An integrated simulation–optimization study for consolidating production lines in a configure-to-order production environment
This study investigates production lines consolidation in a configure-to-order production environment using simulation and optimization strategies. The current production environment has three separate production lines that will be consolidated into two production lines. Two production line configurations are analyzed: product and process layouts. Product layout has a continuous smooth flow, small work-in-process (WIP), short total production time per unit of product, and reduced material handling requirements. On the contrary, process layout offers more flexibility, allows for higher utilization of machines, and requires higher grades of operators’ skills. A simulation-based comparison of the current and future systems is conducted considering lead time, throughput, utilization, and WIP. A mixed integer programming model that optimizes the transportation cost and waiting time is then formulated based on the selected process layout. Simulation results provide recommendations to improve the system level performance measures and support management decisions. The current transportation schedule is ineffective, and hence a real-time dashboard based on the optimization model is suggested. The dashboard will improve communication and transportation between the two production lines.
Integrating data analytics and simulation for defect management in manufacturing environments
Defect management in manufacturing environments requires effective identification of the defects and finding proper solutions to resolve them. Predicting and preventing the defects before they can occur is the focus of quality risk management. To effectively manage defects, companies need to analyze historical data to identify the causes and solutions for defects as well as study the impact the defect can have on the processes, priorities, and operations. This study integrates data analytics and simulation modeling to develop a system for defect management in manufacturing environments. Simulation is used to analyze the behavior of the system whereas data analytics is used to develop prediction models for defect resolution. A case study from high-end server manufacturing environment, which is characterized by extensive test processes to ensure high quality and reliability of servers, is provided. The proposed approach helps decision makers analyze and manage defects and develop proactive means to prevent them.
Computer Simulation Modeling
Computer simulation as a research methodology is presented as the intersection of modeling, simulation, and computer analysis. Five component parts of simulation models are identified: input variables, output variables, assumptions, algorithms, and parameters. Computer simulation (CSM) has two primary uses for those interested in the study of organizations or who work within them: theory development and policy planning. The advantages and disadvantages of CSM for each of these purposes are examined and recent examples for each are explored.