Development Of A Maintenance Strategy For Flour Milling Industry: A Case Study Of Corn Milling Industry In Kenya

Abstract

Good maintenance planning and proper resources scheduling in corn milling industry are of fundamental importance for safe and efficient operation of corn milling plants. This leads to production optimization due to reduced cost of operation. The interactions of aspects of plant safety and reliability with issues related to economic performance, such as production revenues, repair and maintenance costs, renders the problem of managing maintenance and repair activities highly complicated, especially for complex systems with many „interacting‟ components. Corn milling industries experience frequent shutdowns and lack of equipment optimization resulting to high operations and maintenance costs. This has been occasioned by over reliance on failure based maintenance policy with consequence of non-production during the period of down time or reduced through put due to sub-systems not running at full capacity. This has become a common occurrence on the production line equipment resulting to costly production operations. A case study field failure statistics for a 28 metric tonnes per day milling plant production line indicate that, 81 critical sub-system random failures were witnessed leading to total plant shutdown. This translated to 18,877 minutes per year in 2014 of production downtime with production down time cost of US$ 168,892.52, a huge cost that needs to be controlled by either minimising or entirely eliminating the unplanned frequent plant failures. Plant field failure data was systematically collected and analysed for condition parameters that affected the milling plant production process optimization directly or indirectly to establish criticality of failure in terms of failure frequencies, failure downtime and the corresponding failure downtime cost. Tools of reliability analysis for a failure risk based maintenance approach that included failure mode and effect analysis and Pareto analysis tools for failure modes identification, failure mode effects evaluation and failure mode risk prioritization were used. Root cause analysis through application of Ishikawa diagram and Pareto analysis tool were applied for failure root cause identification and failure cause prioritization. The research established that corn milling plants have priority sub-systems with critical failure modes whose failure consequence caused prolonged downtime and high downtime cost. The milling plant critical sub-systems that required close condition monitoring were ‘run to failure’ (RTF), a condition that necessitated the application of failure based maintenance policy to rectify the sub-system failure. This maintenance approach did not optimise maintenance function but instead led to failure effect characterised by unplanned prolonged downtime. Potential failure detection techniques and special service tools for sub-system condition monitoring and failure detection were not available for application in the milling industry. Lack of proper service schedules and adequate maintenance documentation affected the quality of plant maintenance. Based on this research, combination of various maintenance policies together with incorporation of maintenance expertise, special service tools, potential failure detection test methods and optimal maintenance procedures and schedules were found to be adequate for corn milling plants maintenance management optimization. In this work, the author developed an optimal maintenance strategy for corn milling industry that mitigates recurrent failures, thus optimizing milling plant production process. Moreover, this maintenance model or frame work developed in this research can be used to develop an optimal maintenance policy that can be applied in industrial set-ups that employ complex multi-functional systems and a decision tree used to aid the maintenance team and decision makers select the most appropriate and optimal maintenance policy.