One of the most serious problems in current labor-intensive industries, such as clothing manufacture, is difficulty in maintaining special hand skills, especially because of aging of highly skilled workers. A systematic way to hand down special skills is therefore becoming urgently necessary. For the purpose of supporting transmission of such special skills, we propose an efficient method of clarifying the important points of highly skilled behavior.
As target tasks for analysis, we selected four typical difficult operations in clothing manufacture with sewing machines. The results can be flexibly applied to any kind of sewing-machine operations. Through observation of these operations, we pointed out several factors in the differences between highly skilled operators and unskilled operators. For example, highly skilled operators always keep their elbows lower and their wrists higher, whereas unskilled operators use the opposite posture during the task.
To clarify the hypothetical skill factors, quantitative measurement was performed, and an analysis method was developed to quantify the differences in behavior between highly skilled operators and unskilled operators. Task behaviors were measured with several sensing devices, such as a motion capturing device, data gloves, and a sewing-machine motor rotation counter. The proposed analysis method was applied to the experimental data, and adequacy of hypothetical skill factors was confirmed. The elbows of skilled workers are kept more than 40 mm lower than those of other workers.
Qualitative analysis was also performed. Differences in motion sequence patterns were analyzed as follows: First, arithmetically characteristic points were automatically extracted from each set of time-series data for measured behavior. These characteristic points were associated with predefined symbols and the symbols were used to establish a sequence pattern. The sequence pattern of symbols obtained was identified with a task model, which is a previously defined series of motions. Thus, portions of the whole measured behavior were associated with parts of the predefined task in partial motion level. Finally, the sequence patterns of symbols obtained from highly skilled operators and unskilled operators were compared, and the differences were extracted. Corresponding parts of sequences for each motion were also compared and their differences in partial motion level were extracted.
