Capacity and Resource Planning for an Engineering Technology Department

Conference paper AC 2009-1489 by Daniel P. Johnson, associate professor and department chair in manufacturing and mechanical engineering technology at the Rochester Institute of Technology, on applying industrial capacity planning to a university department. Argues that although most education concepts such as curriculum design, learning styles and motivation have little correlation with industrial production, capacity planning maps directly, since enrolment demand plays the same role as product demand on a factory. Describes the use of ordinary spreadsheet tools such as linear regression to build time-series forecasts of student demand for academic resources, then the department's real data: enrollments by programme, available sections and students per section for manufacturing processes laboratories, solid modelling, materials technology and geometric dimensioning and tolerancing. Compares the forecasting tools available and concludes that a Monte Carlo evaluation of the likelihood of future resource shortages gave the best insight into the department's coming constraints, with heijunka-based levelling discussed as an alternative.