Forecasting, Control, and Management of a Production System Using Predictive Visual Interactive Simulation

Rolando Quintana; Mark T. Leung

doi:10.1108/S1477-4070(2011)0000008015

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Advances in Business and Management Forecasting

ISSN: 1477-4070
Series editor(s): Professor Kenneth D. Lawrence

Subject Area: Management Science/Management Studies

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Forecasting, Control, and Management of a Production System Using Predictive Visual Interactive Simulation

Document Information:
Title:	Forecasting, Control, and Management of a Production System Using Predictive Visual Interactive Simulation
Author(s):	Rolando Quintana, Mark T. Leung
Volume:	8 Editor(s): Kenneth D. Lawrence, Ronald K. Klimberg ISBN: 978-0-85724-959-3 eISBN: 978-0-85724-960-9
Citation:	Rolando Quintana, Mark T. Leung (2011), Forecasting, Control, and Management of a Production System Using Predictive Visual Interactive Simulation, in Kenneth D. Lawrence, Ronald K. Klimberg (ed.) Advances in Business and Management Forecasting (Advances in Business and Management Forecasting, Volume 8), Emerald Group Publishing Limited, pp.185-198
DOI:	10.1108/S1477-4070(2011)0000008015 (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	Increasing competition within the global supply chain network has been pressuring managers to improve efficiencies of production systems while, at the same time, reduce manufacturing operation expenses. One well-known approach is to have better control of the manufacturing system through more accurate forecasting and efficient control. In other words, a production control paradigm with more reliable forward visibility should help in maintaining a cost-effective yet lean manufacturing environment. Hence, this study proposes a predictive decision support system for controlling and managing complex production environments and demonstrates a Visual Interactive Simulation (VIS) framework for forecasting system performances given a designated set of production control parameters. The VIS framework is applied to a real-world manufacturing system in which the primary objective is to minimize total production while maintaining consistently high throughput and controlling work-in-process level. Through this case study, we demonstrate the use and validate the effectiveness of VIS in optimization and prediction of the examined production system. Results show that the predictive VIS framework leads to better and more reliable decision making on selection of control parameters for the manufacturing system under study. Statistical analyses are incorporated to further strengthen the VIS decision-making process.