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Optimierung geschlossener Wertschöpfungskreisläufe bei beschränkten Kapazitäten
Citation Link: https://doi.org/10.15480/882.3419
Publikationstyp
Doctoral Thesis
Date Issued
2021-04-11
Sprache
German
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2020-12-11
TORE-DOI
TORE-URI
Citation
Technische Universität Hamburg (2021)
Nowadays, manufacturing companies are faced with the trade-off between cost minimization through mass production of standardized products and the production of individualized products at high costs. Flexible mass production with modularly designed products, component commonality and order-related production should be the solution to this dilemma. In addition, manufacturing companies are encouraged by social and legal requirements, but also for economic reasons, to take back their used products and remanufacture them. Products with a modular design are suitable for remanufacturing. In this work, a closed-loop supply chain with remanufacturing is examined: Products are returned by customers after use and can be processed in such a way that the components they contain are as good as new and used instead of externally procured components for the order-related manufacture of as-new modular products. Subsequently, a mathematical model for planning this closed-loop supply chain is developed.
First, supply chains with reverse product flows are systematically analyzed in order to work out the special planning requirements and thus specifications for the mathematical modeling of the decision problem examined in this work. Quantitative methods for decision support are presented. However, these methods are not suitable for the decision problem of this work because they neglect special planning requirements in the modeling. The facility location problem is one such method; this model and the planning of supply chains using this model are discussed critically. A facility location problem for planning a closed-loop supply chain from the literature is corrected and solved for an example from the copier industry. The solutions show which problems arise from the inadequate mathematical mapping. Building on this knowledge the facility location problem will be expanded step by step. This procedure shows which new findings and improvements can be achieved through the further developed modeling of the decision problem.
First of all, the facility location problem is expanded to include production planning with remanufacturing. The solutions for the example from the copier industry show that the mutual dependencies between location, transport and production planning in the supply chain are recorded. In addition, supplier locations and quantities are now considered in the planning. Then the modeling approach is expanded to include (volume) capacity planning and divided into a multi-period planning horizon. Now, the capacity is optimally determined together with the locations as well as the transport, procurement and processing quantities. The solutions prove that now high overcapacities are prevented and the relationship between transport and storage quantities is mapped with site capacities. Furthermore, the influence of product life cycles, customer usage duration of products and product design can now be examined. It can also be observed that the redistribution of production input is optimal under certain conditions. Since production with remanufacturing is labor-intensive, workforce planning must also be included in the modeling. This means that wage costs, processing times and the working hours available at the location are taken into account in the optimization. This planning is further improved by a differentiated modeling of the decision times. This results in a mathematical model that plans the location, capacity, transport, production and workforce of the closed-loop supply chain combined with their respective medium and long-term decision points. In this way, the influence of seasonally fluctuating demand on the supply chain, in particular on capacities, can be examined. With this detailed modeling, the capacity requirement can be determined more precisely and the recording of costs compared to the facility location problem is improved. Consequently, a detailed mathematical mapping of the decision problem is required so that recommendations for economically reasonable measures result.
First, supply chains with reverse product flows are systematically analyzed in order to work out the special planning requirements and thus specifications for the mathematical modeling of the decision problem examined in this work. Quantitative methods for decision support are presented. However, these methods are not suitable for the decision problem of this work because they neglect special planning requirements in the modeling. The facility location problem is one such method; this model and the planning of supply chains using this model are discussed critically. A facility location problem for planning a closed-loop supply chain from the literature is corrected and solved for an example from the copier industry. The solutions show which problems arise from the inadequate mathematical mapping. Building on this knowledge the facility location problem will be expanded step by step. This procedure shows which new findings and improvements can be achieved through the further developed modeling of the decision problem.
First of all, the facility location problem is expanded to include production planning with remanufacturing. The solutions for the example from the copier industry show that the mutual dependencies between location, transport and production planning in the supply chain are recorded. In addition, supplier locations and quantities are now considered in the planning. Then the modeling approach is expanded to include (volume) capacity planning and divided into a multi-period planning horizon. Now, the capacity is optimally determined together with the locations as well as the transport, procurement and processing quantities. The solutions prove that now high overcapacities are prevented and the relationship between transport and storage quantities is mapped with site capacities. Furthermore, the influence of product life cycles, customer usage duration of products and product design can now be examined. It can also be observed that the redistribution of production input is optimal under certain conditions. Since production with remanufacturing is labor-intensive, workforce planning must also be included in the modeling. This means that wage costs, processing times and the working hours available at the location are taken into account in the optimization. This planning is further improved by a differentiated modeling of the decision times. This results in a mathematical model that plans the location, capacity, transport, production and workforce of the closed-loop supply chain combined with their respective medium and long-term decision points. In this way, the influence of seasonally fluctuating demand on the supply chain, in particular on capacities, can be examined. With this detailed modeling, the capacity requirement can be determined more precisely and the recording of costs compared to the facility location problem is improved. Consequently, a detailed mathematical mapping of the decision problem is required so that recommendations for economically reasonable measures result.
Subjects
Closed Loop Supply Chain
Reverse Logistik
Diskretes Standortplanungsmodell
Refabrikation
Kapazitätsplanung
Intra Transport
Flexible Massenfertigung
Auftragsbezogene Fertigung
Modularisierung
Komponentengemeinschaft
Produktlebenszyklus
Optimization
Supply Chain Management
Reverse Logistics
Facility Location Problem
Remanufacturing
Capacity Planning
Mass Customization
Assemble to Order
Modularisation
Component Commonality
Product Life Cycle
Design Based Research
Cradle to Cradle
DDC Class
330: Wirtschaft
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Steinke_Leena_Optimierung-geschlossener-Wertschoepfungskreislaeufe-bei-beschraenkten-Kapazitaeten.pdf
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