Abstract
Suppliers are adjusting from the order-to-order manufacturing production mode toward demand forecasting. In the meantime, customers have increased demand uncertainty due to their own considerations, such as end-product demand frustration, which leads to suppliers’ inaccurate demand forecasting and inventory wastes. Our research applies ARIMA and LSTM techniques to establish rolling forecast models, which greatly improve accuracy and efficiency of demand and inventory forecasting. The forecast models, developed through historical data, are evaluated and verified by the root mean squares and average absolute error percentages in the actual case application, i.e., the orders of IC trays for semiconductor production plants. The proposed ARIMA and LSTM are superior to the manufacturer’s empirical model prediction results, with LSTM exhibiting enhanced performance in terms of short-term forecasting. The inventory continued to decline significantly after two months of model implementation and application.
Highlights
Taiwan’s semiconductor industry has been growing consistently for more than three decades, promoted as the strategic high-tech industrial development
The Long short-term memory (LSTM) model often has overfitting during training to make predict the number of sales, and the training set is divided into of the total data model predictions
The integrated circuit (IC) tray manufacturers provided the data by the industry–academia
Summary
Taiwan’s semiconductor industry has been growing consistently for more than three decades, promoted as the strategic high-tech industrial development. The industry specializes in integrated circuit (IC) design, fabrication and, develops complete IC packaging production from upstream IC wafer materials until downstream IC packaging and testing. Taiwan has the world’s most comprehensive semiconductor companies with high output values, where production processes, testing equipment, components (e.g., substrates and lead frames), and IC modules are recognized as the global leaders [1]. The Internet of Things (IoT) applications have enabled the real-time big data interactions for intelligent systems and applications, which increase demands for high-volume server and storage clouds. Since 2020, due to COVID19 lockdowns, the global demands of information and communication electronics have increased dramatically pushing the supply chain under tremendous stress. Overall, according to the Taiwan Semiconductor Industry Association (TSIA) and the Industrial
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