Optimization of Dual Stage Overmolding Process for Packaging Automotive Crash Sensors

This research investigates the integration of Axiomatic Design and Process Simulation in the design and development of a novel high-volume manufacturing system for the production of packaging for automotive safety electronic sensors. These electronic devices are to be encased in plastic through a new dual-stage overmolding process that forms the protective plastic envelope around the printed circuit assembly through an injection molding process.;Automotive passive safety electronic systems sense vehicle conditions that indicate the potential for a crash event, determine whether a crash is actually beginning to occur and control the inflation of the vehicle airbags. Critical inputs in this scenario are provided by distance, acceleration and pressure sensing devices. These "satellite" sensors are remotely located from the central electronic control unit and peripherally positioned through-out the vehicle.;The sensing devices must provide functionality that is unaffected by the environment since these sensors are remotely located in the vehicle and may be exposed to both the ambient environment and heat and vibration of the vehicle itself. In this new two stage molding process, the plastic is directly molded around the electronic printed circuit board assembly to provide electrical interconnect to the vehicle wiring harness, environmental protection, vehicle mounting security and mechanical packaging. Design and optimization of this original dual-stage overmolding process employs an innovative amalgamation of the Axiomatic Process Design and Process Simulation.;Optimization of the manufacturing cell design consisted of two phases. The process of designing the manufacturing sequence itself was optimized by employing Manufacturing System Design Decomposition which focuses the cell design on independent cell functional requirements from high-level organization functional requirements. The model that was created by MSDD reduced the manufacturing cell design to the minimum set of Design Parameters that satisfy the Functional Requirements. The second stage of the optimization employed the functional requirement based cell design to define and structure a simulation model. The simulation model was then exercised to assess and maximize utilization and capacity and this information was employed to achieve the goals of maximizing Return on Sales and minimizing manufacturing cost.