PERFORMANCE EVALUATION AND OPTIMIZATION OF PRODUCTION SYSTEM IN AB BREWERIES

SOURCE:

Faculty: Engineering
Department: Industrial And Production Engineering

CONTRIBUTORS:

Ujam, C. J.
Godwin, H. C.

ABSTRACT:

Current increase in product demands and new products brands to market make breweries struggle to meet their daily demands with the existing production capacities. Investing in new production system requires huge capital expenditure and the alternative is to increase production output with the existing production capacities. To achieve this, the evaluation and optimization of production performance and maintenance strategy must be a topmost priority Production process performance data were collected and analyzed with correlation, Pareto and Root cause to determine the degree of inefficiencies, bottlenecks and area of focus. Thereafter, conceptual experimental model was built with Tecnomatrix Plant Simulation Software from the current system sensor speeds. CILT and Kaizen strategies were applied to optimize preventive maintenance of the optimized system. Finally, an excel spreadsheet interface was developed as a tool for easy data analysis and performance tracking. In the results, Filler (core machine) has upstream and downstream machines around it with continuous increase in production capacities to cope with failures. The correlation analyses of production running time with production output of lines were positive. In Pareto Analysis, materials and machine breakdown on EBI, Filler, Labeller, Pasteurizer and Washer were major causes of downtime. OPI of production outputs of Line 1, 2 & 4 recorded 57.9%, 71.3% and 26.7%, respectively with target of 61%. In conceptual model, Line 1 & 2 were regulated lines, while unregulated Line 4 has OPI of 26.7%, far below the target. Speed levels of sensors were not optimized, which affected the production speed, balance and output in line 2. Finally, design of experiments was carried out by adjusting the speed levels of 6 sensors selected out of 17 sensors in 12 experimental runs and experiment 6 was selected as the optimal result. From the result, the average output before and after modifications for CPL 111 and CPL 112 were 57%, 43% and 52%, 48% with output of 420,193 and 447,480 bottles per 8 hours shift respectively. The production output gain after the modification was 27,287 bottles per 8 hours shift, while production imbalance was reduced from 14% to 10% for the two labellers, starvation reduced from 67.85% to 30.62% and failure from 3.07% to 1.46% .CILT activities was reduced from 20 to 10 minutes per shift. Data analysis and performance tracking were achieved by the developed excel interface.