Decision Making in Engineering and Technology Management
Solar collector industry -- management, Production control -- Mathematical models, Production management, Decision making, Technology -- Management
Finding the right product mix for production capacity is an issue facing many manufacturing facilities today. SolarTronic is no exception. This paper looks at forecasting and production issues facing SolarTronic and develops a model that can be used with sales forecasting in order to select an optimal product mix from potential customer orders. The idea is to reduce the impact of bottlenecks and optimize production with regard to product mix. The company wanted the model to be developed from customer criteria that takes into consideration factors such as strategic partnering, market share, and profitability instead of accepting whatever comes along or orders that generate the most revenue.
The model has three parts: A customer criteria-weighting model, a product mix optimization model, and a capacity expansion criteria-weighting model. The customer criteria-weighting model uses a hierarchical decision model, the optimization model uses simple optimization criteria, and the capacity expansion criteria-weighting model also uses a hierarchical decision model. Each model can be expanded upon as complexity demands, but for the purpose of illustrating, the various models have been simplified for clarity. All three models used sample data derived from the team members.
Angel, David; Edqards, Gord; Wright, Michael; and Yates, Diane, "Order Acceptance Optimization in Relation to Production Constraints Course Title:" (2004). Engineering and Technology Management Student Projects. 1397.