The study identifies critical factors influencing companies’ operational and sustainability performance utilising fluid power systems. Firstly, the study performs Machine Learning (ML) modelling using variables extracted from survey instruments in the West Balkan region. The dataset comprises 115 companies (38.75% response rate). The survey data consist of 22 predictors, including meta-data and three target variables. The K-Nearest Neighbours algorithm offers the highest predictive accuracy compared to the other seven ML models, including Ridge Regression, Support Vector Regression, and ElasticNet Regression. Next, using a model-agnostic interpretation, we assess feature importance using mean dropout loss. After extracting the most essential features, we test hypotheses to understand individual variables’ local and global interpretation of maintenance performance metrics. The findings suggest that Failure Analysis Personnel, data analytics, and the usage of advanced technological solutions significantly impact the availability and sustainability of these systems.

The goal of each company today is to improve business and increase profit through the reorganization and simplification of its processes, decrease of costs and resources utilization etc. Improving the business is usually implemented...

Despite nearly two centuries of efforts by scientists and engineers to enhance the efficiency of production processes, today's production processes continue to be inefficient and wasteful. As the production process's complexity increases, the working...

This study is aimed to assess the organisational competitiveness, and readiness of our economy to compete in the open market, after accession to European Union. The concept of organisational competitiveness and business excellence is discussed and viewed through the implementation of LEAN practices. To assess the maturity of LEAN, over 200 organisations from various industries were included into the survey design. The questionnaire was used as a research instrument. In order to avoid the negative effect of a superior competition, it is necessary to help our organizations to reduce the difference between them and their main competitors in the European Union. The first step in a situation like this, has always been establishing the points of greatest differences and vulnerabilities of our economic organizations. The study shows the lack of awareness about some LEAN drivers. Such shortcomings might negatively impact the competitiveness of our economy, due to the fact that many of EU companies are heavily oriented towards the implementation of key LEAN concepts