Predicting the development cost of TFT-LCD manufacturing equipment with artificial intelligence models Jui-Sheng Chou a,n , Yian Tai a , Lian-Ji Chang b a National Taiwan University of Science and Technology, 43 Section 4, Keelung Road, Taipei 106, Taiwan b Contrel Technology Corporation, Taiwan article info Article history: Received 17 March 2009 Accepted 14 July 2010 Available online 23 July 2010 Keywords: TFT-LCD industry Manufacturing Project management Forecasting Artificial intelligence abstract Accurately and timely estimating product costs is extremely beneficial to corporate survival. This study assesses the reliability of multiple regression analysis (MRA), artificial neural networks (ANNs), case- based reasoning (CBR), and hybrid intelligence (Hi) to forecast costs of thin-film transistor liquid-crystal display (TFT-LCD) equipment. Newly completed equipment-development projects are provided by departments in a Taiwanese high-tech company, which is a top global producer of TFT-LCD equipment. The cross-fold validation method is applied to measure model performance, reliability, and prediction ease. Through comparison of various performance indices, the Hi method outperforms MRA, ANNs and CBR when used for cost prediction during conceptual stages. Although it is well developed in academia, artificial intelligence (AI) is rarely applied in practical project management. This study successfully describes an actionable knowledge-discovery process using a real-world data mining approach for the high-tech equipment manufacturing industry. Project managers (PMs) can benefit from applying the Hi approach to establish latent non-linear cost estimation relationships. The Hi approach is empirically proven an effective prediction technique for PMs considering overall evaluation criteria when determining the best selling prices of TFT-LCD manufacturing equipment to clients. & 2010 Elsevier B.V. All rights reserved. 1. Introduction The first impression of a display device is based on its design, quality and presentation in an advertisement. The span of devices ranges from simple displays in watches to complex technologies in computers. More than 500 million displays for televisions and computers were produced in 2008. Roughly 90% of these displays were cathode ray tubes (CRTs) in 1999. However, more than 60% of displays are now flat panels (e.g., liquid crystal displays (LCDs), plasma screens). The global market for panels, which was worth over US $70 billion in 2006, is predicted to reach US $92 billion in 2011 (ITIS, 2008). Therefore, thin-film transistor-LCDs (TFT-LCDs) now play a leading role in various flat-panel display devices (Menozzi et al., 2001), as TFT-LCDs have excellent features such as low profiles, low operating voltage, low power consumption, full- color capabilities, large visible area, and high-quality resolution. Prices of TFT-LCDs are strongly influenced by the high degree of uncertainty in research and development (R&D). In practice, a flat panel’s functions and specifications cannot be completely determined during the early R&D stages; thus, initial cost estimation (ICE) is generally based on the subjective judgment of experienced engineers. This ICE is only a quoted price for potential buyers and a comparative estimate for potential providers. Although knowledgeable sales managers or estimators may generate a good cost assessment via teamwork, professionals are difficult to train and are very mobile in the small- and medium-sized enterprises in Taiwan. Thus, this experience and project knowledge is hard to retain, resulting in such problems as loss of company credibility and potential customers. The TFT-LCD industry, promoted by Taiwan’s government in the Two Trillion Twin Stars plan, has developed rapidly in recent years. The TFT-LCD industry is second only to the semiconductor industry in driving Taiwan’s economic growth. Notably, LCD production involves hundreds of complex processes. Each panel manufacturer typically has unique patented processes and production lines requiring diverse manufacturing equipment with a high degree of customization. The production of diverse panel sizes is generally in demand as the need for next-generation panels increases. The technological environment has become increasingly competitive due to the rapid speed of globalization. Product cost estimation is a critical and important task for sales managers at high-tech equipment development companies to gain competitive advantage. As the time a panel manufacturer devotes to invest- ment and production is critical, fast and accurate estimations are essential to successful delivery of devices in a timely manner, as is quality to customers in the increasingly competitive market environment. Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/ijpe Int. J. Production Economics 0925-5273/$ - see front matter & 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.ijpe.2010.07.031 n Corresponding author. Tel.: + 886 2 2737 6321; fax: + 886 2 2737 6606. E-mail address: jschou@mail.ntust.edu.tw (J.-S. Chou). Int. J. Production Economics 128 (2010) 339–350