CIRP CMS Papers online

The contributions of PLN workgroup members to last years CIRP sponsored conference on manufacturing systems (CMS) in Stuttgart have now been published under a creative commons license in Procedia CIRP.

  • View document on publisher site V. Vican and J. Bendul, “Towards the Investigation of Production Order Interdependency Effects on Logistics Performance.” 2016, pp. 146-151, Factories of the Future in the digital environment – Proceedings of the 49th CIRP Conference on Manufacturing Systems.
    [Bibtex]
    @inproceedings{Vican:2016CMS,
    title = "Towards the Investigation of Production Order Interdependency Effects on Logistics Performance",
    journal = "Procedia CIRP",
    volume = "57",
    number = "",
    pages = "146 -- 151",
    year = "2016",
    note = "Factories of the Future in the digital environment - Proceedings of the 49th CIRP Conference on Manufacturing Systems",
    issn = "2212-8271",
    doi = "10.1016/j.procir.2016.11.026",
    url = "http://www.sciencedirect.com/science/article/pii/S2212827116311799",
    author = "Victor Vican and Julia Bendul",
    keywords = "Production",
    keywords = "Order",
    keywords = "Interdependency",
    keywords = "Granular",
    keywords = "Matter ",
    abstract = "Manufacturers continuously face the challenge of driving down costs while being subjected to increasingly globalized market pressures to shorten production lead times and increase delivery reliability. The early prediction of the expected logistics performance of single production orders as well as for the entire manufacturing system is a pivotal strategic corporate activity. However, companies frequently find themselves struggling to foresee and integrate operational dynamic effects related to production orders into production planning decisions. Such dynamic interdependency effects between orders in close temporal and spatial neighbourhoods can have an impact on logistics performance. In this research, we introduce an index measure that quantifies the spatial and temporal relation of production orders and investigate dynamic effects of production order interdependencies using real production feedback data and derive first results for the improvement of the prediction of logistics performance in an early production planning stage as well as for the configuration of production planning and control."
    }
  • View document on publisher site H. Blunck and J. Bendul, “Controlling Myopic Behavior in Distributed Production Systems — A Classification of Design Choices,” Procedia CIRP, vol. 57, pp. 158-163, 2016, Factories of the Future in the digital environment – Proceedings of the 49th CIRP Conference on Manufacturing Systems.
    [Bibtex]
    @article{Blunck:2016CMS,
    title = "Controlling Myopic Behavior in Distributed Production Systems --- A Classification of Design Choices",
    journal = "Procedia CIRP",
    volume = "57",
    number = "",
    pages = "158 -- 163",
    year = "2016",
    note = "Factories of the Future in the digital environment - Proceedings of the 49th CIRP Conference on Manufacturing Systems",
    issn = "2212-8271",
    doi = "10.1016/j.procir.2016.11.028",
    url = "http://www.sciencedirect.com/science/article/pii/S2212827116311817",
    author = "Blunck, Henning and Bendul, Julia",
    keywords = "Manufacturing System Design",
    keywords = "Distributed Control",
    keywords = "Myopia",
    keywords = "Industry 4.0",
    abstract = "The future of manufacturing and logistics is currently envisioned under many names: Industry 4.0, Manufacturing 2.0, Physical Internet, etc. They share the vision of distributing control tasks to 'smart' machines and products to attain higher flexibility, adaptability, and, in the light of increasingly complex and dynamic environmental conditions, higher logistic performance. The flip-side of such systems under distributed control is the rise of myopic (short-sighted) decision making, leading to system nervousness and loss of performance. Designing manufacturing (control) systems for distributed control hence is a significant challenge: With the system performance becoming an emergent property of the interplay of various decision making entities, system designers become conductors of societies of cyber-physical systems, seeking to balance the desirable traits of distributing control while limiting the negative effects of myopic decision making. In this contribution, we set out to help manufacturing system designers to better understand myopic behavior and the design decisions that are known to affect it. Our contribution can serve as a design aid for planners of distributed control systems by structuring the solution space of design decisions to control myopic behavior. By pointing to examples from various research streams, we provide guidance for system designers, seeking to maximize the performance of distributed production control systems."
    }