Total machine assessment of transport equipment manufacturing systems by principle component analysis

This paper presents a framework for assessment and ranking of transport equipment manufacturing systems based on machine productivity indicators. The integrated approach discussed in this paper is based on principle component analysis (PCA). The validity of the model is verified and validated by numerical taxonomy (NT) approach. Furthermore, a non-parametric correlation method, namely, Spearman correlation experiment shows high level of correlation between the findings of PCA and NT. To achieve the objectives of this study, a comprehensive study was conducted to locate all economic and technical indicators (indexes) that influence machine performance. These indicators are related to machine productivity, efficiency, effectiveness and profitability. 10 indicators were identified as major indexes impacting machinery conditions in manufacturing systems. PCA ranks the transport equipment manufacturing sectors based on 10 indexes discussed in this paper. This in turn shows the weak and strong points of transport equipment manufacturing sector with respect to machine productivity. The modeling approach of this paper could be used for ranking and analysis of other sectors in particular or countries in general.