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논문 기본 정보

자료유형
학술저널
저자정보
Liem Yenny Bendatu (Petra Christian University) Bernardo Nugroho Yahya (Hankuk University of Foreign Studies)
저널정보
대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems Vol.17 No.2
발행연도
2018.6
수록면
193 - 208 (16page)
DOI
10.7232/iems.2018.17.2.193

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초록· 키워드

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Sequential decision problems have been recognized as a strategy which uses search techniques to generate sequence of actions that leads to good states. Current sequential decision problems require a given set of actions while the actions in kiln dry wood process relies on various factors that may diverse from time to time. Predefined kiln schedule has been available to assist kiln operator’s decision making. However, routine decision would be highly affected by either drying problems or customer complaints. Although many works attempt to apply mathematical model and some experiments to predict kiln dry process, relatively little attention has been paid to the problem of discovery sequential pattern from kiln dry wood process data. This study proposes a framework as a decision support for sequential decision problems, specifically, for kiln dry wood process. The framework starts with preprocessing the kiln process data, follows with mapping the preprocessed data into a log, and ends with analyzing as well as verifying the process using quality of predictions performance measures. A case study on real datasets in the field of kiln dry wood process indicate that historical data contain patterns which are able to generate kiln schedule and associated to possible future behavior.

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ABSTRACT
1. INTRODUCTION
2. RELATED WORK
3. METHODOLOGY
4. ANALYSIS RESULT - A CASE STUDY
5. CONCLUSION
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