Original Date: 05/01/2000
Revision Date: 01/18/2007
Best Practice : Production Process Simulation
Previously, Northrop Grumman Defensive Systems Division (DSD) used various low-level tools to make production capacity and product mix decisions. Spreadsheet models assumed level-loaded tasks by using constant manpower throughout the production cycle. Fixed cycle times did not take into account resource availabilities. Equipment tended to be suboptimized which reduced the overall operation’s efficiency. Any gaps in information were filled in through management judgement and experience. As a result, these tools failed to realistically depict the true dynamics and interrelationships of the manufacturing processes. In 1992, the company resolved this situation by implementing simulation modeling software.
Simulation modeling allows system developers and analysts to predict the performance of existing or proposed systems under different configurations or operating policies. This process, carried out before the existing system is actually changed or the new system is built, minimizes the risk of unforeseen bottlenecks, under- or over-utilization of resources, and failure to meet specified system requirements. Northrop Grumman DSD uses its simulation capability to support equipment purchases; view the production impact of a changing product mix; analyze and reduce cycle times; review scheduling practices; select optimal lot sizes; analyze staffing needs; review factory layout changes; and assess just-in-time (JIT) methodologies. By using statistical distributions to define manufacturing variabilities, the company increases the validity of the simulations.
Advanced uses of the Production Process Simulation include data downloads involving inspection and test yields, non-labor related wait times, and weekly batch loading data from the Material Requirements Planning (MRP) system. Northrop Grumman DSD also created two large models: (1) a Shop Operations model with over 1,000 assembly variations, and (2) an MIC/Hybrid model containing more than 850 assemblies. By employing these models and Design of Experiment techniques, the company can perform sensitivity analyses to determine the impact of up to ten input factor changes.
Since implementing Production Process Simulation, Northrop Grumman DSD has completed more than 50 simulation modeling projects. Among the capabilities of this predictive tool are equipment justification, fine tuning of existing programs, future project requirements in resources and training, and layout improvements. In one case, the company used the modeling simulation to analyze its conversion plan for the non-ozone depleting chemical (ODC) cleaning of circuit card assemblies. The simulation showed that current and future production levels could be supported with just two Detrex batch cleaners. Prior to the simulation, Northrop Grumman DSD had planned on purchasing three or more batch cleaners. As a result, the company realized an avoidance cost of $100,000 in capital expenditures.
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