Enhancing the productivity in a dynamic environment - A case study in an automotive sensor manufacturer

Productivity is an essential metric that most companies use to measure their operational efficiency. This research endeavor focused on a high volume and low mix Electronics Manufacturing and Service (EMS) provider, which produces automotive temperature and pressure sensors through a Flexible Manufacturing Systems (FMS) philosophy. With significant challenges imposed by potentially significant strategic changes at this facility that could occur within a predetermined time frame, Industrial and Systems Engineering (ISE) tools were effectively utilized to maintain and improve the production throughput and quality while concurrently coping with the impact of limited and declining resources (such as manpower, equipment, and operating budgets). Through detailed statistical data analysis and a Design of Experiments (DOE) based approach, the critical factors affecting the throughput and resource utilization were identified. Alternative scenarios including (i) improving the production line changeover process, and (ii) 'optimizing' the maintenance schedules were then proposed to provide feasible improvements. In order to evaluate the system's performance based on these approaches without physically modifying the processes or implementing the changes, a discrete event simulation model was build to replicate the current system and subsequently used to quantify the system related improvements under the proposed scenarios. This research effort judiciously combined statistical analysis and simulation to address the various issues that impact productivity enhancement in a dynamic flexible manufacturing environment.