Category Archives: Allgemein

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Two DAAD RISE Interns for PLN-Workgroup

Today, the Production & Logistics Networks Workgroup welcomed two interns, who will support the research of our workgroup as part of the DAAD RISE Program.

Nura Kawa and Jack Rossi hail from the University of California (Berkeley) and the University of Pittsburgh and will stay in Bremen for 12 and 10 weeks respectively. It’s gonna be exciting!

By the way: This is already the third year in a row that the PLN workgroup has the pleasure to host interns as part of the DAAD RISE program!

Papers from CIRP CMS 2015 Published Online

The proceedings of the 48th CIRP Conference on Manufacturing Systems (CMS), held last year in Naples (Italy), have been published online.

The PLN workgroup presented three papers at the conference which can now be obtained through ScienceDirect.

  • View document on publisher site H. Blunck, D. Armbruster, and J. Bendul, “Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control.” 2016, pp. 460-465, Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future – Proceedings of the 48th CIRP Conference on Manufacturing Systems.
    [Bibtex]
    @inproceedings{Blunck:2015CMS,
    title = "Simultaneous Workload Allocation and Capacity Dimensioning for Distributed Production Control",
    journal = "Procedia CIRP",
    volume = "41",
    number = "",
    pages = "460 - 465",
    year = "2016",
    note = "Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems ",
    issn = "2212-8271",
    doi = "10.1016/j.procir.2015.12.117",
    url = "http://www.sciencedirect.com/science/article/pii/S2212827115011968",
    author = "Henning Blunck and Dieter Armbruster and Julia Bendul",
    keywords = "Agent Based Manufacturing Control",
    keywords = "Capacity Dimensioning",
    keywords = "Resource Requirements Problem",
    keywords = "Algorithmic Game Theory ",
    abstract = "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. "
    }
  • View document on publisher site M. Apostu and J. Bendul, “Long-term Capacity Planning in Die Manufacturing Using the Estimated Product Cost: An Exploratory Research.” 2016, pp. 39-44, Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future – Proceedings of the 48th CIRP Conference on Manufacturing Systems.
    [Bibtex]
    @inproceedings{Apostu:2015CMS,
    title = "Long-term Capacity Planning in Die Manufacturing Using the Estimated Product Cost: An Exploratory Research",
    journal = "Procedia CIRP",
    volume = "41",
    number = "",
    pages = "39 - 44",
    year = "2016",
    note = "Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems ",
    issn = "2212-8271",
    doi = "10.1016/j.procir.2015.08.105",
    url = "http://www.sciencedirect.com/science/article/pii/S2212827115010781",
    author = "Marius-Vasile Apostu and Julia Bendul",
    keywords = "cost estimation",
    keywords = "capacity planning",
    keywords = "die manufacturing",
    abstract = "Abstract The tool manufacturing industry is constantly facing the challenge of producing qualitative products while reducing costs. The challenge is increased partly due to the uniqueness of the products and partly due to the architecture of the production facilities. Nowadays tools and dies are still being produced in job-shop environments due to the complexity and high variance of the products. In such a production facility capacity planning is of vital importance as scarce resources need to be cleverly managed in order to obtain a high utilization. However, with unique parts all required processes cannot be fully determined in advance and consequently, in practice, only the estimated cost of the products is used in order to determine the amount of work required to produce them. As a result, the earlier the cost of production for the product can be determined, the better can the long-term investments in production capacity be planned in the job-shop. For this purpose numerous cost estimation techniques have been developed during the past years. From simple parametric methods to complex feature- and case-based cost estimation techniques, the literature is rich with theoretical information intended to address this problem. However, researchers' access to real cost data is almost inexistent as companies are understandably reluctant to release cost information externally. This article aims at revealing the connection between long term capacity planning and the estimated product cost. A secondary aim is investigating to what extent developed cost estimation methods have-been tested with real cost information and furthermore review how accurate they have been established to be. First, an overview of cost estimation as well as a description of various methods will be presented along with an insight into the accuracy of such methods in practice. Secondly, the basics of long-term capacity planning are approached by the paper followed by a discussion of the connection between the two different research foci based on interviews with industry experts."
    }
  • View document on publisher site J. Bendul and M. Knollmann, “The Lead Time Syndrome of Manufacturing Control: Comparison of Two Independent Research Approaches.” 2016, pp. 81-86, Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future – Proceedings of the 48th CIRP Conference on Manufacturing Systems.
    [Bibtex]
    @inproceedings{Bendul:2015CMS,
    title = "The Lead Time Syndrome of Manufacturing Control: Comparison of Two Independent Research Approaches",
    journal = "Procedia CIRP",
    volume = "41",
    number = "",
    pages = "81 - 86",
    year = "2016",
    note = "Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems",
    issn = "2212-8271",
    doi = "10.1016/j.procir.2015.08.104",
    url = "http://www.sciencedirect.com/science/article/pii/S221282711501077X",
    author = "Julia Bendul and Mathias Knollmann",
    keywords = "Control-theoretic simulation",
    keywords = "production planning and control",
    keywords = "manufacturing control",
    keywords = "logistic target achievement",
    abstract = "The aim of production planning and control is to ensure the achievement of the logistic targets of high due date reliability, low lead times, high capacity utilization, and low WIP levels, while maintaining productivity and quality targets. If order due dates are missed, a common intuitive reaction of production planners is to adjust planned lead times. How often and to what extent updates are reasonable has previously been unclear because, while trying to improve the logistic target achievement, planned lead time adjustments may actually cause an opposite effect, which is known as the Lead Time Syndrome (LTS) of Manufacturing Control. Previous research on the LTS interactions has shown that the line of argumentation of the LTS is valid. Knollmann et al. showed by means of mathematical modeling, control-theoretic simulation and case study research that planned lead time adjustments lead to a short-term increase in lead time variation, thus to an increase in lateness variation and to a decrease in due date reliability. The authors suggest to choose update frequency depending on the ratio of latency period and the update frequency (the period between two consecutive adjustments) as the misbalance of these two parameters turns out to be the main trigger of the LTS. Sel\c{c}uk investigated the LTS by means of queuing theory in an independent approach. The authors concluded that planned lead time adjustments lead to an increase in process variability, thus to high WIP levels and long lead times. However, they suggest to reduce update frequency, to decrease process variability and thus to avoid LTS. This conclusion is not in line with the conclusions drawn from the research presented by Knollmann et al.. Therefore, this paper compares the different research approaches methodologies and discusses how the different research methodologies impact the conclusions drawn for practice application. This comparison provides further insights into LTS research and indicates further research fields."
    }