OPUS documents https://opus.constructor.university/index/index/ Thu, 26 Aug 2021 11:16:33 +0200 Thu, 26 Aug 2021 11:16:33 +0200 https://opus.constructor.university/frontdoor/index/index/docId/1003 Global manufacturing networks and the underlying global supply chains form the centerpiece of automotive production. Over the last decades, original equipment manufacturers established overseas plants in the course of their expansion strategy and employed so-called knocked-down supply chains to ship all parts pre-assembled and arranged in kits to them. The overseas plants have matured into fully-equipped plants by taking over value-adding processes. As a consequence, the global manufacturing networks have shifted their focus away from simplification toward performance. The underlying knocked-down supply chains, however, have not adapted and still feature high inventories, lead times and costs. Even though knocked-down supply chains play a key role in global manufacturing networks, they have not been integrated. It is not possible to evaluate their fit and to derive the requirements. Despite the intense effort to improve the performance in the factories, there is little research on improvement levers in the context of knocked-down supply chains. This Thesis intends to explore how knocked-down supply chains can be aligned with global manufacturing networks. It conducts a cross-case study to provide an overview of current knocked-down supply chains and global manufacturing networks. The Thesis develops an integrated framework that matches knocked-down supply chains and global manufacturing networks and identifies weak spots in supply chain performance. The Thesis then applies a two-fold approach. It explores the general working principle of knocked-down supply chains by means of intermodal transportation. Gaining impetus from lean management, the Thesis then identifies improvement levers and subsequently evaluates their effect on knocked-down supply chains. The Thesis shows that the supply chain performance of knocked-down supply chains and thus the fit with the global manufacturing network can be improved. Toni Erfurth doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/1003 Thu, 26 Aug 2021 11:16:33 +0200 https://opus.constructor.university/frontdoor/index/index/docId/914 Commonly, methods applied in production planning may lead to production orders flowing across similar sequences of machines within similar periods of time. However, within such spatiotemporal neighbourhoods, interdependency effects among production orders may arise, causing compounding delays. The importance of anticipating interdependencies amongst production orders during production planning is key to accurately predict logistics performance such as lead time or expected delays. This is a challenging task for production planners, as interdependencies arise during operations, are difficult to foresee, and can be caused by a multitude of different factors. Only little research has been carried out to establish a generic and measurable understanding of the root-causes of interdependencies in manufacturing systems. In other research areas, such interdependency effects are explored as a key impact factor on system performance. Particularly in physics, research on granular matter systems has led to the development of multiple theories and concepts of particle-particle interactions, summarised here as Granular Matter Theory (GMT). In this thesis, we draw on these concepts in order to define and measure interdependency effects for manufacturing systems and discover a negative relation between to logistics performance indicators. Furthermore, we provide first evidence on some structural and non-structural impact factors that drive such effects and derive recommendations for practitioners in production planning. Victor Vican doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/914 Tue, 02 Jun 2020 12:03:49 +0200 https://opus.constructor.university/frontdoor/index/index/docId/783 Based on the research question how to improve traffic in longer tidal waterways in terms of efficiency and risk mitigation, it is the objective of this PhD Thesis to approach an analysis towards the optimization of the Vessel Traffic Management (VTM) in longer tidal waterways. The theoretical relevance is the result of a lack of research to model, e.g. the sequence of vessels in waterways, for optimizing the entire traffic flow. The practical relevance is shown by using the River Elbe of the Port of Hamburg as an exemplary subject of interest for longer tidal waterways, because it is argued that the River Elbe is the most complicated river in Europe. Its dynamics and uncertainties of the waterway with recent developments in vessel sizes makes the traffic organisation more complex so that the VTM should be adapted to these increased challenges to support efficiency and safety. It is discussed by using the framework of Systems Engineering that such an adaptation needs a holistic perspective and must comprise the positioning of the problem-solving capacity of the current VTM organization regarding the external requirements in terms of the complexities of the system. Therefore, the development of a generic model is needed that can serve as the basic for a computer-based traffic prediction and management for the support of decision-making within a system of increasing complexity. To develop such a generic model, expert interviews are selected as the research methodology for the empirical data collection. The empirical data collections confirm that an overarching comprehensive system which is consistent and reliable is needed. With the help of the framework of the Business Process Modelling (BPM), the entire waterway-traffic-environment-system of the Rive Elbe is depicted and illustrated. The analysis of these process diagrams helps moving towards creating a precise system and optimizing the complexity of it. As a result, a conceptual model is outlined. Ilknur Colmorn doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/783 Thu, 01 Feb 2018 14:52:44 +0100 https://opus.constructor.university/frontdoor/index/index/docId/776 The distribution of control capabilities and functions among autonomous system components has attracted extensive research in the fields of logistics and production planning & control (PPC). Their emergent nature, however, renders much of the traditional, reductionist knowledge about the design of manufacturing systems and their control void, opening a gap in the understanding that is already threatening the industrial adoption of distributed PPC approaches. The current thesis addresses this particular research gap. It is driven in especially by the frequently expressed hypothesis that a combination of classical, centralized production control and new, distributed forms can yield optimal performance. This hypothesis is explored through a combination of interdisciplinary literature review and minimal model investigations. Cellular Automata on networks of different structure are applied to investigate the role of control network hierarchy on the performance of agents in simple, distributed problem solving settings, finding not only a performance peak at “medium” levels of hierarchy, but also developing a mechanistic understanding for it. The second quantitative model borrows from findings in algorithmic game theory to explore how the emergent behavior of selfish agents can be reconciled with the established ideal in manufacturing system design to set target utilization levels for machines. The findings of this thesis support a design approach for distributed Production Planning & Control (PPC) systems based on evidence and analysis, instead of experience and experimentation. It enhances our understanding of the success factors of distributed control in production environments and beyond. It can advance the development of “emergence engineering” by providing a deeper understanding of the target-driven design of Complex Adaptive System (CAS). Henning Blunck doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/776 Fri, 19 Jan 2018 14:16:58 +0100 https://opus.constructor.university/frontdoor/index/index/docId/760 The term ‘synchronization’ in manufacturing refers to the provision of the right components to the subsequent production steps at the right moment in time. It is assumed that synchronization is beneficial to the logistics performance (LP) of manufacturing systems (MS). However, in the field of natural sciences synchronization is seen as the adjustment of rhythms due to interaction and it has been shown that synchronization phenomena can be detrimental to systems in which they emerge. Hence, the aim of this thesis is to investigate how synchronization can be explored to achieve better LP in MS. In a first step, a formal quantification and holistic understanding of the types of synchronization phenomena emerging in MS is established by transferring knowledge from the field of natural sciences. Further, an analysis of real-world production data and a discrete-event simulation study are applied to investigate the cause-and-effect relationships between the MS properties and synchronization emergence as well as LP. Two distinct synchronization types occurring in MS are defined, logistics and physics synchronization, and appropriate quantification measures for each of them are developed. Moreover, both structural and dynamic MS parameters are identified as factors triggering synchronization emergence in MS. Network properties of the material flow network (structural property) as well as processing time variability and workload level (dynamic properties) are found to influence emergence. Furthermore, the investigation of synchronization’s relation to LP shows that it is not straightforward and depends on different factors. Four LP indicators are studied: short throughput times, low WIP levels, high due date performance (DDP) and high capacity utilisation. It is shown that both logistics and physics synchronization phenomena relate positively to LP in most cases. However, depending on the MS and the specific DDP measure, for example, they can also have negative effects. Stanislav Chankov doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/760 Thu, 16 Nov 2017 12:51:48 +0100 https://opus.constructor.university/frontdoor/index/index/docId/755 Eugenia Rosca doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/755 Thu, 02 Nov 2017 08:31:26 +0100 https://opus.constructor.university/frontdoor/index/index/docId/739 Today’s supply chains are increasingly global and interconnected while aiming at the same time to lower inventory levels and shorten lead times. This combination makes supply chains more vulnerable to disruptions. In addition, both the number and the severity of supply chain disruptions are increasing. Recovering from supply chain disruptions represents a major challenge for supply chain professionals. There is a lack of research on collaborative networks and their abilities to combine resources after a disruption occurred. Overall, there is a need for a reactive risk management method which meets the framework conditions and addresses the research gaps. By collaborating during disruption recoveries, i.e. leveraging the resources available in their networks, supply chains can recover from disruptions quicker than competing supply chains. This research aims at analysing the relation between collaborative resource sharing and supply chain resilience. It builds on the relational view as a theoretical foundation. Based on extensive literature review, multiple case studies and expert interviews, a framework of collaborative recovery is developed. It incorporates promoting factors, types and effects of collaborative resource sharing. To test the framework, structural equation modeling is conducted with 216 data sets from a survey. The study shows that the sharing of both human resources and production resources during disruption recoveries has a positive effect on supply chain resilience. Supply chains recover faster than competing supply chains and gain a collaborative advantage. Trust and commitment are identified as main promoting factors of collaborative resource sharing. Dependency indirectly influences collaborative resource sharing through trust and commitment. These empirical findings have implications for supply chain and risk managers. In addition, advancements in the relational view theory are made. Marie Brüning doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/739 Fri, 22 Sep 2017 12:50:09 +0200 https://opus.constructor.university/frontdoor/index/index/docId/697 The tasks of steel production planning and control have a major impact on the logistics target achievement and therefore on the competitiveness of the company. The planning process is known to be extremely difficult, with various incompatible local constraints at the different production stages. As a consequence, only limited amount of constraints can be respected in higher planning levels. Detailed production planning at the different production stages has the task to derive production programs that are able to respect all local constraints and at the same time lead to appropriate target achievement. Current approaches developed for detailed continuous casting planning are not able to quickly provide alternative solutions and therewith enable decision support for conflicting objectives. Within this thesis, the detailed continuous casting problem is presented in detail. A new approach to decompose the problem is described. With this decomposition, the problem can be treated as a single machine scheduling problem and effective meta heuristics developed for similar problems can be exploited. Further, with the chosen decomposition it is possible to respect the consumption of hot metal within the scheduling of charges. This important practical constraint could not be respected within the continuous casting problem in the past. Besides the hot metal consumption, setup families and maximum batch sizes are considered in the scheduling model. MILP models are presented for the different extensions of the basic scheduling model. A iterated local search procedure is presented and the effective is shown based on the comparison with a commercial solver. The findings obtained from the scheduling research is transferred into a decision support system for the detailed continuous casting planning. Based on an industry case study, the application of the developed tool is presented on a real industry situation. Oliver Herr doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/697 Fri, 10 Mar 2017 14:57:23 +0100 https://opus.constructor.university/frontdoor/index/index/docId/648 Today's manufacturing companies are faced with a large number of fluctuating influence factors, as supply chains in the production environment grow larger with more suppliers and highly sophisticated products. At the same time, throughput times and due date reliability need to stay on a stable level, to fulfill the expectations of short delivery times and high service-levels of increasingly demanding customers. This ability to maintain specific features or a certain performance when subject to fluctuations and disturbances is generally referred to as robustness. As explained above, robustness of performance indicators, such as due date reliability, is a desirable characteristic for producing companies, hence the question arises how it can be achieved or incorporated in a companies manufacturing system. Looking at other scientific disciplines, such as biology or complex network science, robustness of the respective systems is often caused by redundancy, a situation where identical or similar components can replace each other when a component fails. In manufacturing research, redundancy has often been considered as an aspect to be avoided, as it stands in a potential trade-off with cost-efficiency, for example in lean manufacturing where excess inventory is considered as waste. However, as redundancy has been shown to have a strong relation to robustness in other disciplines, the aim of this thesis is to investigate the role that redundancy plays for achieving robustness of manufacturing system performance. Mirja Meyer doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/648 Tue, 15 Nov 2016 10:12:00 +0100 https://opus.constructor.university/frontdoor/index/index/docId/599 International Supply Networks (ISN) will compete with each other increasingly in the future through Cooperative Competitive Advantage (CCA) on the network level as a result of the cooperative interplays on the individual level. Therewith, a multilevel consideration is needed for investigating the potential emerging characteristics on the network level and the effects of an ISN on the company success that can be summarised in the following two research questions: What are CCA and what are the causal relations between an ISN and the company success? The theoretical relevance of these two research questions is the result of an identified gap of knowledge concerning definitions about CCA and a gap of knowledge about theoretical explanations in the meaning of cause-and-effect relations between ISN and the company success as well as assigning competitiveness to a whole ISN. With regard to the scientific modus operandi the Thesis comprises a complexity-based research model for hypothesizing the effects of the structural complexities on the network and the individual level, a Network Science-based Structural Equation Model with measurement models for the structural complexity, for CCA and for the company success and an empirical data set collected from secondary data containing over 55.000 supply relationships of the German automotive industry for the empirical validation. As a result of the computation with MATLAB, the falsifiable assumptions of the complexity-based research model cannot be completely statistically falsified but the directions of the causal relations are confirmed by trend so that first potential functional relations for the Strategic Complexity Management can be drawn. Consequently, the research contributes to scientific insights to that effect that an explanation approach is developed able to draw conclusions concerning the two research questions. Future research will focus on a deepening and widening of theoretical, methodological and empirical aspects. Richard Colmorn doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/599 Mon, 15 Aug 2016 12:15:17 +0200 https://opus.constructor.university/frontdoor/index/index/docId/510 The aim of PPC is to ensure the achievement of the logistic targets 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 of Manufacturing Control (LTS). Although the LTS was described as early as 1977, the cause-and-effect relationships in the LTS still have not been sufficiently investigated. Thus, this thesis has the overall target of investigating the influence of the LTS of manufacturing control on logistic target achievement by firstly validating the LTS line of argumentation by Mather & Plossl (1977) and secondly developing a roadmap to mitigate the LTS in practice. For the validation initially a mathematical model of LTS interactions by means of the Funnel Model and statistics is presented, which also enables determining the main triggers of the LTS. The insights are then validated and extended in a control theoretic model of the LTS and transferred into strategies to avoid or dampen the LTS. Finally, the derived propositions are evaluated and confirmed in a case study of a job-oriented manufacturing process. To develop a roadmap in the second step, the questions of when, how often, and on which value should planned lead times be adjusted are addressed. The results are finally transferred into a methodology to avoid the LTS in practice. In summary, this thesis validates the LTS line of argumentation and shows the relevance of the problem in today’s manufacturing systems. The roadmap finally transfers the results from theory into practice to support planners in the process of decision-making and prevent accidentally wrong adjustments that might lead to a decrease in performance. Mathias Knollmann doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/510 Mon, 22 Feb 2016 10:50:21 +0100 https://opus.constructor.university/frontdoor/index/index/docId/389 The accuracy of logistic performance becomes more and more a crucial factor for the competiveness of enterprises. Even small advantages decide on economic success or failure. Therefore, companies collect data at an increasing level of detail in order to gain more knowledge about in-depth manufacturing processes and their dynamics, serving as a basis for the adjustment of Production Planning and Control. In traditional logistics, the application of conventional statistical methods for the analysis of manufacturing data has led to formidable improvements of the achievements of logistic objectives. In order to reduce complexity, these traditional approaches rely on greatly simplified models, mostly based on averaging. In order to evaluate data on a higher level of detail for further logistic improvements, actual analyses of manufacturing data more and more include advanced statistical methods, such as Knowledge Discovery in Databases (KDD) and Explorative Data Analysis (EDA). The scientific discipline of Auditory Display has been successfully established in EDA as counterpart to graphical statistics. More specifically known as data sonification, an auditory display is particularly suitable to analyze chronological events, such as the workflow of a production. In this fundamental research, Auditory Display has been applied to the analysis of manufacturing processes. A methodical transfer from logistic to sonic parameters has been developed in order to investigate the potential of sonifications for the identification of bottlenecks in a production workflow, also in regard to the impact of cross-system dynamics. The developed method enables trained analysts to identify systematic order- and process-related bottlenecks, their temporal dynamic evolutions, and their overall impact on schedule adherence of a production workflow. Michael Iber doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/389 Fri, 29 Jan 2016 10:13:36 +0100 https://opus.constructor.university/frontdoor/index/index/docId/37 Production logistics is the planning, scheduling, and control of all activities in a manufacturing system. The management of operations and logistics in manufacturing systems faces numerous challenges, caused by growth, diversity, dynamics and complexity. At the same time, conflicting targets further detain of a favorable solution. Biological concepts, often developed under the term bionics, promise a new perspective on solution approaches, e.g., in terms of organization principles or heuristics. Metabolic systems have already been recognized by scientists as particularly suited systems for a transfer, because they share numerous properties with logistic systems regarding structure, functions, and goals. However, a detailed analysis of even a proof of the systemic similarity is missing. Additionally, there is currently no foundation for a systematic or structured way of transferring concepts from metabolism to logistics due to the lack of a matching of elements, functions, and goals between the two systems. The result of this work is a network-based model that is able to represent material flow and control procedures in manufacturing systems as well as metabolite flow and metabolic regulation in metabolic systems, the proof of its feasibility by modeling flow networks using real company and metabolic data sets, and the use of measures from complex network theory to identify fundamental commonalities and differences between the two systems that can help creating new ideas for a transfer of concepts from metabolic systems to manufacturing systems. Till Becker doctoralthesis https://opus.constructor.university/frontdoor/index/index/docId/37 Thu, 19 Nov 2015 11:33:06 +0100