SBIR Phase I: Adaptive Job Scheduling Software For Cutting Room Operations

This Small Business Innovation Research (SBIR) Phase I project aims to create adaptive job scheduling software for cutting room operations. Cutting rooms are used primarily for the production of sewn goods (apparel, furniture, luggage, etc) as well as many other industries. Today, cutting room managers rely on personal experience, spreadsheets, e-mails, faxes, whiteboards and often outdated rules-of-thumb to schedule material, labor and equipment for their operations. There is currently no software that provides real-time decision support to assist them in executing cutting operations with optimal resource usage. This project is configurable software that can model and optimize, in real-time, the complex variables of cutting operations across many industry segments. The software will collect live manufacturing data and perform calculations to produce job schedules that optimize equipment, labor and material usage in cutting rooms. A further innovation is the addition of adaptive control. This will use actual operational performance to provide feedback in order to fine-tune the scheduling calculations. The use of adaptive job scheduling software is expected to result in a 20% increase in cutting productivity, as measured by lower labor costs, improved machine utilization and shorter lead times. The commercial potential of this project is to make cutting room operations more productive in order to retain U.S. manufacturing jobs. The U.S. sewn goods industries have been devastated by intense international competition that has made most domestic production non-competitive against off-shore labor rates. As a result, new innovations in sewn goods technology have focused on software that enabled manufacturers to outsource production low-cost countries instead of improvements for domestic manufacturing and protection of U.S. jobs. However, recent developments in highly engineered materials, such as body armor, require skilled labor to ensure quality standards of the finished product. These skill sets are more reliably found in domestic labor pools than in low-cost, untrained, foreign language, off-shore labor pools. Furthermore, domestic cutting operations are more likely than off-shore operations to use automated cut room equipment to increase productivity. This automated equipment can be made more efficient with effective job scheduling software. A 20% gain in productivity would help domestic manufacturers offset labor costs to maintain global competitiveness and retain an estimated 75,000 US manufacturing jobs.