Quality Improvement, Inventory Management, Lead Time Reduction and Production Scheduling in High-Mix Manufacturing Environments
MIT Lincoln Laboratory Lexington United States
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This thesis is a compilation of the analysis and recommendations gathered from two industry projects conducted at Applied Materials Varian Division in Gloucester, MA and at the MIT Lincoln Laboratory in Lexington, MA. This thesis addresses the improvement of a quality metric used at Applied Materials through the means of material shortage reduction and lead time reduction of system sub-assemblies. Manufacturing quality was found to be impacted by material shortages across the facility and capacity constraints in an area of the facility that manufactures equipment subassemblies. Implementing a new inventory policy would result in an expected 74 to80 reduction in material shortage occurrences. The capacity increase recommended in this thesis would reduce average lead time for sub-assemblies from about 5-6 days to under 2 days. At the MIT Lincoln Lab, this thesis addresses a possible approach to improving the accuracy of production scheduling and delivery date quotes through the use of job shop scheduling software and historical data analysis. The recommended fabrication request delivery date prediction process involves using a scheduling software to find the optimal delivery date for a job, and then adding a Shop Capacity Buffer time that is calculated using historical data on schedule delays. Schedule delays can be caused by a variety of random events that occur in machine shops, such as machine failures or operators falling ill. By selecting a Shop Capacity Buffer of90, a 90 on-time completion rate should be observed. This new method would achieve improved results from the 75 on-time completion rate at present. The final recommendation is a policy change that aims to characterize sources of delay and accurately compensate for the delay using the Shop Capacity Buffer in the delivery date quote process.
- Administration and Management
- Manufacturing and Industrial Engineering and Control of Production Systems