Model-Based Dynamic Categorization of Alarm Trip Points for Manufacturing Process Disruption Minimization

Abstract

ABSTRACT Faults in manufacturing processes can cause disruptions and downtime, which adversely affects process efficiency and increases production costs. Process downtime can be reduced by monitoring manufacturing processes for faults, categorizing those faults, and prioritizing action. A new approach is proposed for minimizing function downtime, which involves monitoring system faults and generating a system response depending upon the status of the individual workstations in the manufacturing process line. The proposed model dynamically categorizes the faults considering the fault repair time, the weightage assigned to each workstation, and the process status, i.e. idle or running. The proposed model generates the threshold values for setting up trip points and categorizes critical faults into low, medium, and high values. The proposed model is tested using software simulations and an experimental test rig, and the results demonstrate that it can significantly reduce downtime in manufacturing processes. The model has been successfully implemented on a test rig and Asphalt manufacturing plant. In the test rig, 12% improvement is seen while on the Asphalt plant, 60% reduction is noticed in terms of start/ stops incidents, 60 minutes in downtime, and 800 kg of a valuable processed batch is saved in one week.