Cycle Time Forecasting And Improvement Of Chip Assembly And Testing Production Line

Cycle time forecasting and improvement of chip assembly and testing production line was sponsored by 2010 National Natural Science Foundation Self-organized Critical State Identification and Risk Research of Machine Sudden Large Failure(Grant NO.:51075070).In modern manufacturing environment, high competitive production cycle time is one of the key factors of enterprise’s success, especially for its high cost, high-level automation, complex craft and short life cycle, so production’s cycle time relate to the survival of enterprise, which force enterprise control cycle time better to keep its market competitiveness. Because of natural variability, schedule and unscheduled down time, rework, Machine Sudden Large Failure, flow variability etc. in chip assembly and test line, the study of cycle time becomes very complex, the particularity in chip assembly and test line makes its cycle time be more sensitive to variability. A chip assembly and test line was chose to study how to quantify variability, analysis cycle time composition and forecast cycle time. And a feed forward control strategy was established on the basis of a deep understanding and analysis of the chip assembly and test line.Firstly, enter enterprise to study the chip assembly and test production line, analysis its characteristics and abstract the logical line of the actual production line. Furthermore, establish a variability quantify method which is suitable for chip assembly and test line based on the study of cause of variability, variability classification and quantification to lay the foundation to cycle time forecasting and feed forward improvement strategy.Secondly, analysis composed ingredients of cycle time of the production line and pay special attention to queue time which is the most important part of cycle time, study current cycle time forecasting method, analysis its disadvantages and improve it by combining with Machine Sudden Large Failure, historical schedule and unschedule down time data and schedule data to get a new cycle time forecasting method, and do some adjust when meet product mix situation. Then do case study with factory’s actual data to validate the method.At last, combine with internal benchmarking evaluation, X-Factor standard and forecasting result judge again to establish a feed forward improvement strategy based on cycle time forecasting result. When a judge is eligible, the corresponding improvement direction and method is given out to insure the plan is meeting the expectation. A case study is given out to validate the method with actual data.