the missing unproduced quantity and evaluates a warning alarm, that production capacity is not sufficient to satisfy the customer's plan. The algorithm was applied within the SW module for production planning. An example of the algorithm part is shown in Figure 2.  
IMPROVE and CONTROL: Based on the previous analysis, an algorithm was compiled that proposes a production plan for the entire current week according to the agreed logic. There are dynamic inputs at its input, which change with each use--the current stock is used here, the production plan of the customer company, and the current production program, which tells which product is being produced. Due to the findings that the algorithms based on variants I and II could in certain cases critically endanger the supply of JIT parts to the customer, the algorithm based on variant III were chosen, which clearly states that after the end of production of missing parts for the day, production continues until the next day, when the line stops and reconfigures as needed. After creating the algorithm, a test phase was started, where the solution was tested for a certain period. The recorded results from previous production cycles and the new outputs achieved using the planning algorithm were compared. The result is that thanks to the use of automatic production planning it is possible to save at least 1 production line per week, which means saving at least 2% of production capacity (Table 2). This is a great result, as this saved capacity means the production of \(\sim\)120 pieces of the product in addition to the previous solution. The graphical representation of the algorithm is in Figure 3.  
Figure 2: The part of the planning algorithm—production prioritizing. Figure 3: Graphical representation of a general planning algorithm. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Manual Planning** & **Automatic Planning** & **Unit** \\ \hline Count of reconfigurations & 23 & 21 & \\ \hline Time of reconfigurations & 2760 & 2520 & minutes \\ \hline Production time & 11,640 & 11,880 & minutes \\ \hline Count of products made & 11,640 & 11,880 & pieces \\ \hline Number of NOK pieces & 61 & 62 & pieces \\ \hline Line productivity & 83 & 85 & \% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The results of of production capacity. Generalization of the Algorithm for Use in Companies with Similar Production and Planning Conditions  
The algorithm is generally written to be applicable to most companies that are engaged in mass production (Figure 3). It is currently designed to take into account handwritten input data that is drawn from the report and therefore does not work in real-time. The usability is for one production line, in the future it is planned to finalize calculations for more lines on which it is possible to produce the same products. Once this functionality is complete, it will be possible to use it in the vast majority of companies that produce on a mass production basis.