Pannek, Jürgen
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Pannek, Jürgen
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Pannek, Jürgen
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Item-typ:Veröffentlichung, Ein Lösungsverfahren für die integrierte Planung der Produktion in der Werkstattfertigung und den überbetrieblichen Transport(2017-04-19); ; ; Companies are forced to concentrate on their core competencies and a close collaboration with specialized partners in a supply chain due to the competitive situation on global markets. These partners often have different and conflictive goals. Thus, there is only an internal process optimisation and not an optimised planning result for the entire supply chain. Integrated planning is a supply chain management concept which enables a supply chain wide optimisation to reach the overall goals. The focus of this thesis is the integrated production and outbound distribution planning problem. Most of the existing planning methods in this research field are production or distribution oriented with a low integration level of these two suba problems. There is a need for conceptual and methodological support for solving this integrated planning problem. Thus, the overall objective of this thesis was the development of a new integrated planning method for the focused part of the supply chain with a high integration of suba problems and an improved performance. As a result of an intense analysis of the state of the art it can be stated that there are several gaps in the field of integrated planning of production and outbound distribution. Consequently, a number of secondary objectives were defined in order to fill the identified gaps. Two of these secondary objectives were the development of a system of objectives and the development of a representation scheme for classification of existing planning models for the integrated problem considered. Furthermore, it turned out that each of the existing solution methods uses an individual planning model. This prevents a comparison of accuracy and performance between different solution methods. Therefore, another secondary objective was the development of a unified planning model, which was further used for evaluation regarding performance and stability of planning results. The developed integrated planning method is based on a framework, which was also developed in this thesis. The main characteristics of the framework is a multia stage decomposition and integration procedure of the suba problems production and distribution scheduling. The integrated planning method applies this new multia stage structure for the problem solving process and uses already known solution methods to solve the respective suba problems. A real world oriented scenario was used to demonstrate the performance of the developed method. The evaluation shows that the overall costs of planning results generated by solution methods are up to 26% higher than the overall costs of the planning results generated by the developed integrated solution method. Furthermore, in a sensitivity analysis was shown that there is a positive impact on overall costs applying the integrated solution method developed within a wide range of cost parameters. Moreover, the general working principle of the frameworks shows a high flexibility regarding the solution methods to be defined and thus a simple transferability and application in a specific scenario in the field of integrated planning of production and outbound distribution.Dissertation985 650 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Decentralized Robust Capacity Control of Job Shop Systems with Reconfigurable Machine Tools(2019-07-09); ; ; Manufacturing companies are confronted with various challenges from the perspective of customers individual requirements concerning variations of types of products, quantities and delivery dates. This renders the manufacturing process to be more dynamic and complex, which may result in bottlenecks and unbalanced capacity distributions. To cope with these problems, capacity adjustment is an effective approach to balance capacity and load for short or medium term fluctuations on the operational layer. Particularly, new technologies and algorithms need to be developed for the implementation of capacity adjustment. Reconfigurable machine tools (RMTs) and operator-based robust right coprime factorization (RRCF) provide an opportunity for a new capacity control strategy. Therefore, the main purpose of the research is to develop an effective machinery-oriented capacity control strategy by incorporating RMTs and RRCF for a job shop system to deal with volatile customer demands.Dissertation943 709 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Nonlinear Model Predictive Control for Industrial Manufacturing Processes with Reconfigurable Machine Tools(2019-07-18); ; ; Manufacturing companies are faced with challenges to respond to volatile market demands quickly and flexibly while maintaining a cost-effective level of production. Instead of flexible working times, we adopt Reconfigurable Machine Tools (RMTs) to compensate for unpredictable events in case of bottleneck. To include these tools effectively on the operational layer, we propose a complementing feedback approach using model predictive control (MPC) together with genetic algorithm and branch and bound to achieve a better compliance with logistics objectives and a sustainable demand oriented capacity allocation. Further, the system stability is guaranteed by a trajectory-based unconstrained MPC scheme associated with the principle of flexible Lyapunov functions. The effectiveness and plug-and-play availability of the proposed method is demonstrated via a four-workstation job-shop system, which shows that the work in process can be practically asymptotically stabilized by usage of RMTs.Dissertation929 624 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, A flexible integrated forward/reverse logistics model with random path(2019-02-04); ; ; This dissertation focuses on the structure of a particular logistics network design problem, one that is a major strategic issue for supply chain design and management. Nowadays, the design of the supply chain network must allow for operation at the lowest cost, while providing the best customer service and accounting for environmental protection. Due to business and environmental issues, industrial players are under pressure to take back used products. Moreover, the significance of transportation costs and customer satisfaction spurs an interest in developing a flexible network design model. To this end, in this study, we attempt to include this reverse flow through an integrated design of a forward/reverse supply chain network design, that avoids the sub-optimal solutions derived from separated designs. We formulate a cyclic, seven-stage, logistics network problem as an NP-hard mixed integer linear programming (MILP) model. This integrated, multi-stage model is enriched by using a complete delivery graph in forward flow, which makes the problem more complex. As these kinds of problems belong to the category of NP-hard problems, traditional approaches fail to find an optimal solution in sufficiently short time. Furthermore, considering an integrated design and flexibility at the same time makes the logistics network problem even more complex, and makes it even less likely, if not impossible, for a traditional approach to provide solution within an acceptable time frame. Hence, researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near optimal solutions particularly for large scale test problems. In our case within this thesis, to find a near optimal solution, we apply a Memetic Algorithm with a neighborhood search mechanism and a novel chromosome representation called "extended random path direct encoding method" which includes two segments. Chromosome representation is one of the main issues that can affect the performance of a Memetic Algorithm. To illustrate the performance of the proposed Memetic Algorithm, LINGO optimization software as commercial package serves as a comparison for small size problems. We show that the proposed algorithm is able to efficiently find a good solution for the flexible, integrated, logistics network. Each algorithm has some parameters that need to be investigated to provide the best performance. In this regard, the effect of different parameters on the behavior of the proposed meta-heuristic algorithm is surveyed first. Then, the Taguchi method is adapted to identify the most important parameters and rank the latter. Additionally, Taguchi method is applied to identify the optimum operating condition of the proposed Memetic Algorithm to improve the results. In this study, four factors that are defined inputs of the proposed Memetic Algorithm, namely: population size, cross over rate, local search iteration, and number of iterations are considered. The analysis of the parameters and the improvement in results are both illustrated by a numerical case studies. Finally, to show the performance of the Memetic Algorithm, a Genetic Algorithm - as a second meta-heuristic algorithm option - is considered as regards large size cases.Dissertation1056 386