Abstract Nowadays, industrial companies are constantly improving their processes and increasing their efficiency in order to achieve higher profits. One of the most common measures of efficiency at the semi-automatic… Click to show full abstract
Abstract Nowadays, industrial companies are constantly improving their processes and increasing their efficiency in order to achieve higher profits. One of the most common measures of efficiency at the semi-automatic assembly lines is the Overall Equipment Effectiveness (OEE) as a Key Performance Indicator (KPI). The goal of measurement of OEE is to improve the effectiveness of machines or production lines with minimal investments. The article presents a way to increase this indicator using an own hybrid analysis. Firstly, a literature review demonstrates scientific relevance. Secondly, a hybrid analysis is introduced for improving the efficiency. The effectiveness of the analysis is demonstrated by a practical example using data mining and line balancing, during which there was a 60% improvement in yield. Patterns recognitions by machine combined with human analysis provides this outstanding result. Hybrid analysis can be used not only on assembly lines, but also on individual machines where a lot of data is generated and the cycle time or takt time needs to be reduced for higher yields.
               
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