Throughput Time Characteristics of Rush Orders and their Impact on Standard Orders

Trzyna, Daniel; Kuyumcu, Arif; Lödding, Hermann

doi:10.1016/j.procir.2012.07.054

Cited by 12 publications

(8 citation statements)

References 7 publications

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“…In production areas like these and at individual work systems, there is a fundamental conflict of objectives between the level of WIP and the logistics objectives of a short throughput time and a high output rate, as shown by the production operating curves (a) [1]. Furthermore, (b) the chosen sequencing procedure [5,35] and (c) possible prioritisations of rush or fast-track orders have an impact on throughput time (variability) and schedule deviation characteristics [6]. The prioritisation offers the possibility to accelerate material supply for downstream processes actively.…”

Section: B Logistics Modelling As An Enabler For Configuring the Company's Internal Supply Chainmentioning

confidence: 99%

Logistics-Oriented Production Configuration Using the Example of MRO Service Providers

2022

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Section: B Logistics Modelling As An Enabler For Configuring the Company's Internal Supply Chainmentioning

confidence: 99%

Logistics-Oriented Production Configuration Using the Example of MRO Service Providers

2022

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“…Rush orders are classified as special orders. Trzyna et al (2012) provide a technical definition of a rush order as "an order that did not arrange within time of the current schedule placed in a very short time of delivery, and need to be handled in a very short period of time." As previously indicated, time is the defining characteristic that differentiates a rush order from standard orders.…”

Section: Introductionmentioning

confidence: 99%

“…As previously indicated, time is the defining characteristic that differentiates a rush order from standard orders. Trzyna et al (2012) and Yao and Liu (2009) discuss the contemporary need to develop a more precise understanding of what the term "rush order" really means. They point out that the time threshold is a decisive feature of this process, including the impact on the organisational surroundings.…”

Section: Introductionmentioning

confidence: 99%

The Networked Handling of Rush Orders in Customer Services

Engelseth

White²

2020

OSCM: An Int. Journal

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Rush orders are characterised by time constraints and organisational priority. They are handled by the supplier with the aim of meeting customer requirements in as limited a timeframe as possible. Rather than focusing on rush orders as a deterministic planning problem, this paper takes an interorganisational perspective that highlights the complex networked interactions between the supplier and the customers. In this single case study of an advanced sanitary product supplier, rush orders involve process prioritisation concerning both: (i) supplies of in-stock parts that are delivered with preset time objectives; and (ii) parts not in stock that must be quickly fabricated. This supply process is highly emergent, in that unexpected events or properties occur. This study considers the difficulties of determining and dealing with root causes, unexpected effects, and interventive solutions for rush orders. This operational level of analysis provides a foundation for advocating the application of complex systems thinking to solve or at least significantly mitigate the problem of rush orders. It also contributes to and advances further research on this subject.

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“…Rush order is an implicit customer's priority request for his/her products to be delivered very quickly [5,6]. Literatures have treated rush order as a special disturbance that disrupts performance of an entire shop floor [7]. Accepting this perturbation could trade-off manufacturing lead time and resource utilization if an immediate action is not steadily taken.…”

Section: Introductionmentioning

confidence: 99%

CoMM: a consensus algorithm for multi-agent-based manufacturing system to deal with perturbation

Mezgebe

Demesure

Haouzi

et al. 2019

Int J Adv Manuf Technol

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The emergence of Cyber Physical System has dramatically impacted the use of traditionally centralized control system in responding to unexpected events. Rush order is quite common unexpected event in the current dynamic market characteristics and has significant perturbing ability to a centrally predictive schedule. This paper is aimed to propose a Consensus algorithm for Multi-agent based Manufacturing system (CoMM) to control the rush order and henceforth minimize a makespan. Consensus is an algorithmic procedure applied in control theory which allows convergence of state between locally autonomous agents collaborating for their common goal. Leader-Follower communication approach was used among the multi-agent to deal with the perturbing event. Each agent decides when to broadcast its state to neighbor agents and the controlling decision depends on the behavior of this state. The consensus algorithm is initially modeled by networking all contributing agents. After this, it is validated with simulation experiment based on academic full-sized application platform called TRACILOGIS platform. The results showed that the consensus algorithm has significantly minimized the impact of rush order on makespan of manufacturing orders launched on a system.

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Throughput Time Characteristics of Rush Orders and their Impact on Standard Orders

Cited by 12 publications

References 7 publications

Logistics-Oriented Production Configuration Using the Example of MRO Service Providers

Logistics-Oriented Production Configuration Using the Example of MRO Service Providers

The Networked Handling of Rush Orders in Customer Services

CoMM: a consensus algorithm for multi-agent-based manufacturing system to deal with perturbation

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