Tractable supply chain production planning, modeling nonlinear lead time and quality of service constraints
Yükleniyor...
Dosyalar
Tarih
2007
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper addresses the task of coordinated planning of a supply chain (SC). Work in process (WIP) in each facility participating in the SC, finished goods inventory, and backlogged demand costs are minimized over the planning horizon. In addition to the usual modeling of linear material flow balance equations, variable lead time (LT) requirements, resulting from the increasing incremental WIP as a facility's utilization increases, are also modeled. In recognition of the emerging significance of quality of service (QoS), that is control of stockout probability to meet demand on time, maximum stockout probability constraints are also modeled explicitly. Lead time and QoS modeling require incorporation of nonlinear constraints in the production planning optimization process. The quantification of these nonlinear constraints must capture statistics of the stochastic behaviour of production facilities revealed during a time scale for shorter than the customary weekly time scale of the planning process. The apparent computational complexity of planning production against variable LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS impact to the plan's detriment. The computational complexity challenge was overcome by proposing and adopting a time-scale decomposition approach to production planning where short-time-scale stochastic dynamics are modeled in multiple facility-specific subproblems that receive tentative targets from a deterministic master problem and return statistics to it. A converging and scalable iterative methodology is implemented, providing evidence that significantly lower cost production plans are achievable in a computationally tractable manner.
Açıklama
NSF Grant DMI-0300359 is acknowledged for partial support of the research reported here.
Anahtar Kelimeler
Manufacturing flow controllers, Perturbation analysis, Production systems, Inventory control, Large deviations, Network model, Fluid network, Job-shop, Policies, Design, Computational complexity, Lead, Linear equations, Manufacture, Mathematical techniques, Planning, Probability, Process engineering, Process planning, Production control, Production engineering, Project management, Quality control, Statistical methods, Stochastic programming, Supply chain management, Supply chains, Coordinated planning, Finished goods (FG), Lead time, Lower cost, Manufacturing engineers, Material flows, Non linear constraint, On time, Optimization processes, Paper addresses, Planning horizons, Planning process (CPPS), Probability constraints, Production facilities, Production planning, QoS constraints, Quality of service (QoS), Quality of Service (QoS) constraints, Stochastic behavior, Stochastic dynamics, Stock outs, Sub-problems, Supply chain (SC), Time scale decomposition, Time scaling, Variable lead time, Work-in-process (WIP), Quality of service
Kaynak
Journal of Manufacturing Systems
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
26
Sayı
2
Künye
Anli, O. M., Caramanis, M. C. & Paschalidis, I. C. (2007). Tractable supply chain production planning, modeling nonlinear lead time and quality of service constraints. Journal of Manufacturing Systems, 26(2), 116-134. doi:10.1016/j.jmsy.2008.05.001
