Effect of failure type on downtime duration for a manufacturing facility

Machinery infrastructure is usually prone to stoppage due to unexpected breakdowns. This paper analyzes possible failures root causes of manufacturing facilities, including machinery, to improve their performance. The research methodology utilizes a fact-driven statistical approach to investigate the statistical relationships between different affecting factors. These include failure modes, durations of downtime, working shifts, and products. Experimental designs models were employed in this paper, based on the analysis of variance (ANOVA) test and the Kruskal-Wallis test in combination with Tukey’s method for pairwise comparisons. ANOVA analysis identifies different downtime durations influenced by different types of failures. Similarly, the Kruskal-Wallis test results show that downtime durations are affected by different types of failures and not affected by different products and production lines. A case study was done on a dairy plant in Saudi Arabia where ten types of failures were identified. The results showed the top ranked failures to be finished product clearance, setup delay, raw material rejection, mechanical failure, and electrical failure. The findings help the management to develop learned lessons that help to minimize the cost and consequences of having frequent failures