A model-based decision support system for scheduling lumber drying operations

A model-based decision support system for scheduling lumber drying operations

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Article ID: iaor1994579
Country: United States
Volume: 1
Issue: 3
Start Page Number: 320
End Page Number: 321
Publication Date: Jun 1992
Journal: Production and Operations Management
Authors: , ,
Keywords: manufacturing industries, artificial intelligence: decision support
Abstract:

Raw lumber must be dried to a specified level of moisture content before it can be used to make furniture. This paper deals with a model-based decision support system (DSS) for a local furniture manufacturing company to assist its management in scheduling lumber drying operations. In addition to buying ready-to-use dried lumber from vendors at a premium, the company processes raw lumber in house using two production processes that require various lengths of processing time in predryers and dry-kilns. Given the demand for various types of dried lumber over a specified planning horizon, the processing times and costs for each production process, technological restrictions, and management policies, the problem of interest is to satisfy the demand at a minimum cost. The DSS incorporates the mathematical formulation of this problem, is user friendly, maintains model and data independence, and generates the necessary reports, including loading and unloading schedules for the equipment.

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