Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control

Henning Blunck, Hans Armbruster, Julia Bendul

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Capacity dimensioning in production systems is an important task within strategic and tactical production planning which impacts system cost and performance. Traditionally capacity demand at each worksystem is determined from standard operating processes and estimated production flow rates, accounting for a desired level of utilization or required throughput times. However, for distributed production control systems, the flows across multiple possible production paths are not known a priori. In this contribution, we use methods from algorithmic game-theory and traffic-modeling to predict the flows, and hence capacity demand across worksystems, based on the available production paths and desired output rates, assuming non-cooperative agents with global information. We propose an iterative algorithm that converges simultaneously to a feasible capacity distribution and a flow distribution over multiple paths that satisfies Wardrop's first principle. We demonstrate our method on models of real-world production networks.

Original languageEnglish (US)
Title of host publicationProcedia CIRP
PublisherElsevier
Pages460-465
Number of pages6
Volume41
DOIs
StatePublished - 2016
Event48th CIRP International Conference on Manufacturing Systems, CIRP CMS 2015 - Ischia, Italy
Duration: Jun 24 2015Jun 26 2015

Other

Other48th CIRP International Conference on Manufacturing Systems, CIRP CMS 2015
CountryItaly
CityIschia
Period6/24/156/26/15

Fingerprint

Production control
Game theory
Flow rate
Throughput
Control systems
Planning
Costs

Keywords

  • Agent Based Manufacturing Control
  • Algorithmic Game Theory
  • Capacity Dimensioning
  • Resource Requirements Problem

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Cite this

Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control. / Blunck, Henning; Armbruster, Hans; Bendul, Julia.

Procedia CIRP. Vol. 41 Elsevier, 2016. p. 460-465.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Blunck, H, Armbruster, H & Bendul, J 2016, Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control. in Procedia CIRP. vol. 41, Elsevier, pp. 460-465, 48th CIRP International Conference on Manufacturing Systems, CIRP CMS 2015, Ischia, Italy, 6/24/15. https://doi.org/10.1016/j.procir.2015.12.117
Blunck, Henning ; Armbruster, Hans ; Bendul, Julia. / Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control. Procedia CIRP. Vol. 41 Elsevier, 2016. pp. 460-465
@inproceedings{6c66ba4d780f40a48d99457abac43c29,
title = "Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control",
abstract = "Capacity dimensioning in production systems is an important task within strategic and tactical production planning which impacts system cost and performance. Traditionally capacity demand at each worksystem is determined from standard operating processes and estimated production flow rates, accounting for a desired level of utilization or required throughput times. However, for distributed production control systems, the flows across multiple possible production paths are not known a priori. In this contribution, we use methods from algorithmic game-theory and traffic-modeling to predict the flows, and hence capacity demand across worksystems, based on the available production paths and desired output rates, assuming non-cooperative agents with global information. We propose an iterative algorithm that converges simultaneously to a feasible capacity distribution and a flow distribution over multiple paths that satisfies Wardrop's first principle. We demonstrate our method on models of real-world production networks.",
keywords = "Agent Based Manufacturing Control, Algorithmic Game Theory, Capacity Dimensioning, Resource Requirements Problem",
author = "Henning Blunck and Hans Armbruster and Julia Bendul",
year = "2016",
doi = "10.1016/j.procir.2015.12.117",
language = "English (US)",
volume = "41",
pages = "460--465",
booktitle = "Procedia CIRP",
publisher = "Elsevier",

}

TY - GEN

T1 - Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control

AU - Blunck, Henning

AU - Armbruster, Hans

AU - Bendul, Julia

PY - 2016

Y1 - 2016

N2 - Capacity dimensioning in production systems is an important task within strategic and tactical production planning which impacts system cost and performance. Traditionally capacity demand at each worksystem is determined from standard operating processes and estimated production flow rates, accounting for a desired level of utilization or required throughput times. However, for distributed production control systems, the flows across multiple possible production paths are not known a priori. In this contribution, we use methods from algorithmic game-theory and traffic-modeling to predict the flows, and hence capacity demand across worksystems, based on the available production paths and desired output rates, assuming non-cooperative agents with global information. We propose an iterative algorithm that converges simultaneously to a feasible capacity distribution and a flow distribution over multiple paths that satisfies Wardrop's first principle. We demonstrate our method on models of real-world production networks.

AB - Capacity dimensioning in production systems is an important task within strategic and tactical production planning which impacts system cost and performance. Traditionally capacity demand at each worksystem is determined from standard operating processes and estimated production flow rates, accounting for a desired level of utilization or required throughput times. However, for distributed production control systems, the flows across multiple possible production paths are not known a priori. In this contribution, we use methods from algorithmic game-theory and traffic-modeling to predict the flows, and hence capacity demand across worksystems, based on the available production paths and desired output rates, assuming non-cooperative agents with global information. We propose an iterative algorithm that converges simultaneously to a feasible capacity distribution and a flow distribution over multiple paths that satisfies Wardrop's first principle. We demonstrate our method on models of real-world production networks.

KW - Agent Based Manufacturing Control

KW - Algorithmic Game Theory

KW - Capacity Dimensioning

KW - Resource Requirements Problem

UR - http://www.scopus.com/inward/record.url?scp=84968756328&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84968756328&partnerID=8YFLogxK

U2 - 10.1016/j.procir.2015.12.117

DO - 10.1016/j.procir.2015.12.117

M3 - Conference contribution

AN - SCOPUS:84968756328

VL - 41

SP - 460

EP - 465

BT - Procedia CIRP

PB - Elsevier

ER -