Production lines are usually subjected to emergent machine failures. Such emergent failures disrupt pre-established maintenance schedules, which challenge maintenance engineers to react to those failures in real time. This research proposes an optimization procedure for optimizing scheduling repairs of emergent failures. Three optimization models are developed. Model I schedules failures in newly idle repair shops with the objective of maximizing the number of scheduled repairs. Model II maximizes the number of assigned repairs to untapped ranges. Model III maximizes both the number of assigned failure repairs and satisfaction on regular and emergency repairs by resequencing regular and emergent failures in the shop that contains the largest free margin. A real case study is provided to illustrate the proposed optimization procedure. Results reveal that the proposed models efficiently scheduled and sequenced emergent failures in the idle maintenance shops, the untapped ranges between repairs of regular failures, and in the maintenance shop with the largest free margin. In conclusions, the proposed models can greatly support maintenance engineers in planning repairs under unexpected failures.
This research aims at identifying the appropriate lean and/or agile practice(s) to improve the performance of filling process in a pharmaceutical industry. Initially, the As-Is simulation model of production processes was built and then run to estimate the process's output measures; averages of input bottle, work in process, waiting time, cycle time, and output bottles. The simulation results showed overall equipment effectiveness (OEE) score for some production processes were smaller than the recommended minimum world-class values. Consequently, agile and/or lean practices were utilized to generate nine To-Be improvement scenarios. Simulation was run to evaluate the process's output measures and OEE score for each scenario. Finally, the slack based model (SBM) in data envelopment analysis was adopted to determine the best improvement alternative. The SBM results revealed that the lean practice "adding another head to the labeler machine" is the best alternative that may result in anticipated improvement in the OEE by 13.5%. In conclusion, the lean and/or agile practices can result in significant savings in production and quality costs.
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