The goal of the cutting stock operation is to maximize the material utilization by laying out maximum number of parts on a sheet. Historically, laying of parts on a sheet has been performed by humans. As the manual process is very time consuming, a number of heuristic and mathematical algorithms have been developed in recent years. However, these algorithms do not guarantee higher utilizations than those acheived by human operators. This study investigated the feasibility of extracting and generating and generalizing the involved huamn strategies in laying out parts. The results indicated that it is possible to extract and form generalized strategies leading to higher utilization. A group, trained with these strategies, achieved higher utilization than the untrained group. The trained group also achieved higher utilization than hte most promising mathematical algorihtm. This implies that these strategies can be used to train new operators. Using these strategies and automation aids such as a graphics software, the layout process will be much faster and produce high material utilization.
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