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Material Handling and Production Systems Modelling - based on Queuing Models
Queuing networks applied to material handling and production systems
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Queueing models were successfully applied for material handling and production systems.The book helps practitioners to understand the major influences for inventory and lead times. Stochastic effects are frequently disregarded when designing material handling or production systems. Cause and effects for response times are derived. Based on this knowledge it is possible to identify areas of improvement in material handling systems. The book bridges the gap between stochastic modelling and practical engineering by combining the theoretical background with modelling examples in several applicatio...
Queueing models were successfully applied for material handling and production systems.
The book helps practitioners to understand the major influences for inventory and lead times. Stochastic effects are frequently disregarded when designing material handling or production systems. Cause and effects for response times are derived. Based on this knowledge it is possible to identify areas of improvement in material handling systems. The book bridges the gap between stochastic modelling and practical engineering by combining the theoretical background with modelling examples in several application domains. It is also a useful supplement in Masters and Ph.D. courses for students interested in engineering and operations management.
The book helps practitioners to understand the major influences for inventory and lead times. Stochastic effects are frequently disregarded when designing material handling or production systems. Cause and effects for response times are derived. Based on this knowledge it is possible to identify areas of improvement in material handling systems. The book bridges the gap between stochastic modelling and practical engineering by combining the theoretical background with modelling examples in several application domains. It is also a useful supplement in Masters and Ph.D. courses for students interested in engineering and operations management.
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