SAFETY CONFORMITY PREDICTION FOR A BOTTLING PROCESS PLANT: A MULTIPLE REGRESSION APPROACH

Abstract

Safety conformity is an industrial practice to obtain enhanced safety performance and improved worker-management-government relationships. In this paper, a novel method to model and predict the conformity of bottling process operations and activities to safety rules and accident prevention is presented. Inspired by the machine guarding literature in safety compliance, this research extends the regression model beyond the machine operations domain, to cover activities in beverage testing unit (BTU), shuttle vehicle flotilla (SVF), stockroom, and suppliers. Data from practice in a bottling plant in Nigeria demonstrates the model's effectiveness. The coefficients of determination (R2 = 0.8454, 0.3891, 0.8156, 1 and 0.8156), showed the predictive competence of the warehousing, manufacturing hallway (MH), BTU, SVF, and suppliers' variables, respectively. These R2 values were derived from computations and tabulated by the software program used, and BTU and suppliers' values for R2 were obtained as the same from the program software. The relative importance of the bottling segmental factors was evaluated through ANOVA. The bottling process data results revealed the most significant variables at (p<0.05; calculated probability). This insight offers safety managers with useful practice information to plan and control.