Speeding Car Body Production at PSA Peugeot Citroën
The Problem
PSA Peugeot Citroën is the sixth largest carmaker in the world and the second largest in Europe. In 1998, to meet its new CEO's ambitious targets for growth, innovation, and profitability, PSA decided to focus on bottlenecks in the car body shops in its plants. The shops' single flow architecture limited PSA's ability to handle diverse models, and ingrained beliefs and practices in production line design were causing inefficiency. The car body production line needed a new architecture that could handle model diversity and new car launches easily and quickly, and a method of sustaining quick innovation without overinvestment. Solving these problems would require analytics expertise in simulation, Markov chains, and other sophisticated analytical methods.
The Analytics Solution
To realize its plan, PSA needed analytics tools that R&D personnel could use to design shops accurately and quickly. The PSA analytics team used a multi-method approach to evaluate performance, developing an iterative three-step design process that took advantage of the speed of analytic methods and the accuracy of simulation.
The Value
The analytics tools improved throughput with minimal capital investment and no compromise in quality – contributing $130 million to the bottom line in 2001 alone. PSA personnel, initially skeptical about analytics, had the opportunity to compare the results that the analytical methods predicted with the actual outcomes. Persuaded by the accuracy of the forecasts, they and other PSA divisions adopted the tools and initiated further analytics projects.
Said Christophe de Baynast, Director of Car Structure Entity at PSA, "We expect a $130 million revenue gain just from this improvement. Other benefits due to this work include aid in decision making and forecasting, more accurate and faster shops' design, and better knowledge of manufacturing systems in our staff and our suppliers."
