From Volatile Maintenance Data Forecasting to Reliable Capacity Planning
Research output: Contributions to collected editions/works › Article in conference proceedings › Research
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Proceedings of the World Congress on Engineering and Computer Science 2008. ed. / S. I. Ao; Craig Douglas; W.S. Grundfest; LE Schruben; John Borgstone. Newswood Limited, 2008. p. 1118-1122 (Lecture Notes in Engineering and Computer Science; No. 2173).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research
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TY - CHAP
T1 - From Volatile Maintenance Data Forecasting to Reliable Capacity Planning
AU - Berkholz, Daniel
AU - Schmidt, Matthias
AU - Nyhuis, Peter
PY - 2008
Y1 - 2008
N2 - Maintenance, repair and overhaul processes (MRO processes) are elaborate and complex. Rising demands on these after sales services require reliable production planning and control methods particularly for maintainingvaluable capital goods. Downtimes lead to high costs and an inability to meet delivery due dates results in severe contract penalties. Predicting the required capacities for maintenance orders in advance is often difficult due to unknown part conditions unless the goods are actually inspected. This planning uncertainty results in extensive capital tie-up by rising stock levels within the whole MRO network.This paper outlines an approach to planning capacities when maintenance data forecasting is volatile. It focuses on the development of prerequisites for a reliable capacity planning method. This is achieved by deriving order probabilities from Bayesian networks. In addition the residual wear margin isused to determine an appropriate part-dependent work content.
AB - Maintenance, repair and overhaul processes (MRO processes) are elaborate and complex. Rising demands on these after sales services require reliable production planning and control methods particularly for maintainingvaluable capital goods. Downtimes lead to high costs and an inability to meet delivery due dates results in severe contract penalties. Predicting the required capacities for maintenance orders in advance is often difficult due to unknown part conditions unless the goods are actually inspected. This planning uncertainty results in extensive capital tie-up by rising stock levels within the whole MRO network.This paper outlines an approach to planning capacities when maintenance data forecasting is volatile. It focuses on the development of prerequisites for a reliable capacity planning method. This is achieved by deriving order probabilities from Bayesian networks. In addition the residual wear margin isused to determine an appropriate part-dependent work content.
KW - Engineering
KW - Capacity Planning
KW - capital
KW - forecasting
KW - Maintenance
KW - Logistics
KW - Production and Operation Management
M3 - Article in conference proceedings
SN - 978-988-98671-0-2
T3 - Lecture Notes in Engineering and Computer Science
SP - 1118
EP - 1122
BT - Proceedings of the World Congress on Engineering and Computer Science 2008
A2 - Ao, S. I.
A2 - Douglas, Craig
A2 - Grundfest, W.S.
A2 - Schruben, LE
A2 - Borgstone, John
PB - Newswood Limited
T2 - World Congress on Engineering and Computer Science - 2008
Y2 - 22 October 2008 through 24 October 2008
ER -