Artificial Intelligence Based Model to Predict Labour Productivity for Small & Medium Scale Bus Body Building Society in Present and Post Pandemic Situation

Abstract

In the recession, the lack of potential labour was the most important concern for the small- and medium-scale bus body fabrication industries. In the pandemic covid-19 situation, the productivity of these fabrication industries was turndown due to deprivation of labour productivity, postponement of work and cost overshoot, which may pilot to argue. In India, Central Tamil Nadu fabrication industries are buttress by immense labour intensity. In this panic situation, these industries are struggling to obtain better productivity. Diversity of earlier works on the detection of the factors with the intention of impacting labour productivity in structural industries and manufacturing sectors has been carried out by research in many countries. Nevertheless, those attempt characteristics are restricted to credentials and implemented in subjective techniques for analysis in declining bus body fabrication sectors. Ambition of this particular research is to recommend an artificial intelligence-based model to predict the “uncertainty factors” influencing labour productivity and safety performance of bus body fabrication industries related to small and medium scale in the pandemic and post pandemic situation.

Developing management policies and analyzing impact of change orders on labor productivity in construction projects

“…The base model used for the current study was taken from the system dynamics model validated by Taylor and Ford, (2006, 2008) for workflows for a single project system. This model has been used for a number of studies to analyze the impact of tipping points on project performance (Taylor and Ford, 2006; Xu and Zou, 2020), to manage tipping point dynamics in projects (Taylor and Ford, 2008) and to investigate the impact of project controls on project performance (Nagarajan et al , 2020). For this study, the model was expanded to include the direct and indirect effects of change orders on project performance.…”