Details
| Original language | English |
|---|---|
| Pages (from-to) | 544-559 |
| Number of pages | 16 |
| Journal | European Journal of Operational Research |
| Volume | 302 |
| Issue number | 2 |
| Early online date | 13 Jan 2022 |
| Publication status | Published - 16 Oct 2022 |
Abstract
We consider a model of an N-stage flow line with stochastic processing times and interstage buffers that decouple adjacent production stages. Machine downtimes are induced by failures of critical machine components. Each machine is assumed to have exactly one of these failure-prone components. To achieve high machine availability, it is assumed that spare parts for those failure-prone critical components are kept in stock. Failed components are immediately replaced with new, functioning components, and a one-for-one replenishment policy is applied for the restocking of those spare parts. We present a novel decomposition approach to approximate the average throughput and inventory for a system with an arbitrary number of machines, buffers, and spare parts. With a detailed numerical study, we analyze the impact of different parameter constellations on the approximation quality. We demonstrate the remarkable accuracy of our method by comparing our results with both exact and simulated values. Using our method, we further study the complex interaction and partial substitution effects between buffer sizes and spare part base-stock levels on the logistical performance of the flow line.
Keywords
- Decomposition, Manufacturing, Markov processes, Spare parts, Stochastic flow lines
ASJC Scopus subject areas
- Computer Science(all)
- Mathematics(all)
- Modelling and Simulation
- Decision Sciences(all)
- Management Science and Operations Research
- Decision Sciences(all)
- Information Systems and Management
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In: European Journal of Operational Research, Vol. 302, No. 2, 16.10.2022, p. 544-559.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Evaluation of Unreliable Flow Lines with Limited Buffer Capacities and Spare Part Provisioning
AU - Sachs, F. E.
AU - Helber, S.
AU - Kiesmüller, G. P.
PY - 2022/10/16
Y1 - 2022/10/16
N2 - We consider a model of an N-stage flow line with stochastic processing times and interstage buffers that decouple adjacent production stages. Machine downtimes are induced by failures of critical machine components. Each machine is assumed to have exactly one of these failure-prone components. To achieve high machine availability, it is assumed that spare parts for those failure-prone critical components are kept in stock. Failed components are immediately replaced with new, functioning components, and a one-for-one replenishment policy is applied for the restocking of those spare parts. We present a novel decomposition approach to approximate the average throughput and inventory for a system with an arbitrary number of machines, buffers, and spare parts. With a detailed numerical study, we analyze the impact of different parameter constellations on the approximation quality. We demonstrate the remarkable accuracy of our method by comparing our results with both exact and simulated values. Using our method, we further study the complex interaction and partial substitution effects between buffer sizes and spare part base-stock levels on the logistical performance of the flow line.
AB - We consider a model of an N-stage flow line with stochastic processing times and interstage buffers that decouple adjacent production stages. Machine downtimes are induced by failures of critical machine components. Each machine is assumed to have exactly one of these failure-prone components. To achieve high machine availability, it is assumed that spare parts for those failure-prone critical components are kept in stock. Failed components are immediately replaced with new, functioning components, and a one-for-one replenishment policy is applied for the restocking of those spare parts. We present a novel decomposition approach to approximate the average throughput and inventory for a system with an arbitrary number of machines, buffers, and spare parts. With a detailed numerical study, we analyze the impact of different parameter constellations on the approximation quality. We demonstrate the remarkable accuracy of our method by comparing our results with both exact and simulated values. Using our method, we further study the complex interaction and partial substitution effects between buffer sizes and spare part base-stock levels on the logistical performance of the flow line.
KW - Decomposition
KW - Manufacturing
KW - Markov processes
KW - Spare parts
KW - Stochastic flow lines
UR - http://www.scopus.com/inward/record.url?scp=85123924847&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2022.01.005
DO - 10.1016/j.ejor.2022.01.005
M3 - Article
AN - SCOPUS:85123924847
VL - 302
SP - 544
EP - 559
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 2
ER -