Cycle time estimation for printed circuit board assemblies

Competitive pressures continue to force the electronics industry to keep costs down and to reduce the duration of the development cycle for its products. These goals must be accomplished while maintaining the quality of the products and keeping up with the latest technology. In increasing numbers, electronics companies are collaborating with other companies to achieve their business goals and to stay competitive. This collaboration has taken the form of outsourcing entire operations and services in addition to outsourcing certain components. Such collaboration and outsourcing efforts result in a distributed manufacturing environment and place increased stress on the information infrastructure, thus requiring firms to implement technological changes in order to compete using these business and enterprise practices. The Electronics Agile Manufacturing Research Institute (EAMRI), Rensselaer Polytechnic Institute, was formed to develop tools to support distributed electronics manufacturing environments. The principal EAMRI-developed technology is based on a distributed, heterogeneous and network-based information system architecture and is called the Virtual Design Environment (VDE). The VDE uses special algorithms along with a distributed database to optimize printed circuit board design. As a part of this effort, the EAMRI has developed a cycle time estimation model that determines the cycle time or time duration for a printed circuit board assembly before its realization. We model the printed circuit board as going through three stages of realization: design, resource planning, and manufacturing. The cycle time model provides an estimate for each phase based on information available about the printed circuit board before that phase has commenced. This model allows for greater flexibility and insight into planning the development process for a board and in allocating the resources to assure that each circuit board meets its schedule. This paper details the development of cycle time estimation models and describes their potential use in a collaborative, distributed manufacturing environment