Optimization of Printing Press Operations
Journal Title: IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) - Year 2018, Vol 15, Issue 2
Abstract
Printing technology has seen technological advances in the field of automation because it is a very dynamic and innovative process. A good printing factory layout maximizes production with minimum investment in new equipment. However, a good factory layout alone cannot achieve the intended objectives unless tightly coupled with production process monitoring and improvement which entails monitoring of Overall Equipment Effectiveness (OEE) to pinpoint areas of production losses and identify areas of performance improvements.This research focused on carrying out a process and facility layout analysis with the aim of identifying gaps, bottlenecks and challenges in productivity that contributed to poor production throughput and to redesign the layout and optimize the production capacity. Input variables considered were: number of departments, flow matrix, floor area for each machine, design speed, actual speed, losses and rate of failure. Output variables were: dual graph and layout proposition, availability, performance, Quality, OEE.The facility layout add-in that implements the Computerized Relative Allocation of Resources (CRAFT) was used for layout redesign. ARENA was used, for the design of experiment (DoE), simulation, analysis, and optimization. Pareto chart was developed using Minitab statistical software. ThePareto analysis established that 69.6% of the distance covered was taken up by movement between machine and store and 78.2 % of the print volume was taken up by threeprinting machines, (Web, Print master and Speed master). Failures, breakdowns and setup times were found to have a less significant effect on the performance and hence OEE of the factory. The quality of paper affected breakdowns for the web whereas run speed significantly influenced the overall performance and OEE. The optimal conditions obtained at about 80% of design speed of each machine that gave OEE of 79% for 3 critical machines and 68% for all five printing machines (only three machines were considered for optimization). Experimental output values obtained during validation were Web printer at 130,000 runs per day (without auto- splicing), Printer master (PM) and Speed master(SM) printers at 70,000 each at runs per day. These results were closer to the software results since some changes in storage location and automation were not yet put in place.
Authors and Affiliations
Moses B. Kataka, Jean B. Byiringiro, Peter N. Muchiri
Keywords
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