Decentralized multi-product multi-stage systems with backorders

Abstract

A multi-stage production/inventory system with decentralized two-card kanban control policies producing multiple product types is considered. The system involves one-at-a-time processing at each stage, finite target levels in the buffers and batch transfers between production stages. The demand process for each product is assumed to be Poisson and excess demand is backordered. Products have a priority structure and the processor at each stage is shared according to a switching rule. Our objective is to obtain steady-state performance measures such as the average inventory and service levels for each product type. We propose an approximation algorithm based on: (i) characterization of the delay by a product type before receiving the processor's attention at each stage; and (ii) creation of subsystems for all the storage activity and phase-type modeling of the remaining system's behavior. Numerical examples are presented to show the accuracy of the method and its potential use in system design.

Analysis of Multiproduct Manufacturing Systems With Homogeneous Exponential Machines

“…Paper [9] addresses the stability of a multiproduct system with back orders under the assumptions of infinite buffer and constant demand rate. In inventory studies, papers [10] and [11] assume priority processing policy and study continuous-review policy in multiproduct systems. The problem of assigning kanbans to different products under a CONWIP control policy is considered in [12].…”

Scheduling policies in multi-product manufacturing systems with sequence-dependent setup times

“…al 2000;Takagi 2000). In recent years, there is an increasing research attention on multi-product systems (for instance, Altiok and Shiue 2000;Kuhn 2002, 2004;Huang 2005, 2007;Ryan and Vorasayan 2005;Jang 2007;Satyam 2007;Dasci and Karakul 2008;Gurgur and Altiok 2008;Satyam and Krishnamurthy 2008;Tubilla and Gershwin 2009;Wang et. al 2010).…”

Evaluation of multi-product lean manufacturing systems with setup and erratic demand

“…A review of studies on a multi-product lean manufacturing environment shows that the majority of those studies focused on an analysis, planning and scheduling problems (Akturk & Erhun, 1999;Gurgur & Altiok, 2008;Hum & Lee, 1998;Krieg & Kuhn, 2008), production configuration settings and optimisation of production control parameter cards (Bard & Golany, 1991;Soroush et al, 2014), or understanding the control mechanisms of specific pull production control strategies (e.g. Duenyas, 1994;El-Khouly, El-Kilany, & El-Sayed, 2009;Prakash & Chin, 2014;Ryan, Baynat, & Choobineh, 2000;Ryan & Vorasayan, 2005;Satyam & Krishnamurthy, 2008; investigated the behaviour and the effect of the work-in-process inventory limit of CONWIP).…”