Integrating Production Control and Scheduling in Multisite Enterprises on the Basis of Real-Time Detection of Divergence
Scheduling and process control have been long recognized as the two critical building blocks in many manufacturing execution systems. Operating at the interface between the supply chain and the process, the scheduler generates a detailed schedule that has to be executed by the process so as to meet...
Gespeichert in:
Veröffentlicht in: | Industrial & engineering chemistry research 2016-05, Vol.55 (19), p.5681-5695 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Scheduling and process control have been long recognized as the two critical building blocks in many manufacturing execution systems. Operating at the interface between the supply chain and the process, the scheduler generates a detailed schedule that has to be executed by the process so as to meet the demands originating from the supply chain. Given the tight interactions between the two, there has been wide interest in integrating scheduling and process control. Our key insight is that abnormalities which occur after generation of the original schedule trigger a divergence between the operational targets defined by the schedule and its execution. If left uncorrected, then the abnormalities will propagate between the process and the supply chain. A timely response could eliminate or minimize such effects. However, this is a challenge particularly in large multisite enterprises where the scheduling and production responsibilities are typically separated across departments and even across geographical locations. Recognizing this, we propose a novel, scalable framework for integrating scheduling and process control that detects in real time when a divergence occurs between the original schedule and its execution in the process. It then identifies the root-cause(s) of the divergence, i.e., the abnormality, and triggers a suitable response from the scheduler and the process so as to nullify or minimize its effect. In this paper, we will describe the proposed approach and illustrate it using two industrially motivated case studies. |
---|---|
ISSN: | 0888-5885 1520-5045 |
DOI: | 10.1021/acs.iecr.5b04626 |