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    A Decision Support System Approach To Lot-Sizing Problem in Material Requirements Planning Process.
    (Niğde Üniversitesi, 2009) Paksoy, Turan; Bülbül, Hasan; Güzeldülger, Alihan
    Material Requirements Planning (MRP) is a system that has inputs like master production scheduling, product tree, inventory status information and outputs like planning reports of order precedence, performance control reports, and lead time. Decision Support Systems (DSS) is a flexible information technology system that is designed to help the decision making system in case the decision isn’t structural. This study is made for the purpose of resolving the lot-sizing problem in MRP process by using a DSS approach in flour milling system manufacturer firm. Thus, a DSS is developed in Visual Basic 6.0 and using the developed DSS, techniques that determine order quantities and makes cost analysis are researched and these techniques are implemented in the firm. After monthly demand quantities are inserted, the DSS is run, the optimal lot-sizing method that minimises the cost is found as the feasible method.
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    An empirical investigation of advanced manufacturing technology investment patterns: Evidence from a developing country
    (ELSEVIER SCIENCE BV, 2013) Bulbul, Hasan; Omurbek, Nuri; Paksoy, Turan; Bektas, Tolga
    Advanced manufacturing technology (AMT) investment patterns in developing countries is in need of further investigation, particularly in the light of the conflicting evidence from the literature. This paper provides new evidence on AMT investment patterns from the Turkish automotive industry and develops a taxonomy by exploring the relationships between AMT investment patterns, ownership structure, firm size and performance. Analysis of industry survey data suggests the existence of three groups with different AMT investment strategies. Results suggest that AMT investment patterns are not only significantly correlated with firm performance or ownership, but also reveals significant differences in manufacturing performance across investment patterns. (C) 2013 Elsevier B.V. All rights reserved.